Section 4 Future Mobility

**153**

**Chapter 7**

**Abstract**

service (MaaS)

**1. Introduction**

Trends

Future Mobility Advances and

*Michela Longo, Wahiba Yaïci and Federica Foiadelli*

mobility models in order to meet new emerging needs.

The trends of main interest on a global scale are those that can influence the development of humanity in the long term and are sometimes referred to as megatrends. The changes they bring with them can span several generations, profoundly changing society and, consequently, the competitive landscape of companies. The megatrends are numerous and each one involves the development of entire areas of activity. It is important to identify the megatrends of interest for strategic mobility planning and follow their developments, in order to consider them in the planning processes and correctly pilot investments. Megatrends are made possible and also influenced by the offer of new technologies, and lead to changes in cultural models. This chapter shows an era characterized by major technological innovations that are changing people's ways of thinking and acting, with the establishment of new

**Keywords:** transportation system, smart mobility, electric vehicle, mobility as a

The transport sector acquires a key role in promoting a correct balance between the different components of sustainable development. On the one hand, in fact, the mobility of people and goods and the conditions with which it is met (times, price, safety, reliability) decisively influence the present and future competitiveness of production and territorial systems, and, jointly, the accessibility to a series of basic functions within modern societies: work activities, educational services, social and health services, leisure and recreational activities, etc. [1, 2]. It therefore represents a fundamental component of the economic and social dimension of sustainable development [3, 4]. On the other hand, the quantitative evolution of demand volumes and the relative modal shares is at the basis of important critical issues from the point of view of eco-compatibility and security of supply, or two essential determinants of the concept of intergenerational equity that is at the basis of sustainable development [5, 6]. The inability to completely dissociate the demand for transport from the evolution of economic indicators and the almost absolute preponderance of fossil fuels in satisfying it have in fact led to a continuous increase in the contribution of transport to climate-altering gas emissions in recent decades and, at the same time, to increase the vulnerability of present consumption trends with respect to the exhaustion of non-renewable resources and dependence on foreign countries [7, 8]. In this scenario, transport policy becomes a decisive hub for achieving global environmental commitments, including those envisaged by the Kyoto Protocol and

#### **Chapter 7**

## Future Mobility Advances and Trends

*Michela Longo, Wahiba Yaïci and Federica Foiadelli*

#### **Abstract**

The trends of main interest on a global scale are those that can influence the development of humanity in the long term and are sometimes referred to as megatrends. The changes they bring with them can span several generations, profoundly changing society and, consequently, the competitive landscape of companies. The megatrends are numerous and each one involves the development of entire areas of activity. It is important to identify the megatrends of interest for strategic mobility planning and follow their developments, in order to consider them in the planning processes and correctly pilot investments. Megatrends are made possible and also influenced by the offer of new technologies, and lead to changes in cultural models. This chapter shows an era characterized by major technological innovations that are changing people's ways of thinking and acting, with the establishment of new mobility models in order to meet new emerging needs.

**Keywords:** transportation system, smart mobility, electric vehicle, mobility as a service (MaaS)

#### **1. Introduction**

The transport sector acquires a key role in promoting a correct balance between the different components of sustainable development. On the one hand, in fact, the mobility of people and goods and the conditions with which it is met (times, price, safety, reliability) decisively influence the present and future competitiveness of production and territorial systems, and, jointly, the accessibility to a series of basic functions within modern societies: work activities, educational services, social and health services, leisure and recreational activities, etc. [1, 2]. It therefore represents a fundamental component of the economic and social dimension of sustainable development [3, 4]. On the other hand, the quantitative evolution of demand volumes and the relative modal shares is at the basis of important critical issues from the point of view of eco-compatibility and security of supply, or two essential determinants of the concept of intergenerational equity that is at the basis of sustainable development [5, 6]. The inability to completely dissociate the demand for transport from the evolution of economic indicators and the almost absolute preponderance of fossil fuels in satisfying it have in fact led to a continuous increase in the contribution of transport to climate-altering gas emissions in recent decades and, at the same time, to increase the vulnerability of present consumption trends with respect to the exhaustion of non-renewable resources and dependence on foreign countries [7, 8]. In this scenario, transport policy becomes a decisive hub for achieving global environmental commitments, including those envisaged by the Kyoto Protocol and

subsequent developments, as well as the objectives of the Community energy policy. The sectoral dynamics also determine effects characterized by a particular territorial connotation, which assumes specific importance at the level of urban areas, where a preponderant share of movements are carried out and where, consequently, a series of characterizing problems are concentrated: delays due to congestion, employment of soil and competition with other uses (homes, commercial activities, nonmotorized vehicles, green spaces), local pollution emissions and greater exposure of targets (people and things), visual and landscape intrusion [9, 10]. The management of choices and the ability to change the trends experienced up to now become in this scenario one of the essential components of urban sustainability policies, decisively influencing the quality of life and the overall level of attractiveness of cities. The need to attribute a specific value to transport, both in Ref. to global issues (climate change, energy dependence) and to those related to the local dimension (congestion, atmospheric pollution, noise, etc.), finds recognition in the European Development Strategy Sustainable [11, 12], which identifies the ability to promote a model of "sustainable transport" as one of the seven key challenges that the European system must face in the future.

A challenge based as for the other economic and social sectors, on the affirmation and diffusion of new technological solutions in the production/consumption patterns, but also, if not above all, on the recognition of the need to assign a transversal value to the mobility issue and related choices of satisfaction within the various sectoral policies (trade, industrial logistics, tourism, planning and management of the territory, etc.) in order to pursue the first (and functional to all the others) operational objective, or the dissociation of volumes of demand from economic growth.

### **2. New paradigms of society**

In a constantly changing society there are three fundamental aspects that need to be considered:


According to [13, 14] it emerged that in 2050 two thirds of the world population will live in urban areas (over six billion people); the total amount of urban kilometers traveled will triple compared to the current situation; the costs for urban mobility will amount to over 800 billion per year; over 17% of the planet's biocapacity will be used for urban mobility. In addition, regarding the urban distribution of goods [15, 16] between 2006 and 2014 the number of commercial vehicles in the world went from

**155**

concept of E-mobility.

*Future Mobility Advances and Trends*

• Artificial intelligence;

• Autonomous vehicles;

• Big data and data analytics;

• 5G, connected vehicles (V2X);

• Technologies for Blockchain transactions.

• Electric mobility;

impact on mobility services.

**3. E-mobility**

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

Some of interest for mobility may be:

250 to 330 million, mainly due to e-commerce; e-commerce turnover volumes are estimated to increase by 85% between 2015 and 2020 [17]. The demand for mobility of people and goods in urban areas has grown and is destined to increase further and it will not be possible to satisfy it by increasing the infrastructure. It will be necessary to switch to a disruptive technology that is the type of innovation that is considered when it quickly and radically changes a market or the ways in which to operate in it.

• Internet of Things (IoT) and Internet of Everything (IoE);

Widely available over the next decade, these technologies will have a profound

The transport sector, with particular reference to the passenger car segment, being one of the main contributors to CO2 emissions, must undergo substantial improvements in environmental efficiency. Vehicle electrification is often seen as the primary option to help achieve this goal. Although electrification is a recurring theme in the history of the automotive industry, in recent years some changes in the reference context have opened up new development opportunities for electric vehicles: the phenomenon of climate change, the increase in oil prices and the long-term oil shortages, major technological innovations in sectors relevant to the automotive industry (e.g. in the battery industry), pressures to introduce innovations in the automotive sector and the response of manufacturers to the requirements contained in European legislation for reduction of carbon emissions [18, 19]. E-Mobility has become a keyword. Refers to vehicles that use electricity as their main source of energy, with the possibility of recharging the battery by connecting with an outlet to the electrical network, regardless of whether the vehicles are equipped with an auxiliary internal combustion engine to be used in long journeys distances or to keep the battery charged (battery electric vehicles, plug-in hybrid electric vehicles and extended range electric vehicles). This system is not limited only to passenger cars, but also covers motorized two-wheeled vehicles, quadricycles, vans, etc. E-Mobility currently dominates the debate on the future of transport and is becoming popular with policy makers, research institutes and industry. National and local authorities are already providing support for the introduction of these low-carbon vehicles, granting them special tax treatments or favoring their use, compared to conventional cars, with other measures (parking facilities, access to traffic areas limited use of preferential lanes, etc.). **Figure 1** illustrates the

*Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

must face in the future.

economic growth.

to be considered:

**2. New paradigms of society**

subsequent developments, as well as the objectives of the Community energy policy. The sectoral dynamics also determine effects characterized by a particular territorial connotation, which assumes specific importance at the level of urban areas, where a preponderant share of movements are carried out and where, consequently, a series of characterizing problems are concentrated: delays due to congestion, employment of soil and competition with other uses (homes, commercial activities, nonmotorized vehicles, green spaces), local pollution emissions and greater exposure of targets (people and things), visual and landscape intrusion [9, 10]. The management of choices and the ability to change the trends experienced up to now become in this scenario one of the essential components of urban sustainability policies, decisively influencing the quality of life and the overall level of attractiveness of cities. The need to attribute a specific value to transport, both in Ref. to global issues (climate change, energy dependence) and to those related to the local dimension (congestion, atmospheric pollution, noise, etc.), finds recognition in the European Development Strategy Sustainable [11, 12], which identifies the ability to promote a model of "sustainable transport" as one of the seven key challenges that the European system

A challenge based as for the other economic and social sectors, on the affirmation and diffusion of new technological solutions in the production/consumption patterns, but also, if not above all, on the recognition of the need to assign a transversal value to the mobility issue and related choices of satisfaction within the various sectoral policies (trade, industrial logistics, tourism, planning and management of the territory, etc.) in order to pursue the first (and functional to all the others) operational objective, or the dissociation of volumes of demand from

In a constantly changing society there are three fundamental aspects that need

• Sharing (sharing economy): resources, especially if in excess, will be shared with others ("prosumer", from consumer to producer of services). The demand will increasingly be oriented towards the use of shared services (in the United States car owners have drastically decreased: from 74% of Generation X, born

• Information (big data and data analytics): there will be large amounts of data available from which to extract information, also to offer new services. Those

• Supply of customizable and integrated services: the services will be customizable on the basis of demand, integrating those also provided by different subjects (providers). These trends will change the characteristics of the demand

According to [13, 14] it emerged that in 2050 two thirds of the world population will live in urban areas (over six billion people); the total amount of urban kilometers traveled will triple compared to the current situation; the costs for urban mobility will amount to over 800 billion per year; over 17% of the planet's biocapacity will be used for urban mobility. In addition, regarding the urban distribution of goods [15, 16] between 2006 and 2014 the number of commercial vehicles in the world went from

who can use the data will enjoy enormous competitive advantages.

between 1960 and 1975, it has gone to 48% of Millennials).

and supply of services also in the field of mobility.

**154**

250 to 330 million, mainly due to e-commerce; e-commerce turnover volumes are estimated to increase by 85% between 2015 and 2020 [17]. The demand for mobility of people and goods in urban areas has grown and is destined to increase further and it will not be possible to satisfy it by increasing the infrastructure. It will be necessary to switch to a disruptive technology that is the type of innovation that is considered when it quickly and radically changes a market or the ways in which to operate in it.

Some of interest for mobility may be:


Widely available over the next decade, these technologies will have a profound impact on mobility services.

#### **3. E-mobility**

The transport sector, with particular reference to the passenger car segment, being one of the main contributors to CO2 emissions, must undergo substantial improvements in environmental efficiency. Vehicle electrification is often seen as the primary option to help achieve this goal. Although electrification is a recurring theme in the history of the automotive industry, in recent years some changes in the reference context have opened up new development opportunities for electric vehicles: the phenomenon of climate change, the increase in oil prices and the long-term oil shortages, major technological innovations in sectors relevant to the automotive industry (e.g. in the battery industry), pressures to introduce innovations in the automotive sector and the response of manufacturers to the requirements contained in European legislation for reduction of carbon emissions [18, 19].

E-Mobility has become a keyword. Refers to vehicles that use electricity as their main source of energy, with the possibility of recharging the battery by connecting with an outlet to the electrical network, regardless of whether the vehicles are equipped with an auxiliary internal combustion engine to be used in long journeys distances or to keep the battery charged (battery electric vehicles, plug-in hybrid electric vehicles and extended range electric vehicles). This system is not limited only to passenger cars, but also covers motorized two-wheeled vehicles, quadricycles, vans, etc. E-Mobility currently dominates the debate on the future of transport and is becoming popular with policy makers, research institutes and industry. National and local authorities are already providing support for the introduction of these low-carbon vehicles, granting them special tax treatments or favoring their use, compared to conventional cars, with other measures (parking facilities, access to traffic areas limited use of preferential lanes, etc.). **Figure 1** illustrates the concept of E-mobility.

#### **Figure 1.** *Concept of E-mobility.*

The transition from a conventional to an electric car is not automatic, especially if users are not actively involved in the process and if they are not assisted in understanding the meaning and advantages of these new technologies [20, 21]. It is still necessary to overcome not only some major uncertainties in the market, which affect the propensity to buy and consumer behavior (regarding costs, autonomy and viability of electric mobility), but also delicate political issues. The Authorities should favor the development of e-Mobility without creating market distortions, adopting a principle of technological neutrality: the incentives should be linked to performance in carbon emissions ("from well-to-wheels") and not to a specific technology. Furthermore, the incentives should not further aggravate overall energy taxation; the spread of electric vehicles should be linked to the use of renewable energy (with a positive environmental impact "from the well to the wheels"); Standardization Bodies and the industrial sector should agree, adopting common standards and protocols regarding the systems and devices for recharging batteries and the communication and information systems associated with them.

However, also with the aim of reducing CO2 emissions by improving the efficiency of internal combustion engines (e.g. by reducing vehicle weight and engine power) and by increasing the use of alternative fuels (methane, biodiesel, etc.), electric vehicles could be an important way to improve individual mobility while minimizing emissions, representing a major challenge for European industries. The development of electric mobility, in fact, will depend not only on the adoption of specific technologies, but also on the ability to organize and manage the activities of different actors: automotive industry, battery manufacturers, mobility service providers, energy suppliers and distributors [22, 23].

It is important to understand the mobility needs and the types of demand that electric vehicles can meet and the performance they can offer to families compared to cars with internal combustion engines. Excluding future advances that may allow the capacity of electric vehicles to be increased, the latter currently offer a limited range compared to traditional cars, with the possibility of quick recharging only by replacing the battery. Therefore, electric vehicles are better suited for travel in urban areas and over short distances. This need not necessarily be a handicap once consumers understand the difference between battery electric vehicles and conventional vehicles, and the benefits the former can offer: zero emissions "from tank to wheels", affordable charging costs, flexibility in urban areas, etc. Electric vehicles offer consumers a wider choice to meet their mobility needs.

**157**

**Figure 2.**

*Example of connected vehicles.*

*Future Mobility Advances and Trends*

citizens and mobility.

up to answer this question.

**4. Connected and cooperative vehicles**

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

The important challenge is to be able to meet the different demand needs even if using different technologies. Therefore, the policies should guarantee the presence on the market of a differentiated mix of technologies. Meanwhile, hybrid vehicles currently on the market - including plug-in hybrids - offer a range comparable to vehicles with traditional engines. Alongside a diversification of the demand for mobility, there are also some changes in the use of the car. The high costs of batteries, current and predictable, associated with a limited range will continue to represent barriers to the purchase of electric vehicles. These difficulties could be mitigated through different mechanisms, such as car-sharing systems, corporate fleets and leasing. A conceptual change in the use of cars is observed, especially among young people: from an owned asset to an asset that can be rented only when necessary, such as is happening with bike-sharing services. Electric cars, such as electric motorcycles and bicycles, could reinforce this new relationship between

As a guideline, between 2025 and 2030 we could reach the breakeven point between the prices of electric cars (BEVs) and those with internal combustion power trains. All these will depend on the technological evolution of the accumulators; the growth in demand for batteries; the methods of their reuse and/or disposal; from access to raw materials to make them. As experiences in other countries (Denmark, Norway) show, the spread of electric-only vehicles is strongly linked to the availability of economic incentives. A widespread diffusion of the recharging network (columns) is fundamental. Dynamic inductive charging is being tested and it is not currently possible to understand if and when it will contribute to the spread of BEV power trains. The tendency to promote electric mobility in urban areas is shared by regulators. Technology providers are gearing

The technology for the highest levels of automation is already available, but it is nevertheless necessary to gradually prepare for the impact that the phenomenon will have on the way of using vehicles. Mobility understood as the ability of people to move, in the shortest possible time, with the least use of resources and at the same time reducing the environmental impact should be a strategic objective for the institutions, with a view to integrating public mobility systems and collective with those of private and individual mobility [24, 25]. Obviously, this integration is also related to the complex issue of traffic management, especially urban traffic and in this sense computer networks will tend to take on ever greater importance due

#### *Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

The transition from a conventional to an electric car is not automatic, especially

if users are not actively involved in the process and if they are not assisted in understanding the meaning and advantages of these new technologies [20, 21]. It is still necessary to overcome not only some major uncertainties in the market, which affect the propensity to buy and consumer behavior (regarding costs, autonomy and viability of electric mobility), but also delicate political issues. The Authorities should favor the development of e-Mobility without creating market distortions, adopting a principle of technological neutrality: the incentives should be linked to performance in carbon emissions ("from well-to-wheels") and not to a specific technology. Furthermore, the incentives should not further aggravate overall energy taxation; the spread of electric vehicles should be linked to the use of renewable energy (with a positive environmental impact "from the well to the wheels"); Standardization Bodies and the industrial sector should agree, adopting common standards and protocols regarding the systems and devices for recharging batteries

and the communication and information systems associated with them.

providers, energy suppliers and distributors [22, 23].

offer consumers a wider choice to meet their mobility needs.

However, also with the aim of reducing CO2 emissions by improving the efficiency of internal combustion engines (e.g. by reducing vehicle weight and engine power) and by increasing the use of alternative fuels (methane, biodiesel, etc.), electric vehicles could be an important way to improve individual mobility while minimizing emissions, representing a major challenge for European industries. The development of electric mobility, in fact, will depend not only on the adoption of specific technologies, but also on the ability to organize and manage the activities of different actors: automotive industry, battery manufacturers, mobility service

It is important to understand the mobility needs and the types of demand that electric vehicles can meet and the performance they can offer to families compared to cars with internal combustion engines. Excluding future advances that may allow the capacity of electric vehicles to be increased, the latter currently offer a limited range compared to traditional cars, with the possibility of quick recharging only by replacing the battery. Therefore, electric vehicles are better suited for travel in urban areas and over short distances. This need not necessarily be a handicap once consumers understand the difference between battery electric vehicles and conventional vehicles, and the benefits the former can offer: zero emissions "from tank to wheels", affordable charging costs, flexibility in urban areas, etc. Electric vehicles

**156**

**Figure 1.**

*Concept of E-mobility.*

The important challenge is to be able to meet the different demand needs even if using different technologies. Therefore, the policies should guarantee the presence on the market of a differentiated mix of technologies. Meanwhile, hybrid vehicles currently on the market - including plug-in hybrids - offer a range comparable to vehicles with traditional engines. Alongside a diversification of the demand for mobility, there are also some changes in the use of the car. The high costs of batteries, current and predictable, associated with a limited range will continue to represent barriers to the purchase of electric vehicles. These difficulties could be mitigated through different mechanisms, such as car-sharing systems, corporate fleets and leasing. A conceptual change in the use of cars is observed, especially among young people: from an owned asset to an asset that can be rented only when necessary, such as is happening with bike-sharing services. Electric cars, such as electric motorcycles and bicycles, could reinforce this new relationship between citizens and mobility.

As a guideline, between 2025 and 2030 we could reach the breakeven point between the prices of electric cars (BEVs) and those with internal combustion power trains. All these will depend on the technological evolution of the accumulators; the growth in demand for batteries; the methods of their reuse and/or disposal; from access to raw materials to make them. As experiences in other countries (Denmark, Norway) show, the spread of electric-only vehicles is strongly linked to the availability of economic incentives. A widespread diffusion of the recharging network (columns) is fundamental. Dynamic inductive charging is being tested and it is not currently possible to understand if and when it will contribute to the spread of BEV power trains. The tendency to promote electric mobility in urban areas is shared by regulators. Technology providers are gearing up to answer this question.

#### **4. Connected and cooperative vehicles**

The technology for the highest levels of automation is already available, but it is nevertheless necessary to gradually prepare for the impact that the phenomenon will have on the way of using vehicles. Mobility understood as the ability of people to move, in the shortest possible time, with the least use of resources and at the same time reducing the environmental impact should be a strategic objective for the institutions, with a view to integrating public mobility systems and collective with those of private and individual mobility [24, 25]. Obviously, this integration is also related to the complex issue of traffic management, especially urban traffic and in this sense computer networks will tend to take on ever greater importance due

**Figure 2.** *Example of connected vehicles.*

to the amount of useful information that can be exchanged and the possibility of crossing millions of data also in a predictive function. **Figure 2** shows an example of connected vehicles.

Expressions such as smart mobility and smart city are used to indicate intelligent infrastructural and mobility systems. With these terms we mean that set of logistics and transport systems that are supported and integrated by ICT. In particular, smart mobility refers to a new mobility model that uses new technologies for road safety and integrates information and innovations on board the vehicle to increase transport efficiency [26, 27].

Smart city does not mean, of course, digital city, even if in the past the tendency was to essentially make the two expressions coincide. The goal of the smart city is not digitization, which is instead an effective and flexible tool for improving many aspects of the quality of life of citizens and promoting the country's economic growth. The approach to the issue of smart cities brings with its undoubted elements of difficulty, just think of identifying the interventions to be carried out, their alignment with the economic and social context of the city and the assessment of the impact on the community, without considering that the various projects, once conceived, must be able to be effectively carried out in that specific urban and social context. It is possible to argue that a city can be defined as "smart" that is to say "intelligent" when, according to a strategic, integrated and organic vision, using ICT tools to improve the lives of its citizens, it uses real-time information from various areas and exploits both tangible (e.g. infrastructure, energy and natural resources) and intangible (e.g. human capital, knowledge) resources, adapting from time to time to the needs of users with a view to sustainable development [28, 29].

It was estimated that in 2020 approximately 75% of new vehicles were able to connect to the internet, thus accessing different services and potentially allowing the exchange of information with the infrastructure (V2I), with other vehicles (V2V) and, generalizing, with anyone (V2X) (for example for updates of on-board software (SW) or the acquisition of travel information by various service providers). **Figure 3** presents the different types of connections.

**159**

*Future Mobility Advances and Trends*

**5. Autonomous vehicles**

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

The spread of connected vehicles supports the adoption of increasingly high levels

The term autonomous refers to the ability and faculty to govern or stand alone. According to the NHTSA (National Highway Traffic Safety Administration), or the US government agency for road safety, it defines an autonomous car "*a vehicle whose operation takes place without direct intervention by the driver to control steering, acceleration and braking and which is designed in such a way that do not expect to constantly* 

In order to achieve a certain level of autonomy, the car exploits the ability to detect the surrounding environment through techniques such as radar, LIDAR, GPS and sensors. Therefore, the interaction between these components and the advanced control systems on board the car allows the latter to make decisions about the paths to follow and any obstacles and signals to monitor. To verify the degree of autonomy of the car, there are different classifications and standards coexisting with each other. The most adopted and followed by the scientific literature are the standard published by the NHTSA and the standard published by the SAE (a standardization body in the field of the automotive industry). In 2016, the NHTSA adopted the SAE J3016 standard, which therefore is configured as the reference standard. The latter has established six levels of autonomous driving that are based on the greater or lesser degree of automation of the vehicle, with the relative level of

• *Level 0*: No autonomy. The car does not have a driver assistance function and

• *Level 1*: Driving assistance. This level of automation requires the driver to make decisions as to when to accelerate, decelerate or steer but is informationally supported by other systems that may indicate the presence of hazards or adverse conditions. The car simply analyzes and represents situations in the form of visual or acoustic alerts. The driver has full responsibility for the

• *Level 2*: Partial automation. In this degree of automation, the car is able to manage acceleration and deceleration through different types of systems such as assisted braking and emergency anti-collision braking. The direction and

• *Level 3*: Conditional automation. In this level the car begins to automate. It is able to manage acceleration, deceleration and steering, while the driver intervenes in problematic situations such as driving on dirt roads or where

traffic control remain under the control of the driver.

*check the road, when the automatic mode is running*" [30, 31].

human participation in driving the car [32–34]:

the driver is in full control.

vehicle.

of automation (autonomous driving) and access to articulated mobility services offered by different subjects. Connected travelers and vehicles will become Internet of Things (IoT) or Internet of Everything (IoE) nodes. The demand for mobility will therefore be satisfied through a multimodal, on-demand, and shared offer. The consumer will have multiple offers, more choice between different service levels. Public and private operators will coexist. Vehicles and travelers, as nodes in the network, will generate data that will allow, if shared, an optimization of the offer and resources. The trend to take advantage of shared services and integration into the web through the IoT will push to meet the needs of mobility by accessing a different mobility service according to needs, rather than buying vehicles or making medium-long term choices.

**Figure 3.** *Different types of connections.*

#### *Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

connected vehicles.

transport efficiency [26, 27].

able development [28, 29].

**Figure 3** presents the different types of connections.

to the amount of useful information that can be exchanged and the possibility of crossing millions of data also in a predictive function. **Figure 2** shows an example of

Smart city does not mean, of course, digital city, even if in the past the tendency was to essentially make the two expressions coincide. The goal of the smart city is not digitization, which is instead an effective and flexible tool for improving many aspects of the quality of life of citizens and promoting the country's economic growth. The approach to the issue of smart cities brings with its undoubted elements of difficulty, just think of identifying the interventions to be carried out, their alignment with the economic and social context of the city and the assessment of the impact on the community, without considering that the various projects, once conceived, must be able to be effectively carried out in that specific urban and social context. It is possible to argue that a city can be defined as "smart" that is to say "intelligent" when, according to a strategic, integrated and organic vision, using ICT tools to improve the lives of its citizens, it uses real-time information from various areas and exploits both tangible (e.g. infrastructure, energy and natural resources) and intangible (e.g. human capital, knowledge) resources, adapting from time to time to the needs of users with a view to sustain-

It was estimated that in 2020 approximately 75% of new vehicles were able to connect to the internet, thus accessing different services and potentially allowing the exchange of information with the infrastructure (V2I), with other vehicles (V2V) and, generalizing, with anyone (V2X) (for example for updates of on-board software (SW) or the acquisition of travel information by various service providers).

Expressions such as smart mobility and smart city are used to indicate intelligent infrastructural and mobility systems. With these terms we mean that set of logistics and transport systems that are supported and integrated by ICT. In particular, smart mobility refers to a new mobility model that uses new technologies for road safety and integrates information and innovations on board the vehicle to increase

**158**

**Figure 3.**

*Different types of connections.*

The spread of connected vehicles supports the adoption of increasingly high levels of automation (autonomous driving) and access to articulated mobility services offered by different subjects. Connected travelers and vehicles will become Internet of Things (IoT) or Internet of Everything (IoE) nodes. The demand for mobility will therefore be satisfied through a multimodal, on-demand, and shared offer. The consumer will have multiple offers, more choice between different service levels. Public and private operators will coexist. Vehicles and travelers, as nodes in the network, will generate data that will allow, if shared, an optimization of the offer and resources. The trend to take advantage of shared services and integration into the web through the IoT will push to meet the needs of mobility by accessing a different mobility service according to needs, rather than buying vehicles or making medium-long term choices.

#### **5. Autonomous vehicles**

The term autonomous refers to the ability and faculty to govern or stand alone. According to the NHTSA (National Highway Traffic Safety Administration), or the US government agency for road safety, it defines an autonomous car "*a vehicle whose operation takes place without direct intervention by the driver to control steering, acceleration and braking and which is designed in such a way that do not expect to constantly check the road, when the automatic mode is running*" [30, 31].

In order to achieve a certain level of autonomy, the car exploits the ability to detect the surrounding environment through techniques such as radar, LIDAR, GPS and sensors. Therefore, the interaction between these components and the advanced control systems on board the car allows the latter to make decisions about the paths to follow and any obstacles and signals to monitor. To verify the degree of autonomy of the car, there are different classifications and standards coexisting with each other. The most adopted and followed by the scientific literature are the standard published by the NHTSA and the standard published by the SAE (a standardization body in the field of the automotive industry). In 2016, the NHTSA adopted the SAE J3016 standard, which therefore is configured as the reference standard. The latter has established six levels of autonomous driving that are based on the greater or lesser degree of automation of the vehicle, with the relative level of human participation in driving the car [32–34]:


autonomous driving is not allowed or is too dangerous, for example in case of bad weather. The driver can, therefore, momentarily divert attention, but must quickly acquire control of the car if necessary.


There is significant consensus that, in the context of urban mobility, robotaxi fleets will be available between 2025 and 2030 (currently being tested). Autonomous vehicles and the services that can be activated thanks to their diffusion are expected to bring significant benefits to mobility [36, 37]. However, regulators will have to carefully govern the dissemination process. The advantages that can be found in the introduction of autonomous vehicles can be:


The spread of shared and autonomous on-demand services will offer solutions for Local Public Transport in the first and last mile, as feeder services of the power lines. They must be part of a flexible and integrated public transport service. Autonomous vehicles should be shared as much as possible, and not merely replace the current private vehicles. However, the driverless, without driver is the future of motoring, and more. In a first phase, an authorized driver must in any case be present in the driving seat: he will be able to carry out work or play activities but must always be available to regain control of the vehicle if requested by the computer system. In a second phase, less distant than one might imagine, there will be no driver, but only passengers in a vehicle entirely managed by technology. Every year around 1,400,000 people in the world die from being involved in

**161**

*Future Mobility Advances and Trends*

to technological defects [38, 39].

*Automation levels defined by the SAE [35].*

many challenges to be solved.

mation vehicles should exchange [40].

currently available.

**Figure 4.**

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

road accidents: a massacre. The most accredited statistics on the causes of these accidents attribute them, in about 90% of cases, to inappropriate behavior or distraction of the driver. In only about 2% of cases, the responsibility is attributed

With the widespread use of driverless, the decrease in the number and severity of accidents will be drastic: this is indicated by all independent scientific forecasts

However, technology still poses challenges. For example, environmental perception can be made more robust through the fusion of information from different sensors, a research area in which further development is expected in order to be able to make full use of all the information available. In addition, new deep learning algorithms for object detection have shown significant performance gains, but still need to be extended in order to operate with fused data from different sensors. Still, despite recent advances in solving the localization problem, there are problems with long-term mapping. Updating the maps with static, topometric, activity and semantic data as time changes in order to ensure the vehicle can be located precisely and consistently with respect to the environment is an open research topic with

Despite the significant advances demonstrated in the field of planning algorithms, further improvements are anticipated in the field of real-time planning in dynamic environments. The field of control has also shown important progress in recent years, however, many of the fundamental results obtained have only been validated in simulation. Ensuring that the autonomous system pursues the intentions of higher-level decision making is crucial. Finally, it has been demonstrated how vehicle cooperation (V2V) can increase the performance of the perception and planning process, but there is still much to be achieved to offer greater scalability of multi-vehicle cooperation algorithms and despite the fact that the hardware has been standardized, there is currently no standard that defines what types of infor-

But technological issues are only one, probably minor, aspect of a problem whose solution involves evaluating several issues to consider. One of these concerns the regulatory and ethical problems. The first refers to the legislative question. It is necessary to have a regulation that modifies the highway code in order to allow the circulation of autonomous cars. At the moment only a few states have opened road sections dedicated to the transit of autonomous cars. In the United

*Self-Driving Vehicles and Enabling Technologies*

quickly acquire control of the car if necessary.

of automation levels as defined by the SAE.

found in the introduction of autonomous vehicles can be:

• Increase of road safety;

and better environmental impact;

complete territorial accessibility;

Transport (LPT) or Taxi;

• Reduction of parking areas;

ridesharing.

the driver to regain full control of the car, if he so requests.

autonomous driving is not allowed or is too dangerous, for example in case of bad weather. The driver can, therefore, momentarily divert attention, but must

• *Level 4*: High automation. This level provides for autonomous management of acceleration, deceleration, steering, and traffic control. The car handles the typical situations caused by traffic or traveling on urban or suburban roads. In this situation the car is able to drive in complete autonomy, but it is possible for

• *Level 5*: Complete automation. In this level, no intervention is required from the driver. The car drives exclusively autonomously, completely managing all the typical aspects of driving and based on the required tasks, it autonomously identifies the path to follow, take the right direction, accelerate or decelerate based on traffic conditions or upcoming situations. **Figure 4** shows a summary

• Optimization of traffic flows with consequent reduction of urban congestion

• Mobility guaranteed to the entire population (elderly, disabled, minors) and

• Reduction of the "driver costs" currently incurred with the use of Local Public

The spread of shared and autonomous on-demand services will offer solutions for Local Public Transport in the first and last mile, as feeder services of the power lines. They must be part of a flexible and integrated public transport service. Autonomous vehicles should be shared as much as possible, and not merely replace the current private vehicles. However, the driverless, without driver is the future of motoring, and more. In a first phase, an authorized driver must in any case be present in the driving seat: he will be able to carry out work or play activities but must always be available to regain control of the vehicle if requested by the computer system. In a second phase, less distant than one might imagine, there will be no driver, but only passengers in a vehicle entirely managed by technology. Every year around 1,400,000 people in the world die from being involved in

• Transformation of time spent driving from unproductive to productive;

• Diffusion of a new shared mobility model based on car sharing and

There is significant consensus that, in the context of urban mobility, robotaxi fleets will be available between 2025 and 2030 (currently being tested). Autonomous vehicles and the services that can be activated thanks to their diffusion are expected to bring significant benefits to mobility [36, 37]. However, regulators will have to carefully govern the dissemination process. The advantages that can be

**160**

**Figure 4.** *Automation levels defined by the SAE [35].*

road accidents: a massacre. The most accredited statistics on the causes of these accidents attribute them, in about 90% of cases, to inappropriate behavior or distraction of the driver. In only about 2% of cases, the responsibility is attributed to technological defects [38, 39].

With the widespread use of driverless, the decrease in the number and severity of accidents will be drastic: this is indicated by all independent scientific forecasts currently available.

However, technology still poses challenges. For example, environmental perception can be made more robust through the fusion of information from different sensors, a research area in which further development is expected in order to be able to make full use of all the information available. In addition, new deep learning algorithms for object detection have shown significant performance gains, but still need to be extended in order to operate with fused data from different sensors. Still, despite recent advances in solving the localization problem, there are problems with long-term mapping. Updating the maps with static, topometric, activity and semantic data as time changes in order to ensure the vehicle can be located precisely and consistently with respect to the environment is an open research topic with many challenges to be solved.

Despite the significant advances demonstrated in the field of planning algorithms, further improvements are anticipated in the field of real-time planning in dynamic environments. The field of control has also shown important progress in recent years, however, many of the fundamental results obtained have only been validated in simulation. Ensuring that the autonomous system pursues the intentions of higher-level decision making is crucial. Finally, it has been demonstrated how vehicle cooperation (V2V) can increase the performance of the perception and planning process, but there is still much to be achieved to offer greater scalability of multi-vehicle cooperation algorithms and despite the fact that the hardware has been standardized, there is currently no standard that defines what types of information vehicles should exchange [40].

But technological issues are only one, probably minor, aspect of a problem whose solution involves evaluating several issues to consider. One of these concerns the regulatory and ethical problems. The first refers to the legislative question. It is necessary to have a regulation that modifies the highway code in order to allow the circulation of autonomous cars. At the moment only a few states have opened road sections dedicated to the transit of autonomous cars. In the United

States it is possible to test certain cars without a driver on board. In Japan, the test of autonomous cars without humans on board was allowed, as long as they were controlled and monitored remotely. In Germany, the presence of a human being is still required, but it is allowed to carry out technological tests while the driver can take care of other things, without having to keep their hands on the wheel. France is preparing a regulatory evolution to facilitate and expand the opportunities for experimenting with autonomous cars, as long as there is a human being on board.

Furthermore, the legislative problem is intertwined with the ethical-moral question, for which a definitive solution has not yet been found. This refers to who to attribute responsibility in the event of an accident. Who to blame in case of damage, if the manufacturing company or the owner/passenger and what decision to make the car make about who to save for example in a situation where the car has a school group in front of it and has to choose to avoid a collision with another vehicle. These issues are crucial in carrying out this technological diffusion.

#### **6. Mobility as a service**

The acronym MaaS (Mobility as a Service) describes a new way of moving which, to the concept of personal ownership of the vehicle, replaces the concept of shared mobility understood as a service to be used according to need [41].

Moving from a lifestyle based on the possession of the means of transport, in particular the car, to a lifestyle based on the concept of Mobility as a Service, is not easy but considering mobility as a shared service offers many advantages for the individual citizen, for society and for the environment. MaaS is an ICT platform to manage the supply–demand meeting of transport and services offered by different subjects through a single information system interoperable with the proprietary systems of the individual operators. Service providers will also be able to operate on larger scales than the local one [42]. A successful MaaS service also brings new business models and ways to organize and manage various transport options, with benefits for transport operators including access to improved user and demand information, and new opportunities to meet unmet demand. MaaS's goal is to provide an alternative to private car use that can be cheaper, more sustainable, help reduce congestion and transport capacity constraints. For the user, MaaS can offer added value through the use of a single application to provide access to mobility, with a single payment channel instead of multiple ticketing and payment operations.

Mobility as a service is a relatively new concept that, in addition to changing the business model for the provision of transport services, promises a change in the means and methods of providing the service. This concept was created to be applied above all in large cities, where traffic congestion and levels of atmospheric and environmental pollution have reached their peak [43, 44].

Technology plays a fundamental role in making possible the spread of this business model, which has as its main feature the possibility for the citizen to choose the most suitable means of transport based on the route to be taken, passing from car to train, up to get to busses, trams, scooters and bicycles. In perspective, in fact, the user, through a single application, will have a service available on his smartphone that will allow him to plan the trip and to choose which means of transport to use for each journey to be made, paying for the single trip or taking advantage of monthly passes or unified rates for several different means of transport. The main feature of MaaS lies in offering travelers solutions based on their real travel needs. To do this, it is essential to combine public transport service providers (such as busses, trams and trains) with private services such as car sharing, bike sharing or

**163**

framework of MaaS.

**Figure 5.**

*Mobility as a service framework.*

**7. Sharing mobility**

*Future Mobility Advances and Trends*

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

car rental services. In this way, through a single platform, users can plan their trip and pay using a single account. The most advanced platforms will have to be able to show the user the different travel options with relative prices and travel times, to

Once the trip has been planned, the natural evolution of the service lies in allowing the user to book the means of transport directly in the App (taxi, car sharing, scooter, train) to be sure to arrive at their destination in the manner and on schedule

In the long term, with a view to increasingly shared and sustainable mobility, Mobility as a Service should also allow roaming: a single application that can be used by the user to move around different cities without having to sign up for different services each time. Customization and flexibility in the transport system is an increasingly requested feature that has generated in recent decades a market space and growing interest in MaaS by both the public and the private sector. In the private sector, many services for sharing cars, bicycles, scooters and busses were born, for citizens and companies. But it is in the public sector that Mobility as a Service can be considered as a real revolution, able to connect trains, planes, trams and busses, to car sharing and bike sharing services that complete the range of customizable travel possibilities by the user. In Europe, the state that has made the most progress towards the concept of mobility as a service is Finland, where there are already pilot cases of MaaS. In Italy, on the other hand, the city that most of all believed in shared and sustainable mobility is Milan. **Figure 5** illustrates the

Shared mobility is a topic of great depth and importance as it is going to revolutionize the traditional essence of transport itself, and which takes the name of Sharing Mobility (SM) or also called Shared Mobility. SM is a particular mobility system, which allows people to move from one place to another, through shared vehicles [46, 47]. Users therefore do not only use proprietary vehicles for travel, but use rental services, which leverage on digital platforms for the provision of the service. This system describes a transport service that includes, public transport and taxis, bike sharing, car sharing, carpooling, scooter sharing, shuttle services

allow him to choose the best solution according to his needs.

without unnecessary waste of time [45].

*Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

**6. Mobility as a service**

States it is possible to test certain cars without a driver on board. In Japan, the test of autonomous cars without humans on board was allowed, as long as they were controlled and monitored remotely. In Germany, the presence of a human being is still required, but it is allowed to carry out technological tests while the driver can take care of other things, without having to keep their hands on the wheel. France is preparing a regulatory evolution to facilitate and expand the opportunities for experimenting with autonomous cars, as long as there is a human being on board. Furthermore, the legislative problem is intertwined with the ethical-moral question, for which a definitive solution has not yet been found. This refers to who to attribute responsibility in the event of an accident. Who to blame in case of damage, if the manufacturing company or the owner/passenger and what decision to make the car make about who to save for example in a situation where the car has a school group in front of it and has to choose to avoid a collision with another vehicle. These issues are crucial in carrying out this technological diffusion.

The acronym MaaS (Mobility as a Service) describes a new way of moving which, to the concept of personal ownership of the vehicle, replaces the concept of

Moving from a lifestyle based on the possession of the means of transport, in particular the car, to a lifestyle based on the concept of Mobility as a Service, is not easy but considering mobility as a shared service offers many advantages for the individual citizen, for society and for the environment. MaaS is an ICT platform to manage the supply–demand meeting of transport and services offered by different subjects through a single information system interoperable with the proprietary systems of the individual operators. Service providers will also be able to operate on larger scales than the local one [42]. A successful MaaS service also brings new business models and ways to organize and manage various transport options, with benefits for transport operators including access to improved user and demand information, and new opportunities to meet unmet demand. MaaS's goal is to provide an alternative to private car use that can be cheaper, more sustainable, help reduce congestion and transport capacity constraints. For the user, MaaS can offer added value through the use of a single application to provide access to mobility, with a single payment channel instead of multiple ticketing and payment

Mobility as a service is a relatively new concept that, in addition to changing the business model for the provision of transport services, promises a change in the means and methods of providing the service. This concept was created to be applied above all in large cities, where traffic congestion and levels of atmospheric and

Technology plays a fundamental role in making possible the spread of this business model, which has as its main feature the possibility for the citizen to choose the most suitable means of transport based on the route to be taken, passing from car to train, up to get to busses, trams, scooters and bicycles. In perspective, in fact, the user, through a single application, will have a service available on his smartphone that will allow him to plan the trip and to choose which means of transport to use for each journey to be made, paying for the single trip or taking advantage of monthly passes or unified rates for several different means of transport. The main feature of MaaS lies in offering travelers solutions based on their real travel needs. To do this, it is essential to combine public transport service providers (such as busses, trams and trains) with private services such as car sharing, bike sharing or

environmental pollution have reached their peak [43, 44].

shared mobility understood as a service to be used according to need [41].

**162**

operations.

**Figure 5.** *Mobility as a service framework.*

car rental services. In this way, through a single platform, users can plan their trip and pay using a single account. The most advanced platforms will have to be able to show the user the different travel options with relative prices and travel times, to allow him to choose the best solution according to his needs.

Once the trip has been planned, the natural evolution of the service lies in allowing the user to book the means of transport directly in the App (taxi, car sharing, scooter, train) to be sure to arrive at their destination in the manner and on schedule without unnecessary waste of time [45].

In the long term, with a view to increasingly shared and sustainable mobility, Mobility as a Service should also allow roaming: a single application that can be used by the user to move around different cities without having to sign up for different services each time. Customization and flexibility in the transport system is an increasingly requested feature that has generated in recent decades a market space and growing interest in MaaS by both the public and the private sector. In the private sector, many services for sharing cars, bicycles, scooters and busses were born, for citizens and companies. But it is in the public sector that Mobility as a Service can be considered as a real revolution, able to connect trains, planes, trams and busses, to car sharing and bike sharing services that complete the range of customizable travel possibilities by the user. In Europe, the state that has made the most progress towards the concept of mobility as a service is Finland, where there are already pilot cases of MaaS. In Italy, on the other hand, the city that most of all believed in shared and sustainable mobility is Milan. **Figure 5** illustrates the framework of MaaS.

#### **7. Sharing mobility**

Shared mobility is a topic of great depth and importance as it is going to revolutionize the traditional essence of transport itself, and which takes the name of Sharing Mobility (SM) or also called Shared Mobility. SM is a particular mobility system, which allows people to move from one place to another, through shared vehicles [46, 47]. Users therefore do not only use proprietary vehicles for travel, but use rental services, which leverage on digital platforms for the provision of the service. This system describes a transport service that includes, public transport and taxis, bike sharing, car sharing, carpooling, scooter sharing, shuttle services

and others (**Figure 6**). This shared mobilization system relies not only on private users who make their own vehicle available to others, allowing access to it, but this has also been possible thanks to the birth of companies that make their services available (as for example Car2Go and Enjoy in Italy).

The SM aims to respond to new travel needs, trying to offer new options and solutions for transport. This system is able to provide more mobility choices to the user, put the last mile in contact with the first mile and reduce traffic congestion through the shared use of vehicles. In addition, it helps reduce air pollution, reduce transport costs, increase efficiency, and last but not least, it offers travel options for those who are unable to economically maintain a vehicle they own. This system also seeks to solve some historical problems inherent in traditional mobility, or to facilitate the sharing of vehicles and journeys between individuals, creating "tailormade" services for each user of the platform, and maximizing the use of latent resources. Recent technological innovations have allowed the sharing of vehicles at lower transaction costs than in the past, thus allowing the sharing of vehicles that were normally designed for personal use (see for example Uber or Auting).

To classify a transport service under the "Sharing Mobility" label, certain characteristics must be present. In the first analysis, there is a need for the sharing of a mobility service, or that this service is shared between two users. This is possible in two different ways: there can be the use of the service simultaneously, as for example with BlaBlaCar, when the service is used simultaneously with other passengers, or differently the service can be offered in succession, when for example it is used a Car Sharing or Car-Pooling service (such as Uber) [48, 49].

Another important feature of shared mobility is the use of digital platforms, these are a necessary support for the creation of an original collaborative service. These platforms are based on the use of websites accessible from desktops, apps for smartphones and other mobile devices. Digital platforms allow levels of

**165**

vehicle.

*Future Mobility Advances and Trends*

transaction costs.

market share.

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

interactions unimaginable compared to the past, in fact they are able to easily put demand and supply in contact in real time, create relationships with service users, are easy and immediate to use and finally are more effective allowing to reduce

The use of the internet and the development of the "Information Technology System" (ITS) has proved to be of vital importance for these platforms; these tools have in fact allowed niche practices to impose themselves as forms of mass consumption, thus gaining visibility in the minds of consumers and at the same time

The car in the model of traditional mobility is a "Status Symbol", which indicates the acquisition of full freedom by the individual in travel and the ability to satisfy their interests: it is the quintessential symbol of emancipation. This has given rise to a model in which almost every individual owns one or more owned cars to make their trips around the city, with a consequent increase in the number of cars in circulation over time. Today, this increase is causing major problems both in the field of mobility and in the sustainable and environmental sphere, and this is how measures have been developed to reduce and discourage the use of individual

SM can be a useful model for encouraging these behaviors. It is unthinkable to pass from a model that contemplates owned vehicles as a vehicle for travel, to a model that instead contemplates only shared means, without there being a period of experimentation and adaptation. The SM allows you to use your individual vehicle in a shared way, making your vehicle accessible to other users. Access to these services gives users new methods to evaluate which is the most favorable option regardless of the means of transport that you own or otherwise do not have at all. The main objective but also the most difficult to achieve since it must go to break already consolidated paradigms, is to encourage these practices of sustainable mobility, and make sure that the first choice of the individual is not to use his own vehicle, but rather the use of systems headed by the SM. Only in this way will it be possible to have decisive repercussions in the field of sustainability with the reduc-

Technology plays a fundamental role in the orientation of users to choose the best vehicle to use for their journeys. There is a need to replace vehicle keys with smartphones, able to search, through mobility service aggregators, what is the best

SM could also solve traffic congestion problems. Often, in fact, the cars do not travel with their full load capacity, and many drivers are found on the streets who drive their vehicle without any passengers. This is even more relevant at peak times, when users are on their way to work or on their way home. The roads are invaded by thousands of vehicles at the same time, and this causes major traffic problems with consequent queues and delays. MS could partially solve this problem by reducing the number of vehicles on the roads. As previously mentioned, digital platforms are able to connect supply and demand in real time, and to bring users with the same travel needs together. With these tools, it would be relatively easy to organize the sorts of shuttle vehicles, traveling fully loaded to transport users who have a similar destination, thus reducing the number of vehicles needed to move on the roads. These forms of displacement are already present today but are still underused. There is a need to make users understand what the advantages are of sharing a

A reduction of vehicles on the roads as well as advantages to the road mobility system would also lead to a reduction in polluting emissions from vehicles. MS is known not only for the use of innovative digital platforms, but also for the use of new forms of energy. This model is increasingly pushing towards an

vehicles, to induce users to more sustainable forms of transport.

tion of consumption of traditional mobility.

way to move to the preset destination.

**Figure 6.** *Sharing mobility.*

#### *Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

available (as for example Car2Go and Enjoy in Italy).

Car Sharing or Car-Pooling service (such as Uber) [48, 49].

and others (**Figure 6**). This shared mobilization system relies not only on private users who make their own vehicle available to others, allowing access to it, but this has also been possible thanks to the birth of companies that make their services

The SM aims to respond to new travel needs, trying to offer new options and solutions for transport. This system is able to provide more mobility choices to the user, put the last mile in contact with the first mile and reduce traffic congestion through the shared use of vehicles. In addition, it helps reduce air pollution, reduce transport costs, increase efficiency, and last but not least, it offers travel options for those who are unable to economically maintain a vehicle they own. This system also seeks to solve some historical problems inherent in traditional mobility, or to facilitate the sharing of vehicles and journeys between individuals, creating "tailormade" services for each user of the platform, and maximizing the use of latent resources. Recent technological innovations have allowed the sharing of vehicles at lower transaction costs than in the past, thus allowing the sharing of vehicles that were normally designed for personal use (see for example Uber or Auting).

To classify a transport service under the "Sharing Mobility" label, certain characteristics must be present. In the first analysis, there is a need for the sharing of a mobility service, or that this service is shared between two users. This is possible in two different ways: there can be the use of the service simultaneously, as for example with BlaBlaCar, when the service is used simultaneously with other passengers, or differently the service can be offered in succession, when for example it is used a

Another important feature of shared mobility is the use of digital platforms, these are a necessary support for the creation of an original collaborative service. These platforms are based on the use of websites accessible from desktops, apps for smartphones and other mobile devices. Digital platforms allow levels of

**164**

**Figure 6.** *Sharing mobility.* interactions unimaginable compared to the past, in fact they are able to easily put demand and supply in contact in real time, create relationships with service users, are easy and immediate to use and finally are more effective allowing to reduce transaction costs.

The use of the internet and the development of the "Information Technology System" (ITS) has proved to be of vital importance for these platforms; these tools have in fact allowed niche practices to impose themselves as forms of mass consumption, thus gaining visibility in the minds of consumers and at the same time market share.

The car in the model of traditional mobility is a "Status Symbol", which indicates the acquisition of full freedom by the individual in travel and the ability to satisfy their interests: it is the quintessential symbol of emancipation. This has given rise to a model in which almost every individual owns one or more owned cars to make their trips around the city, with a consequent increase in the number of cars in circulation over time. Today, this increase is causing major problems both in the field of mobility and in the sustainable and environmental sphere, and this is how measures have been developed to reduce and discourage the use of individual vehicles, to induce users to more sustainable forms of transport.

SM can be a useful model for encouraging these behaviors. It is unthinkable to pass from a model that contemplates owned vehicles as a vehicle for travel, to a model that instead contemplates only shared means, without there being a period of experimentation and adaptation. The SM allows you to use your individual vehicle in a shared way, making your vehicle accessible to other users. Access to these services gives users new methods to evaluate which is the most favorable option regardless of the means of transport that you own or otherwise do not have at all. The main objective but also the most difficult to achieve since it must go to break already consolidated paradigms, is to encourage these practices of sustainable mobility, and make sure that the first choice of the individual is not to use his own vehicle, but rather the use of systems headed by the SM. Only in this way will it be possible to have decisive repercussions in the field of sustainability with the reduction of consumption of traditional mobility.

Technology plays a fundamental role in the orientation of users to choose the best vehicle to use for their journeys. There is a need to replace vehicle keys with smartphones, able to search, through mobility service aggregators, what is the best way to move to the preset destination.

SM could also solve traffic congestion problems. Often, in fact, the cars do not travel with their full load capacity, and many drivers are found on the streets who drive their vehicle without any passengers. This is even more relevant at peak times, when users are on their way to work or on their way home. The roads are invaded by thousands of vehicles at the same time, and this causes major traffic problems with consequent queues and delays. MS could partially solve this problem by reducing the number of vehicles on the roads. As previously mentioned, digital platforms are able to connect supply and demand in real time, and to bring users with the same travel needs together. With these tools, it would be relatively easy to organize the sorts of shuttle vehicles, traveling fully loaded to transport users who have a similar destination, thus reducing the number of vehicles needed to move on the roads. These forms of displacement are already present today but are still underused. There is a need to make users understand what the advantages are of sharing a vehicle.

A reduction of vehicles on the roads as well as advantages to the road mobility system would also lead to a reduction in polluting emissions from vehicles. MS is known not only for the use of innovative digital platforms, but also for the use of new forms of energy. This model is increasingly pushing towards an

eco-sustainable approach, through the use of vehicles that no longer rely on traditional fuels, but on new electrical technologies. Electric vehicles are known to be non-polluting vehicles as they use electric propulsion for driving and are silent. In the main cities there are today Car Sharing services that use these vehicles, which are parked in special parking areas equipped with an electric charging column. In addition to being vehicles that respect the environment more, they are characterized by low cost of refueling compared to fossil fuel vehicles, they also arouse great interest in people, since electric is still a technology that is little used for traditional travel.

Today we have reached a point where the traditional transport system is no longer able to support the needs of users, everyone wants to go everywhere in the most efficient way, but the road network is now congested by too many vehicles that travel it, creating big problems in moving. The car is the vehicle that guarantees the greatest versatility, it can be used for short urban journeys or for long journeys from one city to another: therefore, it allows the driver a degree of freedom and autonomy that no other public transport can guarantee. People today want to feel free, and they do not want to feel constrained in their movements, so they are looking for the type of mobility that can meet these needs. For these reasons, MS can be the solution to all these problems: it promotes access to mobility services with respect to vehicle ownership and uses a digital platform capable of representing the best travel solutions both from the point of view of the child, travel time and lower cost, both from the point of view of environmental impacts and efficiency. It is a model that goes against the traditional paradigms of mobility, but at the same time wants to satisfy the same needs: freedom and versatility of movement.

Owning a car is a significant cost in families' assets, in fact it can weigh up to 20% on family income. On the other hand, car sharing users are freed from these ownership costs, from the fixed costs of maintaining the vehicle, from insurance, and pay only what they consume. With traditional mobility based on ownership, we have reached a point where a vicious circle has been triggered, in which as the ownership of a private car increases, congestion on the road network and the need for new road infrastructure increases. With SM, on the other hand, we are experiencing the birth of a virtuous circle, in which the decrease in ownership and use of the private car follows a propensity to reduce ownership, which leads to a regeneration of the urban area and better accessibility within cities. Ownership by young people is perceived as something ancient, thanks to the internet they are now used to sharing, exchanging, reusing goods, and services. They are no longer willing to pay to own something for one-time use. They are inclined to pay for the actual use and are not interested in mere possession.

Innovations, especially radical ones, are capable of changing the game rules of a market. An innovation is said to be radical when it gives rise to new technological paradigms thanks to the Research and Development (R&D) of industrial or government laboratories, with the aim of combining product, process and organizational innovations to develop new markets. SM can be part of this context of radical innovation, as it is a model that is challenging traditional mobility and the most common transport methodologies.

Sharing Mobility can also be thought of as a disruptive type of innovation, an innovation that radically changes habits and the way consumers use a good or service, bringing about changes that can affect an entire ecosystem. As we have been able to analyze in the previous paragraphs, MS has led to new ways of conceiving mobility thanks to the support of new technologies, but many wonders if this model is truly capable of overwhelming and replacing the previous one based on ownership and possession of the vehicle.

**167**

**Author details**

constant evolution.

**Conflict of interest**

Michela Longo1

Canada

\*, Wahiba Yaïci2

provided the original work is properly cited.

The authors declare no conflict of interest.

\*Address all correspondence to: michela.longo@polimi.it

and Federica Foiadelli1

In a decade, as a result of technologies, mobility management will be significantly more complex and business models will change. New mobility services (e.g., robotaxi) will be offered by more and more operators, public and private: carpooling, car sharing, ride sharing. It will be important to provide mobility services based on the integration, including multimodal, of Local Public Transport, private mobility, light mobility, shared transport services, etc. Public Transport operators will have to reposition their offer and services, forge alliances, review the value chain. A dynamic and integrated allocation of resources managed by various different entities (public and private transport services, physical network infrastructures, etc.) will be needed. An "intelligent" transport infrastructure will have to be developed, able to communicate with users and vehicles through multiple standards and control and regulation centers for the transport infrastructure offer will have to be implemented. It will be necessary to spread a greater culture, awareness of the economic value of the data generated as a result of access to shared services and autonomous driving. As a result of the high levels of vehicle automation, the spread of vehicle connections with the web, the cybersecurity aspects will assume absolute importance. As a result of its complexity and integration, mobility could be more vulnerable to malfunctions of its components (communication networks, power grid, control centers, etc.). It is therefore a field of work that is still open, in

1 Federica Foiadelli, Politecnico di Milano, Department of Energy, Milan, Italy

2 CanmetENERGY Research Centre, Natural Resources Canada, Ottawa, Ontario,

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Future Mobility Advances and Trends*

**8. Conclusions**

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

### **8. Conclusions**

*Self-Driving Vehicles and Enabling Technologies*

for traditional travel.

movement.

and are not interested in mere possession.

common transport methodologies.

ship and possession of the vehicle.

eco-sustainable approach, through the use of vehicles that no longer rely on traditional fuels, but on new electrical technologies. Electric vehicles are known to be non-polluting vehicles as they use electric propulsion for driving and are silent. In the main cities there are today Car Sharing services that use these vehicles, which are parked in special parking areas equipped with an electric charging column. In addition to being vehicles that respect the environment more, they are characterized by low cost of refueling compared to fossil fuel vehicles, they also arouse great interest in people, since electric is still a technology that is little used

Today we have reached a point where the traditional transport system is no longer able to support the needs of users, everyone wants to go everywhere in the most efficient way, but the road network is now congested by too many vehicles that travel it, creating big problems in moving. The car is the vehicle that guarantees the greatest versatility, it can be used for short urban journeys or for long journeys from one city to another: therefore, it allows the driver a degree of freedom and autonomy that no other public transport can guarantee. People today want to feel free, and they do not want to feel constrained in their movements, so they are looking for the type of mobility that can meet these needs. For these reasons, MS can be the solution to all these problems: it promotes access to mobility services with respect to vehicle ownership and uses a digital platform capable of representing the best travel solutions both from the point of view of the child, travel time and lower cost, both from the point of view of environmental impacts and efficiency. It is a model that goes against the traditional paradigms of mobility, but at the same time wants to satisfy the same needs: freedom and versatility of

Owning a car is a significant cost in families' assets, in fact it can weigh up to 20% on family income. On the other hand, car sharing users are freed from these ownership costs, from the fixed costs of maintaining the vehicle, from insurance, and pay only what they consume. With traditional mobility based on ownership, we have reached a point where a vicious circle has been triggered, in which as the ownership of a private car increases, congestion on the road network and the need for new road infrastructure increases. With SM, on the other hand, we are experiencing the birth of a virtuous circle, in which the decrease in ownership and use of the private car follows a propensity to reduce ownership, which leads to a regeneration of the urban area and better accessibility within cities. Ownership by young people is perceived as something ancient, thanks to the internet they are now used to sharing, exchanging, reusing goods, and services. They are no longer willing to pay to own something for one-time use. They are inclined to pay for the actual use

Innovations, especially radical ones, are capable of changing the game rules of a market. An innovation is said to be radical when it gives rise to new technological paradigms thanks to the Research and Development (R&D) of industrial or government laboratories, with the aim of combining product, process and organizational innovations to develop new markets. SM can be part of this context of radical innovation, as it is a model that is challenging traditional mobility and the most

Sharing Mobility can also be thought of as a disruptive type of innovation, an innovation that radically changes habits and the way consumers use a good or service, bringing about changes that can affect an entire ecosystem. As we have been able to analyze in the previous paragraphs, MS has led to new ways of conceiving mobility thanks to the support of new technologies, but many wonders if this model is truly capable of overwhelming and replacing the previous one based on owner-

**166**

In a decade, as a result of technologies, mobility management will be significantly more complex and business models will change. New mobility services (e.g., robotaxi) will be offered by more and more operators, public and private: carpooling, car sharing, ride sharing. It will be important to provide mobility services based on the integration, including multimodal, of Local Public Transport, private mobility, light mobility, shared transport services, etc. Public Transport operators will have to reposition their offer and services, forge alliances, review the value chain. A dynamic and integrated allocation of resources managed by various different entities (public and private transport services, physical network infrastructures, etc.) will be needed. An "intelligent" transport infrastructure will have to be developed, able to communicate with users and vehicles through multiple standards and control and regulation centers for the transport infrastructure offer will have to be implemented. It will be necessary to spread a greater culture, awareness of the economic value of the data generated as a result of access to shared services and autonomous driving. As a result of the high levels of vehicle automation, the spread of vehicle connections with the web, the cybersecurity aspects will assume absolute importance. As a result of its complexity and integration, mobility could be more vulnerable to malfunctions of its components (communication networks, power grid, control centers, etc.). It is therefore a field of work that is still open, in constant evolution.

### **Conflict of interest**

The authors declare no conflict of interest.

### **Author details**

Michela Longo1 \*, Wahiba Yaïci2 and Federica Foiadelli1

1 Federica Foiadelli, Politecnico di Milano, Department of Energy, Milan, Italy

2 CanmetENERGY Research Centre, Natural Resources Canada, Ottawa, Ontario, Canada

\*Address all correspondence to: michela.longo@polimi.it

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] "Mobility 2030: Transforming the mobility landscape", KPMG, 2019: https://assets.kpmg/content/dam/ kpmg/xx/pdf/2019/02/mobility-2030 transforming-the-mobility-landscape. pdf (Accessed by March 2021)

[2] "McKinsey Center for Future Mobility®", McKinsey & company: https://www.mckinsey.com/features/ mckinsey-center-for-future-mobility/ overview# (Accessed by March 2021)

[3] "Autonomous Mobility and Energy Service Management in Future Smart Cities: An Overview", Xiaoqi Tan, Alberto Leon-Garcia, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8642141 (Accessed by March 2021)

[4] "Race 2050 – a vision for the european automotive industry", McKinsey & company, 2019: https:// www.mckinsey.com/~/media/ mckinsey/industries/automotive%20 and%20assembly/our%20insights/a%20 long%20term%20vision%20for%20 the%20european%20automotive%20 industry/race-2050-a-vision-for-theeuropean-automotive-industry.pdf (Accessed by March 2021)

[5] "Future Networks 2030: Challenges in Intelligent Transportation Systems", Mădălin-Dorin Pop, Jitendra Pandey, Velmani Ramasamy, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9197951

[6] "Future Networks 2030: Architecture & Requirements", Anastasia Yastrebova, Ruslan Kirichek, Yevgeni Koucheryavy, Aleksey Borodin, Andrey Koucheryavy, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8631208

[7] "Smart Transportation System: Mobility solution for Smart Cities", Samir Maqbool Al-Shariff, M. Saad Alam, Zaurez Ahmad, Furkan Ahmad, 2019: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=9124988

[8] "Big Data Analytics for Electric Vehicle Integration in Green Smart Cities", Boyang Li, Mithat C. Kisacikoglu, Chen Liu, Navjot Singh, and Melike Erol-Kantarci, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8114543

[9] "Highlighting the future of Autonomous vehicle technology in 2020-2050", Nedaa Baker Al Barghuti, Deepa Pavithran, Huwida E. Said, 2018: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8649510

[10] "How to Conceive Future Mobility Services in Smart Cities according to the FIWARE frontierCities Experience", Lorenzo Carnevale, Antonio Celesti, Maria Di Pietro, Antonino Galletta, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8497005

[11] "Smart city drivers and challenges in urbanmobility, health-care, and interdependent infrastructure systems", Amro M. Farid, Muhannad Alshareef, Parupkar Singh Badhesha, Chiara Boccaletti, Nelio Alessandro Azevedo Cacho, Claire-Isabelle Carlier, Amy Corriveau, Inas Khayal, Barry Liner, Joberto S.B. Martins, Farokh Rahimi, Rosaldo Rossetti, Wester C.H. Schoonenberg, Ashlynn Stillwell, and Yinhai Wang, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9307293

[12] "Planning the Second Generation of Smart Cities", Itai Dadon, 2019: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8818647 (Accessed by March 2021)

[13] S K. Kaur, "A Survey on Internet of Things – Architecture, Applications, and Future Trends," in 2018 First International Conference on Secure

**169**

*Future Mobility Advances and Trends*

[14] "The Internet of Things for Intelligent Transportation Systems in Real Smart Cities Scenarios", Alberto Attilio Brincat, Federico Pacifici, Stefano Martinaglia, Francesco Mazzola, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8767247

[15] "A Closer Look at the IoT's "Things"", Jeffrey Voas, Bill Agresti, Phillip A. Laplante, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8378976

[16] "Application of Internet of Things and Big Data towards", Preeti Yadav, Sandeep Vishwakarma, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8519920

[17] "A Study on a Routing-Based Mobility Management Architecture for IoT Devices,",M. Ishino, Y. Koizumi and T. Hasegawa, 2014 IEEE 22nd International Conference on Network Protocols, Raleigh, NC, 2014, pp. 498-500, doi: 10.1109/ICNP.2014.78.: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=6980417

[18] "From electric mobility to hydrogen mobility: current state and possible future expansions", Guido Ala, Vincenzo Castiglia, Gabriella Di Filippo, Rosario Miceli, Pietro Romano and Fabio Viola, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9140482

[19] "Battery Based Last-Mile Module for Freight Electric Locomotives," M. Brenna, F. Foiadelli and J. Stocco, 2019 IEEE Vehicle Power and Propulsion Conference (VPPC), Hanoi,

Vietnam, 2019, pp. 1-6, doi: 10.1109/ VPPC46532.2019.8952376: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8952376

581-583.

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

Cyber Computing and Communication (ICSCCC), Jalandhar, India, 2018, pp.

[20] "E-Mobility — Advancements and Challenges", Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdows, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi, 2019: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=8895956

[21] "Dynamic Wireless Charging of Autonomous Vehicles: Small-scale demonstration of inductive power transfer as an enabling technology for self-sufficient energy supply.", Giuseppe Guidi, Anastasios M. Lekkas, Jon Eivind Stranden, and Jon Are Suul: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9024243

[22] "Study of Wireless Charging Lane for Electric Vehicles", Jiongran Xiao, Eric Cheng, Norbert Cheung, Bo Zhang, J. F. Pan, 2016: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7845989

[23] "A review on the key issues for lithium-ion battery management in electric vehicles", Languang Lu , Xuebing Han, Jianqiu Li, Jianfeng Hua, Minggao Ouyang,2013: https://www. researchgate.net/profile/Languang\_Lu/ publication/257225400\_A\_review\_on\_ the\_key\_issues\_for\_lithium-ion\_battery\_ management\_in\_electric\_vehicles/ links/5c42fe6ba6fdccd6b5b84a94/Areview-on-the-key-issues-for-lithiumion-battery-management-in-electricvehicles.pdf (Accessed by March 2021)

[24] "E-Mobility & Microgrid Laboratory at the Savona Campus of Genova University", Stefano Bracco, Federico Delfino, Giorgio Piazza, 2020: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=9241138

by March 2021)

[25] "How Electric Vehicles and the Grid Work Together", 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8501603 (Accessed Cyber Computing and Communication (ICSCCC), Jalandhar, India, 2018, pp. 581-583.

[14] "The Internet of Things for Intelligent Transportation Systems in Real Smart Cities Scenarios", Alberto Attilio Brincat, Federico Pacifici, Stefano Martinaglia, Francesco Mazzola, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8767247

[15] "A Closer Look at the IoT's "Things"", Jeffrey Voas, Bill Agresti, Phillip A. Laplante, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8378976

[16] "Application of Internet of Things and Big Data towards", Preeti Yadav, Sandeep Vishwakarma, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8519920

[17] "A Study on a Routing-Based Mobility Management Architecture for IoT Devices,",M. Ishino, Y. Koizumi and T. Hasegawa, 2014 IEEE 22nd International Conference on Network Protocols, Raleigh, NC, 2014, pp. 498-500, doi: 10.1109/ICNP.2014.78.: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=6980417

[18] "From electric mobility to hydrogen mobility: current state and possible future expansions", Guido Ala, Vincenzo Castiglia, Gabriella Di Filippo, Rosario Miceli, Pietro Romano and Fabio Viola, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9140482

[19] "Battery Based Last-Mile Module for Freight Electric Locomotives," M. Brenna, F. Foiadelli and J. Stocco, 2019 IEEE Vehicle Power and Propulsion Conference (VPPC), Hanoi, Vietnam, 2019, pp. 1-6, doi: 10.1109/ VPPC46532.2019.8952376: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8952376

[20] "E-Mobility — Advancements and Challenges", Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdows, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi, 2019: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8895956

[21] "Dynamic Wireless Charging of Autonomous Vehicles: Small-scale demonstration of inductive power transfer as an enabling technology for self-sufficient energy supply.", Giuseppe Guidi, Anastasios M. Lekkas, Jon Eivind Stranden, and Jon Are Suul: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9024243

[22] "Study of Wireless Charging Lane for Electric Vehicles", Jiongran Xiao, Eric Cheng, Norbert Cheung, Bo Zhang, J. F. Pan, 2016: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7845989

[23] "A review on the key issues for lithium-ion battery management in electric vehicles", Languang Lu , Xuebing Han, Jianqiu Li, Jianfeng Hua, Minggao Ouyang,2013: https://www. researchgate.net/profile/Languang\_Lu/ publication/257225400\_A\_review\_on\_ the\_key\_issues\_for\_lithium-ion\_battery\_ management\_in\_electric\_vehicles/ links/5c42fe6ba6fdccd6b5b84a94/Areview-on-the-key-issues-for-lithiumion-battery-management-in-electricvehicles.pdf (Accessed by March 2021)

[24] "E-Mobility & Microgrid Laboratory at the Savona Campus of Genova University", Stefano Bracco, Federico Delfino, Giorgio Piazza, 2020: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9241138

[25] "How Electric Vehicles and the Grid Work Together", 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8501603 (Accessed by March 2021)

**168**

*Self-Driving Vehicles and Enabling Technologies*

[1] "Mobility 2030: Transforming the mobility landscape", KPMG, 2019: https://assets.kpmg/content/dam/ kpmg/xx/pdf/2019/02/mobility-2030 transforming-the-mobility-landscape.

2019: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=9124988

[8] "Big Data Analytics for Electric Vehicle Integration in Green Smart Cities", Boyang Li, Mithat C.

Kisacikoglu, Chen Liu, Navjot Singh, and Melike Erol-Kantarci, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8114543

[9] "Highlighting the future of Autonomous vehicle technology in 2020-2050", Nedaa Baker Al Barghuti, Deepa Pavithran, Huwida E. Said, 2018: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=8649510

[10] "How to Conceive Future Mobility Services in Smart Cities according to the FIWARE frontierCities Experience", Lorenzo Carnevale, Antonio Celesti, Maria Di Pietro, Antonino Galletta, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8497005

[11] "Smart city drivers and challenges

[12] "Planning the Second Generation of Smart Cities", Itai Dadon, 2019: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8818647 (Accessed

[13] S K. Kaur, "A Survey on Internet of Things – Architecture, Applications, and Future Trends," in 2018 First International Conference on Secure

by March 2021)

in urbanmobility, health-care, and interdependent infrastructure systems", Amro M. Farid, Muhannad Alshareef, Parupkar Singh Badhesha, Chiara Boccaletti, Nelio Alessandro Azevedo Cacho, Claire-Isabelle Carlier, Amy Corriveau, Inas Khayal, Barry Liner, Joberto S.B. Martins, Farokh Rahimi, Rosaldo Rossetti, Wester C.H. Schoonenberg, Ashlynn Stillwell, and Yinhai Wang, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9307293

pdf (Accessed by March 2021)

**References**

[2] "McKinsey Center for Future Mobility®", McKinsey & company: https://www.mckinsey.com/features/ mckinsey-center-for-future-mobility/ overview# (Accessed by March 2021)

[3] "Autonomous Mobility and Energy Service Management in Future Smart Cities: An Overview", Xiaoqi Tan, Alberto Leon-Garcia, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8642141 (Accessed

[4] "Race 2050 – a vision for the european automotive industry", McKinsey & company, 2019: https:// www.mckinsey.com/~/media/ mckinsey/industries/automotive%20 and%20assembly/our%20insights/a%20 long%20term%20vision%20for%20 the%20european%20automotive%20 industry/race-2050-a-vision-for-theeuropean-automotive-industry.pdf

(Accessed by March 2021)

[5] "Future Networks 2030: Challenges in Intelligent Transportation Systems", Mădălin-Dorin Pop, Jitendra Pandey, Velmani Ramasamy, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9197951

[6] "Future Networks 2030: Architecture & Requirements", Anastasia Yastrebova, Ruslan Kirichek, Yevgeni Koucheryavy, Aleksey Borodin, Andrey Koucheryavy, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8631208

[7] "Smart Transportation System: Mobility solution for Smart Cities", Samir Maqbool Al-Shariff, M. Saad Alam, Zaurez Ahmad, Furkan Ahmad,

by March 2021)

[26] "Power Interchange Analysis for Reliable Vehicle-to-Grid Connectivity", Saba Al-Rubaye, Anwer Al-Dulaimi, and Qiang Ni, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8808171

[27] "Optimized power flow control of smart grids with electric vehicles and DER", Metody Georgiev EORGIEV, Rad Stanev, Anastassia Krusteva, 2019: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8771575

[28] "Analysis of Electrical Vehicle behavior from real world data: a V2I Architecture", Luca Bascetta, Giambattista Gruosso, Giancarlo Storti Gajani, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8493203

[29] "Reliability Verification Procedure of Secured V2X Communication for Autonomous Cooperation Driving", Han-Gyun Jung, Dae-Kyo Shin, Ki-Taeg Lim, Sang-Hun Yoon, Seong-Keun Jin, Soo-Hyun Jang, Jae-Min Kwak, 2018: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8539617

[30] "Functional architecture for autonomous driving and its implementation", Rihards Novickis, Aleksandrs Levinskis, Roberts Kadiis, Vitalijs Fescenko, Kaspars Ozols, 2020: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9276943

[31] "The autonomous mobility innovation lifecycle", Evangelos Simoudis, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8943257

[32] "Autonomous Vehicle Ethics Stock or Custom?", Sally Applin, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7948873

[33] "Incorporating Ethical Considerations Int o Automated Vehicle Control", Sarah M. Thornton, Selina Pan, Stephen M. Erlien, and J. Christian Gerdes, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7588150

[34] "Public Health, Ethics, and Autonomous Vehicles", Janet Fleetwood, 2017: https://ajph.aphapublications.org/ doi/pdfplus/10.2105/AJPH.2016.303628

[35] "Smart Car Road Testing 101", 2020: https://www.acmwillowrun.org/smartcar-road-testing-101/ (Accessed by March 2021)

[36] "Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy", Asif Faisal, Tan Yigitcanlar, Md Kamruzzaman, Graham Currie, 2018: https://conservancy.umn.edu/ bitstream/handle/11299/209218/JTLU\_ vol-12\_pp45-72.pdf?sequence=1

[37] "Driving Information Logger with In-Vehicle Communication for Autonomous Vehicle Research", Kyungbok Sung, Kyoungwook Min, and Jeongdan Choi, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8323732

[38] "New frontiers in driverless vehicles", Brad Pietras, 2015: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7088509

[39] "A Preliminary Investigation of an Autonomous Vehicle Validation Infrastructure for Smart Cities", Kyriakos M. Deliparaschos, Gergely Santha, Luca Zanotti Fragonara, Ivan Petrunin, Argyrios C. Zolotas, Antonios Tsourdos, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9201644

[40] "Development of Key Technologies for Autonomous Driving Vehicles", Jason Sheng-Hong Tsai, Jyh-Ching Juang, Chia-Heng Tu, Tzong-Yow Tsai, Pau-Choo Chung, Chih-Chung Hsu, Chao-Yang Lee, Ching-Fu Lin, 2019:

**171**

*Future Mobility Advances and Trends*

jsp?tp=&arnumber=9024730

*DOI: http://dx.doi.org/10.5772/intechopen.97108*

https://ieeexplore.ieee.org/stamp/stamp.

George Cristian Lazaroiu, 2016: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7526011

[48] "The Future of Mobility—Electric, Autonomous, and Shared Vehicles", Paul R. Donnellan, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8625919

[49] "Mobility Sharing as a Preference Matching Problem", Hongmou Zhang and Jinhua Zhao, 2019: https:// ieeexploriee.org/stamp/stamp. jsp?tp=&arnumber=8478802

[41] "Urban Mobility Digitalization: Towards Mobility as a Service (MaaS)", Luìs Barreto, Antonio Amaral, Sara Baltazar, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8710457

[42] "A Generic Future Mobility Sensing System for Travel Data Collection, Management, Fusion, and Visualization", Linlin You, Fang Zhao, Lynette Cheah, Kyungsoo Jeong, Pericles Christopher Zegras, and Moshe Ben-Akiva, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8833515

[43] "Evaluating citizens' willingness to uptake a MaaS tool for metropolitan multimodal trips", Andres Monzon, Iria Lopez-Carreiro, Elena Lopez, 2019: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=9071696

[44] "Mobility as a Service (MaaS) in rural regions: An overview", Luìs Barreto, Antonio Amaral, Sara Baltazar, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8710455

[45] "Want to Ride My Bicycle: a Microservice-Based Use Case for a MaaS Architecture", Franco Callegati, Giovanni Delnevo , Andrea Melis, Silvia Mirri, Marco Prandini, Paola Salomoni, 2017: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8024498

[46] "Concept of interlinking mobility services for urban transport towards intermodal mobility including private and shared electromobility", Daniel Breuer, Philipp Spichartz and Constantinos Sourkounis, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8813511

[47] "Innovative approach of the sharing E-Mobility", Mariacristina Roscia, Luigi Mingrone, Gianni Pignataro,

*Future Mobility Advances and Trends DOI: http://dx.doi.org/10.5772/intechopen.97108*

*Self-Driving Vehicles and Enabling Technologies*

[26] "Power Interchange Analysis for Reliable Vehicle-to-Grid Connectivity", Saba Al-Rubaye, Anwer Al-Dulaimi,

Selina Pan, Stephen M. Erlien, and J. Christian Gerdes, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7588150

[34] "Public Health, Ethics, and

March 2021)

Autonomous Vehicles", Janet Fleetwood, 2017: https://ajph.aphapublications.org/ doi/pdfplus/10.2105/AJPH.2016.303628

[35] "Smart Car Road Testing 101", 2020: https://www.acmwillowrun.org/smartcar-road-testing-101/ (Accessed by

[36] "Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy", Asif Faisal, Tan Yigitcanlar, Md Kamruzzaman, Graham Currie, 2018: https://conservancy.umn.edu/ bitstream/handle/11299/209218/JTLU\_ vol-12\_pp45-72.pdf?sequence=1

[37] "Driving Information Logger with In-Vehicle Communication for Autonomous Vehicle Research", Kyungbok Sung, Kyoungwook Min, and Jeongdan Choi, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8323732

[38] "New frontiers in driverless vehicles", Brad Pietras, 2015: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7088509

[39] "A Preliminary Investigation of an Autonomous Vehicle Validation Infrastructure for Smart Cities", Kyriakos M. Deliparaschos, Gergely Santha, Luca Zanotti Fragonara, Ivan Petrunin, Argyrios C. Zolotas, Antonios Tsourdos, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9201644

[40] "Development of Key Technologies for Autonomous Driving Vehicles", Jason Sheng-Hong Tsai, Jyh-Ching Juang, Chia-Heng Tu, Tzong-Yow Tsai, Pau-Choo Chung, Chih-Chung Hsu, Chao-Yang Lee, Ching-Fu Lin, 2019:

[27] "Optimized power flow control of smart grids with electric vehicles and DER", Metody Georgiev EORGIEV, Rad Stanev, Anastassia Krusteva, 2019: https://ieeexplore.ieee.org/stamp/stamp.

and Qiang Ni, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8808171

jsp?tp=&arnumber=8771575

[28] "Analysis of Electrical Vehicle behavior from real world data: a V2I Architecture", Luca Bascetta, Giambattista Gruosso, Giancarlo Storti Gajani, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8493203

[29] "Reliability Verification Procedure of Secured V2X Communication for Autonomous Cooperation Driving", Han-Gyun Jung, Dae-Kyo Shin, Ki-Taeg Lim, Sang-Hun Yoon, Seong-Keun Jin, Soo-Hyun Jang, Jae-Min Kwak, 2018: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=8539617

[30] "Functional architecture for autonomous driving and its implementation", Rihards Novickis, Aleksandrs Levinskis, Roberts Kadiis, Vitalijs Fescenko, Kaspars Ozols, 2020: https://ieeexplore.ieee.org/stamp/stamp.

jsp?tp=&arnumber=9276943

Simoudis, 2019: https://

[33] "Incorporating Ethical Considerations Int o Automated Vehicle Control", Sarah M. Thornton,

[31] "The autonomous mobility innovation lifecycle", Evangelos

ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8943257

[32] "Autonomous Vehicle Ethics Stock or Custom?", Sally Applin, 2017: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7948873

**170**

https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9024730

[41] "Urban Mobility Digitalization: Towards Mobility as a Service (MaaS)", Luìs Barreto, Antonio Amaral, Sara Baltazar, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8710457

[42] "A Generic Future Mobility Sensing System for Travel Data Collection, Management, Fusion, and Visualization", Linlin You, Fang Zhao, Lynette Cheah, Kyungsoo Jeong, Pericles Christopher Zegras, and Moshe Ben-Akiva, 2020: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8833515

[43] "Evaluating citizens' willingness to uptake a MaaS tool for metropolitan multimodal trips", Andres Monzon, Iria Lopez-Carreiro, Elena Lopez, 2019: https://ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=9071696

[44] "Mobility as a Service (MaaS) in rural regions: An overview", Luìs Barreto, Antonio Amaral, Sara Baltazar, 2018: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8710455

[45] "Want to Ride My Bicycle: a Microservice-Based Use Case for a MaaS Architecture", Franco Callegati, Giovanni Delnevo , Andrea Melis, Silvia Mirri, Marco Prandini, Paola Salomoni, 2017: https://ieeexplore.ieee.org/stamp/ stamp.jsp?tp=&arnumber=8024498

[46] "Concept of interlinking mobility services for urban transport towards intermodal mobility including private and shared electromobility", Daniel Breuer, Philipp Spichartz and Constantinos Sourkounis, 2019: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8813511

[47] "Innovative approach of the sharing E-Mobility", Mariacristina Roscia, Luigi Mingrone, Gianni Pignataro,

George Cristian Lazaroiu, 2016: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=7526011

[48] "The Future of Mobility—Electric, Autonomous, and Shared Vehicles", Paul R. Donnellan, 2018: https:// ieeexplore.ieee.org/stamp/stamp. jsp?tp=&arnumber=8625919

[49] "Mobility Sharing as a Preference Matching Problem", Hongmou Zhang and Jinhua Zhao, 2019: https:// ieeexploriee.org/stamp/stamp. jsp?tp=&arnumber=8478802

**173**

**Chapter 8**

**Abstract**

decisions.

**1. Introduction**

*Prem Chand Jain*

Trends in Next Generation

**Keywords:** ITS, ADAS, DSRC, C-V2X, LiDAR, Vehicle, Autonomous

There are many accidents occurring on roads due to negligence and lack of proper Intelligent transport system (ITS). Around 1.25 million people worldwide die from traffic accidents each year and between 20 to 50 million suffer from non-fatal injuries (WHO, May 2013). Studies proved that 60% of accidents can be avoided if a warning message is sent to that vehicle at least half a second before accident. The primary objective of ITS and related National highway traffic safety administration (NHTSA) to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. Manufacturers are adding ADAS to achieve greater safety in vehicles. ADAS additional cost will become low when ADAS is made part of vehicle cost. ADAS includes backup camera, lane-keeping steering, blind-spots detection,

Intelligent Transportation Systems

The objective of Intelligent transportation system (ITS) and related National highway traffic safety administration (NHTSA) is to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by the driver to take the decision. Vehicular communication is a part of Intelligent Transport System which provides an intelligent way of transport to avoid accidents. As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes important. Connected vehicles can be used for both infotainment and navigation for vehicle safety. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. C-V2X (Cellular-Vehicle-to-Everything) can provide better quality of service support, large coverage, and high data rate for moving vehicles. Deviceto-device (D2D) communication in C-V2X provides high reliability and low latency. In 5G Rel.16 C-V2X will become an integral part of 5G cellular network providing higher capacity, coverage, etc. Today old aged/disabled person look for driving technology that is convenient and easy to use. V2X technology will offset some of the concerns about old aged/disabled driver's abilities to respond quickly to challenge by driving environment as they no longer be required to handle most of the

#### **Chapter 8**

## Trends in Next Generation Intelligent Transportation Systems

*Prem Chand Jain*

#### **Abstract**

The objective of Intelligent transportation system (ITS) and related National highway traffic safety administration (NHTSA) is to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by the driver to take the decision. Vehicular communication is a part of Intelligent Transport System which provides an intelligent way of transport to avoid accidents. As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes important. Connected vehicles can be used for both infotainment and navigation for vehicle safety. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. C-V2X (Cellular-Vehicle-to-Everything) can provide better quality of service support, large coverage, and high data rate for moving vehicles. Deviceto-device (D2D) communication in C-V2X provides high reliability and low latency. In 5G Rel.16 C-V2X will become an integral part of 5G cellular network providing higher capacity, coverage, etc. Today old aged/disabled person look for driving technology that is convenient and easy to use. V2X technology will offset some of the concerns about old aged/disabled driver's abilities to respond quickly to challenge by driving environment as they no longer be required to handle most of the decisions.

**Keywords:** ITS, ADAS, DSRC, C-V2X, LiDAR, Vehicle, Autonomous

#### **1. Introduction**

There are many accidents occurring on roads due to negligence and lack of proper Intelligent transport system (ITS). Around 1.25 million people worldwide die from traffic accidents each year and between 20 to 50 million suffer from non-fatal injuries (WHO, May 2013). Studies proved that 60% of accidents can be avoided if a warning message is sent to that vehicle at least half a second before accident. The primary objective of ITS and related National highway traffic safety administration (NHTSA) to improve vehicle safety and reduce accidents, injuries, and deaths. Advanced driver assistance system (ADAS) is making a difference in vehicle safety. Manufacturers are adding ADAS to achieve greater safety in vehicles. ADAS additional cost will become low when ADAS is made part of vehicle cost. ADAS includes backup camera, lane-keeping steering, blind-spots detection,

automatic braking, parking assistance, pedestrian detection, traffic sign detection, night vision, etc. In ADAS, a cluster of sensors like video cameras, 77GHz millimeter (mm) wave radars like LiDAR (Light detection and ranging), and ultrasonic transducers feed their digital data via multiple serial interfaces to processors that store the data and process it. The vision processors prepare data for fusion processing, which combines the inputs from multiple sensors to produce feature recognition of nearby objects as well as their distance, motion, and status. They in turn make decisions and initiate the control of selected driving functions or provides driver notification by visual, audible signals. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by driver to take decision. ADAS development involves massive software which includes special algorithms as well as Artificial intelligence (AI) technique such as machine vision and deep learning. It requires popular processors, interfaces, programing, and AI tools to speed up and simplify development.

As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes essential. Automakers are looking to offload critical, time-sensitive decisions-making from passengers to autonomous vehicles through a complex set of sensors and communication with everything around the vehicle. Connected vehicles can be used for infotainment and navigation to vehicle safety. There is large potential for connecting other road users such as heavy duty vehicles, pedestrians, cyclists, etc. The introduction of a communication interface into vehicles will also provide a pathway for state and local government that operate transportation system to communicate safety information from the Road side units (RSU) to vehicles. For the same the RSUs are connected to the Traffic management center (TMC). Given the volume of data to be transmitted, the RSU are connected to TMC through some short of backhaul. Wide spread audio/video (AV) technology deployment for infotainment will require robust communication system and communication infrastructure capable of moving the Megabit data generated in AV system. The integrated In-Vehicle Infotainment (IVI) helps to improve automobiles safety by providing the driver high quality information from audio, video, radar, and other sensors. It generates a seamless 360 degree view of vehicle surroundings from multiple independent HD video streams from front, rear, and side-mounted cameras. IVI also provides high quality audio, video entertainment. Imagine 10 to 20 cameras providing 360 degree view, all sending 4 k (3840X2160) resolution HD video streams with pixel depth increasing from 16 to 20 or even 24 bits. A single 4 k video camera with 24bits per pixel will produce around 200Mbit per frame at 10 to 30 frames per sec. This will range overall data rate around 6Gbps.

One forthcoming technology to be adopted is Vehicle-to-Everything (V2X) radio communication. V2X improves ADAS safety by providing radio communication between vehicles, and between vehicles and nearby roadside units that supply valuable information. V2X is a broaden term which includes V2V, V2I (Infrastructure), in addition to objects such as pedestrian crossing road (V2P), detecting bicycles, motor cycles on a car lane, detecting traffic light conflicts, and Internet based networks (V2N) which distribute software and firmware updates to vehicles including HD maps shown in **Figure 1** [1]. V2X technology has been mandated by NHTSA. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. The V2I will connect vehicles to Infrastructure that can inform about traffic congestion, road conditions, weather alerts, and construction going on to provide safety as well as convenience. The V2V communication is to avoid accidents by sending data about position and speed of vehicle in transit to another

**175**

conclude the chapter.

**Figure 1.**

*V2X communication [1].*

**2. Internet of vehicles**

traffic signals, and city infrastructure.

**2.1 Vehicle-to-vehicle communication**

*Trends in Next Generation Intelligent Transportation Systems*

vehicle over an adhoc mesh network. It provides 360-degree awareness of surrounding threats. It supersedes techniques like blind spot detection, rear parking sonar, and backup camera. The main purpose of vehicle-to-vehicle communication is to provide an intelligent means of transport service. This is introduced in order to avoid accidents between vehicles by sending warning messages to each other. These warning messages consist of information regarding vehicles speed, emergency stopping, brake status, etc. V2V communication is like an additional step for warning the drivers. With the growth of mobile data, a cellular network has great potential to support various vehicular communication services for safety applications. Cellular system such as 4G-LTE can become the useful vehicle communication. Cellular V2X (C-V2X) can provide better quality of service (QoS) support, large coverage, and high data rate for moving vehicles. Device-to-device (D2D) communication in C-V2X provides high reliability and low latency, range, scalability, number of devices supported, security, and reduced cost of ownership. In 5G Rel. 16 C-V2X will be an integral part of 5G cellular network providing higher capacity, coverage. In this chapter Section 2 discusses V2X communication while Section 3 discusses Dedicated short range communication (DSRC). Section 4 discusses about Cellular vehicle-to-everything (C-V2X) while Section 5 discusses level of automation and Section 6 about self driving vehicles, and finally Section 7

Internet of vehicles (IoV) can be named as Internet of Things (IoT) on wheels. It will allow vehicles to communicate with their drivers, with other vehicles, with

Inter-Vehicle communication uses multi-hop multicast/broadcast to communicate between each vehicle. Collision warning messages broadcast from V2V across multi-hops. This is suitable for short range, a vehicle communicates with another vehicle by using different protocols. In such cases receiver takes appropriate

*DOI: http://dx.doi.org/10.5772/intechopen.97690*

*Trends in Next Generation Intelligent Transportation Systems DOI: http://dx.doi.org/10.5772/intechopen.97690*

#### **Figure 1.**

*Self-Driving Vehicles and Enabling Technologies*

range overall data rate around 6Gbps.

automatic braking, parking assistance, pedestrian detection, traffic sign detection, night vision, etc. In ADAS, a cluster of sensors like video cameras, 77GHz millimeter (mm) wave radars like LiDAR (Light detection and ranging), and ultrasonic transducers feed their digital data via multiple serial interfaces to processors that store the data and process it. The vision processors prepare data for fusion processing, which combines the inputs from multiple sensors to produce feature recognition of nearby objects as well as their distance, motion, and status. They in turn make decisions and initiate the control of selected driving functions or provides driver notification by visual, audible signals. The objective of ADAS is to provide a continuous picture environment surrounding the vehicle. This vision around the vehicle is seen by driver to take decision. ADAS development involves massive software which includes special algorithms as well as Artificial intelligence (AI) technique such as machine vision and deep learning. It requires popular processors,

interfaces, programing, and AI tools to speed up and simplify development.

As the transportation moves towards environment of connected and autonomous vehicles, the role of communication and data transfer becomes essential. Automakers are looking to offload critical, time-sensitive decisions-making from passengers to autonomous vehicles through a complex set of sensors and communication with everything around the vehicle. Connected vehicles can be used for infotainment and navigation to vehicle safety. There is large potential for connecting other road users such as heavy duty vehicles, pedestrians, cyclists, etc. The introduction of a communication interface into vehicles will also provide a pathway for state and local government that operate transportation system to communicate safety information from the Road side units (RSU) to vehicles. For the same the RSUs are connected to the Traffic management center (TMC). Given the volume of data to be transmitted, the RSU are connected to TMC through some short of backhaul. Wide spread audio/video (AV) technology deployment for infotainment will require robust communication system and communication infrastructure capable of moving the Megabit data generated in AV system. The integrated In-Vehicle Infotainment (IVI) helps to improve automobiles safety by providing the driver high quality information from audio, video, radar, and other sensors. It generates a seamless 360 degree view of vehicle surroundings from multiple independent HD video streams from front, rear, and side-mounted cameras. IVI also provides high quality audio, video entertainment. Imagine 10 to 20 cameras providing 360 degree view, all sending 4 k (3840X2160) resolution HD video streams with pixel depth increasing from 16 to 20 or even 24 bits. A single 4 k video camera with 24bits per pixel will produce around 200Mbit per frame at 10 to 30 frames per sec. This will

One forthcoming technology to be adopted is Vehicle-to-Everything (V2X) radio communication. V2X improves ADAS safety by providing radio communication between vehicles, and between vehicles and nearby roadside units that supply valuable information. V2X is a broaden term which includes V2V, V2I (Infrastructure), in addition to objects such as pedestrian crossing road (V2P), detecting bicycles, motor cycles on a car lane, detecting traffic light conflicts, and Internet based networks (V2N) which distribute software and firmware updates to vehicles including HD maps shown in **Figure 1** [1]. V2X technology has been mandated by NHTSA. Vehicle-to-vehicle (V2V) communication allows vehicles to talk to each other and exchange data about location, direction of travel, speed, brake, accelerator status, and other facts. This information is analyzed and used to avoid collision. The V2I will connect vehicles to Infrastructure that can inform about traffic congestion, road conditions, weather alerts, and construction going on to provide safety as well as convenience. The V2V communication is to avoid accidents by sending data about position and speed of vehicle in transit to another

**174**

*V2X communication [1].*

vehicle over an adhoc mesh network. It provides 360-degree awareness of surrounding threats. It supersedes techniques like blind spot detection, rear parking sonar, and backup camera. The main purpose of vehicle-to-vehicle communication is to provide an intelligent means of transport service. This is introduced in order to avoid accidents between vehicles by sending warning messages to each other. These warning messages consist of information regarding vehicles speed, emergency stopping, brake status, etc. V2V communication is like an additional step for warning the drivers. With the growth of mobile data, a cellular network has great potential to support various vehicular communication services for safety applications. Cellular system such as 4G-LTE can become the useful vehicle communication. Cellular V2X (C-V2X) can provide better quality of service (QoS) support, large coverage, and high data rate for moving vehicles. Device-to-device (D2D) communication in C-V2X provides high reliability and low latency, range, scalability, number of devices supported, security, and reduced cost of ownership. In 5G Rel. 16 C-V2X will be an integral part of 5G cellular network providing higher capacity, coverage. In this chapter Section 2 discusses V2X communication while Section 3 discusses Dedicated short range communication (DSRC). Section 4 discusses about Cellular vehicle-to-everything (C-V2X) while Section 5 discusses level of automation and Section 6 about self driving vehicles, and finally Section 7 conclude the chapter.

#### **2. Internet of vehicles**

Internet of vehicles (IoV) can be named as Internet of Things (IoT) on wheels. It will allow vehicles to communicate with their drivers, with other vehicles, with traffic signals, and city infrastructure.

#### **2.1 Vehicle-to-vehicle communication**

Inter-Vehicle communication uses multi-hop multicast/broadcast to communicate between each vehicle. Collision warning messages broadcast from V2V across multi-hops. This is suitable for short range, a vehicle communicates with another vehicle by using different protocols. In such cases receiver takes appropriate decision on the basis of emergency messages received and accordingly takes appropriate action. To avoid collision in V2V communication, location based multicast and broadcasting is used [2]. Multi-hop communication propagates the message in the absence of RSU infrastructure. However, in low density vehicular network V2V communication is not very good solution due to large range. V2V could eliminate 80% of crashes that do not involve alcohol or drugs.

#### **2.2 Vehicle-to-infrastructure communication**

Vehicle-to-Infrastructure (V2I) provides awareness of traffic light status, a road that is closed, to guide the vehicle around obstacles, traffic, road condition, weather, construction, etc. Vehicles connected to stationary infrastructure is known as Road side unit (RSU). Communication between vehicles and RSU are supported by V2R protocol. In V2R warning messages are sent first to RSU, and then RSU broadcast to all vehicles in the range. The Road side infrastructure involves additional installation costs. V2I provides large BW link between vehicles and RSU. The RSU can be deployed after every km to obtain high data rates required during heavy traffic. When a vehicle has mechanical failure or detects road hazards, vehicle generates an EWM (Emergency warning message) and keeps one copy with him for retransmission, if required. Vehicle broadcasts to neighboring vehicles and it transmits periodically to RSU also through transceivers with different frequency bands till it receives the message with the same ID from vehicle behind and RSU respectively. When RSU receives EWM from source vehicle, it replaces with own ID and forwards to all vehicles within the range [3].

#### **2.3 Vehicle-to-network communication**

Vehicles connected to Application server. It transforms connected transportation around the globe. It allows one way broadcast to multiple vehicles thereby facilitating V2N functions. The network based communication (V2N) operates over licensed spectrum to support telematics, connected infotainment, and growing variety of advanced informational safety use cases.

#### **2.4 Vehicle-to-pedestrian communication**

Vehicle is able to detect in advance pedestrians including cyclist, motor cycles in cross walks, blind spots, or other dangerous locations.

#### **3. Dedicated short range communication**

NHTSA proposed V2V technology called Dedicated short range communication (DSRC) for all new light vehicles. As a result IEEE approved an amendment to IEEE802.11 standard named as 802.11p for Wireless access in vehicle environment (WAVE). The 802.11p is enhancement of 802.11a Wireless local area network (WLAN) required supporting ITS applications [4]. This includes data exchange between high speed vehicles and between vehicles and Road side infrastructure (V2R) in ITS 5.9GHz band. The DSRC combines Wi-Fi and GPS positioning to get a 360-degree awareness of all vehicles around them. It helps to provide the driver with warning to avoid collision using on-board computer. The cars share their positions very rapidly even though two cars could be around a corner. DSRC allows Cooperative collision avoidance (CCA) in which cars warns each other about changing conditions

**177**

**Figure 2.**

*DSRC protocol stack.*

802.11a.

investment.

*Trends in Next Generation Intelligent Transportation Systems*

(25 ms) and packet delivery ratio is high compared to 802.11a [5].

to significantly improve safety. DSRC is a two way short-to-medium range wireless communication that permits very high data transmission in V2V communication. The main reason for using DSRC in V2V communication is to detect hazards in vehicle's path even though the driver in not in such a position to see. DSRC PHY (Physical) layer is targeted to operate in 5.9 GHz band (5.85–5.925GHz) with 75 MHz BW as opposed to IEEE 802.11a that allows only the unlicensed frequency band 5GHz. In MAC (Media access control) layer the DSRC band consists of seven channels each with 10 MHz BW and that include one control channel and 6 service channels. It can support a large family of vehicular safety and non-safety applications. Some requirements of MAC are low latency and high reliability. The PHY Layer provides better radio propagation with respect to multi-path reflection delay and Doppler effects occur due to high speed vehicles and road environment. The end-to-end delay is low

The 802.11p standard adds wireless access to vehicular networks and implements OSI layers stack. Upper layers of OSI follows IEEE1609 family standard as shown in **Figure 2**. Wireless Protocol works at licensed band of 5.9GHz with 300 m range, and data rate of 6 to 27Mbps. DSRC PHY layer adopts same OFDM and digital modulation types BPSK, QPSK, 16-QAM, 64-QAM as used in

The DSRC transmits Basic safety message (BSM) between vehicles. It includes information like exact vehicle location, direction of travel, speed, braking status, and some other data. The BSM is updated and transmitted 10 times per sec. DSRC is proven standard, mature technology, and cost effective but with little growth potential. Latency is around 25 ms which is not fast enough for collision avoidance action. Another application of DSRC is V2I but V2I depends on new development and deployment of infrastructure. This new infrastructure is a major

*DOI: http://dx.doi.org/10.5772/intechopen.97690*

#### *Trends in Next Generation Intelligent Transportation Systems DOI: http://dx.doi.org/10.5772/intechopen.97690*

*Self-Driving Vehicles and Enabling Technologies*

80% of crashes that do not involve alcohol or drugs.

**2.2 Vehicle-to-infrastructure communication**

and forwards to all vehicles within the range [3].

variety of advanced informational safety use cases.

cross walks, blind spots, or other dangerous locations.

**2.4 Vehicle-to-pedestrian communication**

**3. Dedicated short range communication**

**2.3 Vehicle-to-network communication**

decision on the basis of emergency messages received and accordingly takes appropriate action. To avoid collision in V2V communication, location based multicast and broadcasting is used [2]. Multi-hop communication propagates the message in the absence of RSU infrastructure. However, in low density vehicular network V2V communication is not very good solution due to large range. V2V could eliminate

Vehicle-to-Infrastructure (V2I) provides awareness of traffic light status, a road that is closed, to guide the vehicle around obstacles, traffic, road condition, weather, construction, etc. Vehicles connected to stationary infrastructure is known as Road side unit (RSU). Communication between vehicles and RSU are supported by V2R protocol. In V2R warning messages are sent first to RSU, and then RSU broadcast to all vehicles in the range. The Road side infrastructure involves additional installation costs. V2I provides large BW link between vehicles and RSU. The RSU can be deployed after every km to obtain high data rates required during heavy traffic. When a vehicle has mechanical failure or detects road hazards, vehicle generates an EWM (Emergency warning message) and keeps one copy with him for retransmission, if required. Vehicle broadcasts to neighboring vehicles and it transmits periodically to RSU also through transceivers with different frequency bands till it receives the message with the same ID from vehicle behind and RSU respectively. When RSU receives EWM from source vehicle, it replaces with own ID

Vehicles connected to Application server. It transforms connected transportation around the globe. It allows one way broadcast to multiple vehicles thereby facilitating V2N functions. The network based communication (V2N) operates over licensed spectrum to support telematics, connected infotainment, and growing

Vehicle is able to detect in advance pedestrians including cyclist, motor cycles in

NHTSA proposed V2V technology called Dedicated short range communication (DSRC) for all new light vehicles. As a result IEEE approved an amendment to IEEE802.11 standard named as 802.11p for Wireless access in vehicle environment (WAVE). The 802.11p is enhancement of 802.11a Wireless local area network (WLAN) required supporting ITS applications [4]. This includes data exchange between high speed vehicles and between vehicles and Road side infrastructure (V2R) in ITS 5.9GHz band. The DSRC combines Wi-Fi and GPS positioning to get a 360-degree awareness of all vehicles around them. It helps to provide the driver with warning to avoid collision using on-board computer. The cars share their positions very rapidly even though two cars could be around a corner. DSRC allows Cooperative collision avoidance (CCA) in which cars warns each other about changing conditions

**176**

to significantly improve safety. DSRC is a two way short-to-medium range wireless communication that permits very high data transmission in V2V communication. The main reason for using DSRC in V2V communication is to detect hazards in vehicle's path even though the driver in not in such a position to see. DSRC PHY (Physical) layer is targeted to operate in 5.9 GHz band (5.85–5.925GHz) with 75 MHz BW as opposed to IEEE 802.11a that allows only the unlicensed frequency band 5GHz. In MAC (Media access control) layer the DSRC band consists of seven channels each with 10 MHz BW and that include one control channel and 6 service channels. It can support a large family of vehicular safety and non-safety applications. Some requirements of MAC are low latency and high reliability. The PHY Layer provides better radio propagation with respect to multi-path reflection delay and Doppler effects occur due to high speed vehicles and road environment. The end-to-end delay is low (25 ms) and packet delivery ratio is high compared to 802.11a [5].

The 802.11p standard adds wireless access to vehicular networks and implements OSI layers stack. Upper layers of OSI follows IEEE1609 family standard as shown in **Figure 2**. Wireless Protocol works at licensed band of 5.9GHz with 300 m range, and data rate of 6 to 27Mbps. DSRC PHY layer adopts same OFDM and digital modulation types BPSK, QPSK, 16-QAM, 64-QAM as used in 802.11a.

The DSRC transmits Basic safety message (BSM) between vehicles. It includes information like exact vehicle location, direction of travel, speed, braking status, and some other data. The BSM is updated and transmitted 10 times per sec. DSRC is proven standard, mature technology, and cost effective but with little growth potential. Latency is around 25 ms which is not fast enough for collision avoidance action. Another application of DSRC is V2I but V2I depends on new development and deployment of infrastructure. This new infrastructure is a major investment.

**Figure 2.** *DSRC protocol stack.*

#### **4. Cellular vehicle-to-everything (C-V2X) communication**

The Automation industry was agreed upon DSRC but suddenly C-V2X popped up disrupting the DSRC plans. The DSRC will require new deployment of thousands of roadside units (RSU) and associated infrastructure network such as fiber backhaul along the roads. This is a challenge for rural areas considering vast distances involved. The progress of DSRC has been delayed because of new alternative radio technology based on cellular mobile communication called C-V2X. C-V2X utilizes cellular mobile technology to provide the link between the vehicles and rest of the world including other vehicles and traffic control system. C-V2X provide high performance for capacity, coverage, range, scalability, number of devices supported, and security. C-V2X can achieve longer range which can directly translates into earlier alert and better visibility of unexpected dangerous situation. It also allows vehicles to travel at higher speeds while still being able to stop in time to avoid hazardous conditions compared to DSRC. It was designed initially to use 4G-LTE cellular mobile standard defined in 3GPP Rel.14 [6]. The new version 5G (Rel. 15) includes device-to-device (D2D) communication (V2V, V2I, V2P) and device-to-network (V2N) which will transform connected transportation around the globe [7]. The 4G-LTE and 5G can provide RSU functions eliminating the need of additional RSUs in DSRC. The V2V and V2I will connect and interact with ADAS providing intelligence beyond the short range environment covered by ADAS sensors. V2V and V2I will make ADAS an attractive alternative to full automation. Finally security is a major factor, if automobiles are connected to the Internet where they may be exposed to hack.

C-V2X also uses 5.9GHz band but instead of OFDM, it uses Single carrier-Frequency division multiple access (SC-FDMA) to lower down the Peak to average power ratio (PAPR) to reduce power consumption. It uses Turbo coding and Hybrid automatic repeat request (HARQ ) protocol to enhance reliability in data transfer at high vehicle speeds, and lower latency (< 5 ms). C-V2X is designed to be globally compatible with 5G. The 5G will provide very high throughput, high reliability, low latency, and accurate position determination. 5G can offer multigigabit speeds for infotainment, telematics, and teleoperation. C-V2X is designed to offer low latency communication to V2V, V2I, and V2P. C-V2X encompasses two transmission modes, direct communication (V2V), and network based communication (V2N). The network based communication utilizes 4G and emerging 5G cellular network for V2N, and operates over licensed spectrum to support telematics, connected infotainment, and growing variety of advanced informational safety use cases. C-V2X is the gateway to the connecting vehicles and in long run to the self-driving vehicles. Full automated driving will be in 5G environment and C-V2X will be the bridge towards 5G [8]. C-V2X will be able to take 5G network advantages namely enhanced mobile broadband (eMBB), ultra low-latency communication (uRLLC), and massive scale machine-to-machine (M2M) communication (mMTC). This will enable more V2X services by providing long range, higher density, very high throughput, reliability, high precision positioning, and ultra low latency (1 ms). LTE variant LTE-m (Machine) and Narrow band (NB)-IoT Low power WAN (LPWAN) are not fast enough. LTE-b (Broadcast) is another variant which allows one way broadcast to multiple vehicles thereby facilitating V2I and V2N functions. 5G Automation association (5GAA) has 50+ automobile manufacturers, and mobile network industry including Audi, BMW, Daimler, Ericsson, Huawei, Intel, Nokia, Qualcomm to collaborate between automotive and mobile communication industry. 5GAA has recommended C-V2X to NHTSA. After taking the decision, 2 years period

**179**

*Trends in Next Generation Intelligent Transportation Systems*

would occur to accommodate manufacturers product development cycle, and full

Some potential candidates for V2V and V2I in 4G LTE cellular network are LTE-m and NB-IoT (Rel 13). LTE-m (Machine) is a versatile technology, supporting high data rates, mobility, and voice facility. It is a stripped version of LTE, uses 1.4 MHz instead of 20 MHz BW. Reduction in BW to 1.4 MHz will reduce size of FFT blocks results in cost reduction by 28%. Power consumption will also reduce as fewer number of subcarriers needs to be processed at RF level. This will further reduce the cost by 20 to 30% by means of RF transceiver design including low noise amplifier, mixer, and local oscillator. Overall average 39% cost saving and also modem complexity by 50% observed [9]. It effectively provides down link and uplink peek rates of 1Mbps covering 1.08 MHz bandwidth in half duplex mode. LTE-m supports full voice functionality via Voice over LTE (VoLTE) along with full mobility and in-vehicle hand-over. The major reason is that it can serve in automotive sector because of its extended range, deep penetration in buildings and basement, and low latency. The maximum uplink power transmitted by device is 23 dBm, and 46 dBm for downlink with 10–15 ms latency. It also supports power saving mode– sends an acknowledgement before going to sleep and then on waking up sends check along with data (if any) to the network.

NB-IoT uses different technoloy (DSSS modulation in place of OFDM), but operates in LTE band [10]. With NB-IoT gatewys are not required, and thus sensor data is directly tranamitted to main server. NB-IoT has an advantage of low cost and lesser power requirements. The maximum tarnsmitted power is 20 dBm over 200 kHz bandwith (180 kHz one resource block). The complexity is reduced by 75% as compared to the LTE-m. Down link and uplink peek data rates supported by NB-IoT is around 250 kbps with 1.6 to 10sec latency. It works best for applications that requires moderate latency and throughput. It uses licensed band which eliminates interference and provides high security. It can provide 50 k to 100k vehicles connections per cell. It can operate by uploading a new software on LTE infrastructure. When transmitting 200 bytes in day on an average, one can achieve 10 years battery life time. NB-IoT Rel. 13 lacks mobile support and high power consumption while NB-IoT Rel. 14 support 160 kbps data rate and lower transmit power level.

Autonomous vehicles users will expect that their vehicle should provide seamless Internet connectivity to their laptop, mobile phone as provided in living room. It will be possible by using automotive Ethernet [11]. Ethernet is well known ubiquitous solution to traditional LAN (Local area network). The advantage of Ethernet is multipoint connections, higher BW, and low latency. IEEE introduced 802.3bw for automotive applications called 100Base-T1 supporting 100Mbps data on a single balanced twisted pair cable CAT5 or CAT6 of 15 m length [12]. To achieve 100Mbps it uses 3 bit per symbol (PAM3). It supports full duplex. Power over Ethernet (PoE) is being investigated and standardized using IEEE802.3bu with one pair power over data line group. The Gigabit ethernet (GbE) for 2.5/5/10GBase-T1 on single pair of wires standardized using IEEE802.3ch, is also being investigated for infotainment. Audi, BMW Mercedes have began implementation of Ethernet based connectivity.

*DOI: http://dx.doi.org/10.5772/intechopen.97690*

**4.1 LTE-m**

**4.2 NB-IoT**

**4.3 Automotive Ethernet**

compliance would require additional 2 years.

would occur to accommodate manufacturers product development cycle, and full compliance would require additional 2 years.

#### **4.1 LTE-m**

*Self-Driving Vehicles and Enabling Technologies*

they may be exposed to hack.

**4. Cellular vehicle-to-everything (C-V2X) communication**

The Automation industry was agreed upon DSRC but suddenly C-V2X popped up disrupting the DSRC plans. The DSRC will require new deployment of thousands of roadside units (RSU) and associated infrastructure network such as fiber backhaul along the roads. This is a challenge for rural areas considering vast distances involved. The progress of DSRC has been delayed because of new alternative radio technology based on cellular mobile communication called C-V2X. C-V2X utilizes cellular mobile technology to provide the link between the vehicles and rest of the world including other vehicles and traffic control system. C-V2X provide high performance for capacity, coverage, range, scalability, number of devices supported, and security. C-V2X can achieve longer range which can directly translates into earlier alert and better visibility of unexpected dangerous situation. It also allows vehicles to travel at higher speeds while still being able to stop in time to avoid hazardous conditions compared to DSRC. It was designed initially to use 4G-LTE cellular mobile standard defined in 3GPP Rel.14 [6]. The new version 5G (Rel. 15) includes device-to-device (D2D) communication (V2V, V2I, V2P) and device-to-network (V2N) which will transform connected transportation around the globe [7]. The 4G-LTE and 5G can provide RSU functions eliminating the need of additional RSUs in DSRC. The V2V and V2I will connect and interact with ADAS providing intelligence beyond the short range environment covered by ADAS sensors. V2V and V2I will make ADAS an attractive alternative to full automation. Finally security is a major factor, if automobiles are connected to the Internet where

C-V2X also uses 5.9GHz band but instead of OFDM, it uses Single carrier-Frequency division multiple access (SC-FDMA) to lower down the Peak to average power ratio (PAPR) to reduce power consumption. It uses Turbo coding and Hybrid automatic repeat request (HARQ ) protocol to enhance reliability in data transfer at high vehicle speeds, and lower latency (< 5 ms). C-V2X is designed to be globally compatible with 5G. The 5G will provide very high throughput, high reliability, low latency, and accurate position determination. 5G can offer multigigabit speeds for infotainment, telematics, and teleoperation. C-V2X is designed to offer low latency communication to V2V, V2I, and V2P. C-V2X encompasses two transmission modes, direct communication (V2V), and network based communication (V2N). The network based communication utilizes 4G and emerging 5G cellular network for V2N, and operates over licensed spectrum to support telematics, connected infotainment, and growing variety of advanced informational safety use cases. C-V2X is the gateway to the connecting vehicles and in long run to the self-driving vehicles. Full automated driving will be in 5G environment and C-V2X will be the bridge towards 5G [8]. C-V2X will be able to take 5G network advantages namely enhanced mobile broadband (eMBB), ultra low-latency communication (uRLLC), and massive scale machine-to-machine (M2M) communication (mMTC). This will enable more V2X services by providing long range, higher density, very high throughput, reliability, high precision positioning, and ultra low latency (1 ms). LTE variant LTE-m (Machine) and Narrow band (NB)-IoT Low power WAN (LPWAN) are not fast enough. LTE-b (Broadcast) is another variant which allows one way broadcast to multiple vehicles thereby facilitating V2I and V2N functions. 5G Automation association (5GAA) has 50+ automobile manufacturers, and mobile network industry including Audi, BMW, Daimler, Ericsson, Huawei, Intel, Nokia, Qualcomm to collaborate between automotive and mobile communication industry. 5GAA has recommended C-V2X to NHTSA. After taking the decision, 2 years period

**178**

Some potential candidates for V2V and V2I in 4G LTE cellular network are LTE-m and NB-IoT (Rel 13). LTE-m (Machine) is a versatile technology, supporting high data rates, mobility, and voice facility. It is a stripped version of LTE, uses 1.4 MHz instead of 20 MHz BW. Reduction in BW to 1.4 MHz will reduce size of FFT blocks results in cost reduction by 28%. Power consumption will also reduce as fewer number of subcarriers needs to be processed at RF level. This will further reduce the cost by 20 to 30% by means of RF transceiver design including low noise amplifier, mixer, and local oscillator. Overall average 39% cost saving and also modem complexity by 50% observed [9]. It effectively provides down link and uplink peek rates of 1Mbps covering 1.08 MHz bandwidth in half duplex mode. LTE-m supports full voice functionality via Voice over LTE (VoLTE) along with full mobility and in-vehicle hand-over. The major reason is that it can serve in automotive sector because of its extended range, deep penetration in buildings and basement, and low latency. The maximum uplink power transmitted by device is 23 dBm, and 46 dBm for downlink with 10–15 ms latency. It also supports power saving mode– sends an acknowledgement before going to sleep and then on waking up sends check along with data (if any) to the network.

#### **4.2 NB-IoT**

NB-IoT uses different technoloy (DSSS modulation in place of OFDM), but operates in LTE band [10]. With NB-IoT gatewys are not required, and thus sensor data is directly tranamitted to main server. NB-IoT has an advantage of low cost and lesser power requirements. The maximum tarnsmitted power is 20 dBm over 200 kHz bandwith (180 kHz one resource block). The complexity is reduced by 75% as compared to the LTE-m. Down link and uplink peek data rates supported by NB-IoT is around 250 kbps with 1.6 to 10sec latency. It works best for applications that requires moderate latency and throughput. It uses licensed band which eliminates interference and provides high security. It can provide 50 k to 100k vehicles connections per cell. It can operate by uploading a new software on LTE infrastructure. When transmitting 200 bytes in day on an average, one can achieve 10 years battery life time. NB-IoT Rel. 13 lacks mobile support and high power consumption while NB-IoT Rel. 14 support 160 kbps data rate and lower transmit power level.

#### **4.3 Automotive Ethernet**

Autonomous vehicles users will expect that their vehicle should provide seamless Internet connectivity to their laptop, mobile phone as provided in living room. It will be possible by using automotive Ethernet [11]. Ethernet is well known ubiquitous solution to traditional LAN (Local area network). The advantage of Ethernet is multipoint connections, higher BW, and low latency. IEEE introduced 802.3bw for automotive applications called 100Base-T1 supporting 100Mbps data on a single balanced twisted pair cable CAT5 or CAT6 of 15 m length [12]. To achieve 100Mbps it uses 3 bit per symbol (PAM3). It supports full duplex. Power over Ethernet (PoE) is being investigated and standardized using IEEE802.3bu with one pair power over data line group. The Gigabit ethernet (GbE) for 2.5/5/10GBase-T1 on single pair of wires standardized using IEEE802.3ch, is also being investigated for infotainment. Audi, BMW Mercedes have began implementation of Ethernet based connectivity.

#### **5. Level of automation**

There are five levels of automation defined by the Society of automation engineers (SAE) [13]. Level 0 has no automation, driver performs all the functions. In level 1 driver performs all the functions but ADAS system provides alerts and partial control. Level 2 defines partial automation. Driver must still monitor actions but automated system controls braking, steering, and acceleration. Level 3 called automated driving systems performs all driving activities. Driver must still be available to take control in special circumstances. Level 4 automated driving systems perform all driving activities. Driver may still control the vehicle if needed or desired. Finally in level 5 automation no driver is needed.

#### **6. Self driving cars**

Self driving cars also referred as Autonomous vehicles. It improves automotive safety and provides help to old age and handicapped citizen who may not be able to drive in difficult traffic conditions. Uber and Ola my also like to reduce the cost of personnel in driving activities. Currently automation level is 1 and 2. Testing is being carried out for level 4 and 5 but final product on road may take long time. Autonomous vehicles need ADAS with full sensor inputs from Radar, LiDAR, Video camera (360 degree field of view), and Ultrasound sensor unit. GNSS/GPS navigation mapping is also essential. Most modern vehicles use simultaneous location and mapping algorithm. It combines information from multiple sensors and an off-line map to calculate current vehicle location and generate more real-time map of the current environment. Real time HD mapping is critical ingredient for automated driving. HD maps play a critical role in path planning at cm level distance. All the data received from sensors are processed in real time so that steering, braking, and accelerator setting outputs are generated. This requires massive computing. Artificial intelligence (AI) has been responsible to implement because of improved performance of processors like GPU (Graphics processing unit). Some applications uses GPU cluster for training neural network. The challenge in neural networks is to determine weights, and number of nodes in each layer, and number of layers (or depth) of system. The weights are determined by training the network via set of inputs to recognize the object. Training uses feedback system when an input is matched with outputs and internal hidden layer weights are adjusted. Self driving cars do not sleep, do not drink, do not get phone calls, will certainly reduce car accidents caused by human error.

Auto Industries already ahead with manufacturers like Tesla, Audi, Mercedes, BMW produce level 2 automobile where driver not have to physically operate the vehicle, and can have his hands off the steering wheel and foot-off the accelerator/brake pedals at the same time. In level 3 human drivers fail to properly take over when necessary, or drivers of other cars are at fault. The Google automotive spin-off Waymo has recently started to test level 4 vehicle on public roads in Arizona, USA. According to GSMA 2013, 500 million cars will be connected by 2025, and 75% of cars on the road will be autonomous by 2035 as per Navigation Research 2013.

#### **6.1 Autonomous motor bikes**

A new self driving motor bikes developed by M/S AB Dynamics promises to allow ADAS and autonomous system to be tested under much challenging

**181**

possible.

*Trends in Next Generation Intelligent Transportation Systems*

conditions. Motor bikes stability control utilizes advanced gyroscopes and accelerometers to detect parameters such as speed, lean angles, and braking force, and can quickly adjust electronic braking and throttle settings to help prevent crash. The system provides assistance by continuously monitoring a compressive set of key vehicle data including torque, lean angle, and acceleration to detect critical situations. This improves both riding stability and braking performance. According to Bosch Accident Research motor bike-to-car communication could prevent nearly 1/3 of the motor cycle accidents. The system uses DSRC IEEE802.11p. The motor bike will exchange information up to 10 times per sec. with other vehicles on the road within radius of several hundred meters. The information consists of vehicle type, speed, position, and directional travel. When a motor bike ends up in a car's blind spot or changes lanes to pass, this technology informs the car that motor bike is approaching. If system identifies a potential dangerous situation, it can warn the rider by sounding an alarm and flashing a warning notice on the dash board. The blind spot warning system works similar to those implemented in a car. A radar sensor serves as the blind spot recognition system's electronic eye, registering objects in hard-to-sea areas. The small radar sensor will help to detect vehicles approaching and offer a warning ideally by illuminating light in the appropriate side mirror. This system keeps a lookout in all directions to add motorcyclist change lanes safely. The system is active as soon as the vehicle starts and it supports the rider in all relevant speed ranges. If the system detects another vehicle is dangerously close and the rider does not react to the situation, it warn rider by way of an

The streets of China, Asia, and India are filled with millions of motor bikes, manufacturers feel that autonomous technology built in to motor bikes can be a good solution to manage the movements of vehicles. Kawasaki, BMW, Honda, Yamaha, and Ford are making a lot of headway to bring the concept to fruition

V2X communication benefits the environment by reducing traffic jams that increases pollution. The coordination between V2I will reduce unnecessary braking further reduce fuel consumption and emission. C-V2X will save millions of lives but it will take time to equip into vehicles on road. The mobile network operators (MNO) need to offer C-V2X services by extending their networks to accommodate the C-V2X applications. For the same, service agreement would be required for each vehicle. Embedded SIM (eSIM) can be soldered in to cellular device of vehicles. GSMA has developed such eSIM profile specifications. ADAS and V2X form full autonomous vehicles. From level of automation it can be seen that level 5 automation may take long time to achieve with above, but level 4 can be achieved in shorter time. Although full automation is a goal but perhaps a better solution is simply let AI complement the driver rather than replace the driver. While some learning and adaptation will be required by the human, the powerful combination of human/AI should be able to provide the best safety improvement everyone needs. With C-V2X, 5G cellular network, and AI the intelligent connected vehicles will stay at the forefront of the automotive industry. Growing manufacturers have come to the conclusion that C-V2X is superior to DSRC IEEE802.11p technology. Global shifting is towards C-V2X as C-V2X is superior in a sense it enables not only V2V services, but in addition V2N services are also

*DOI: http://dx.doi.org/10.5772/intechopen.97690*

acoustic or optical signal.

much sooner.

**7. Conclusions**

#### *Trends in Next Generation Intelligent Transportation Systems DOI: http://dx.doi.org/10.5772/intechopen.97690*

*Self-Driving Vehicles and Enabling Technologies*

There are five levels of automation defined by the Society of automation engineers (SAE) [13]. Level 0 has no automation, driver performs all the functions. In level 1 driver performs all the functions but ADAS system provides alerts and partial control. Level 2 defines partial automation. Driver must still monitor actions but automated system controls braking, steering, and acceleration. Level 3 called automated driving systems performs all driving activities. Driver must still be available to take control in special circumstances. Level 4 automated driving systems perform all driving activities. Driver may still control the vehicle if needed

Self driving cars also referred as Autonomous vehicles. It improves automotive safety and provides help to old age and handicapped citizen who may not be able to drive in difficult traffic conditions. Uber and Ola my also like to reduce the cost of personnel in driving activities. Currently automation level is 1 and 2. Testing is being carried out for level 4 and 5 but final product on road may take long time. Autonomous vehicles need ADAS with full sensor inputs from Radar, LiDAR, Video camera (360 degree field of view), and Ultrasound sensor unit. GNSS/GPS navigation mapping is also essential. Most modern vehicles use simultaneous location and mapping algorithm. It combines information from multiple sensors and an off-line map to calculate current vehicle location and generate more real-time map of the current environment. Real time HD mapping is critical ingredient for automated driving. HD maps play a critical role in path planning at cm level distance. All the data received from sensors are processed in real time so that steering, braking, and accelerator setting outputs are generated. This requires massive computing. Artificial intelligence (AI) has been responsible to implement because of improved performance of processors like GPU (Graphics processing unit). Some applications uses GPU cluster for training neural network. The challenge in neural networks is to determine weights, and number of nodes in each layer, and number of layers (or depth) of system. The weights are determined by training the network via set of inputs to recognize the object. Training uses feedback system when an input is matched with outputs and internal hidden layer weights are adjusted. Self driving cars do not sleep, do not drink, do not get phone calls, will certainly reduce car

Auto Industries already ahead with manufacturers like Tesla, Audi, Mercedes, BMW produce level 2 automobile where driver not have to physically operate the vehicle, and can have his hands off the steering wheel and foot-off the accelerator/brake pedals at the same time. In level 3 human drivers fail to properly take over when necessary, or drivers of other cars are at fault. The Google automotive spin-off Waymo has recently started to test level 4 vehicle on public roads in Arizona, USA. According to GSMA 2013, 500 million cars will be connected by 2025, and 75% of cars on the road will be autonomous by 2035 as per Navigation

A new self driving motor bikes developed by M/S AB Dynamics promises to allow ADAS and autonomous system to be tested under much challenging

or desired. Finally in level 5 automation no driver is needed.

**5. Level of automation**

**6. Self driving cars**

accidents caused by human error.

**6.1 Autonomous motor bikes**

**180**

Research 2013.

conditions. Motor bikes stability control utilizes advanced gyroscopes and accelerometers to detect parameters such as speed, lean angles, and braking force, and can quickly adjust electronic braking and throttle settings to help prevent crash. The system provides assistance by continuously monitoring a compressive set of key vehicle data including torque, lean angle, and acceleration to detect critical situations. This improves both riding stability and braking performance. According to Bosch Accident Research motor bike-to-car communication could prevent nearly 1/3 of the motor cycle accidents. The system uses DSRC IEEE802.11p. The motor bike will exchange information up to 10 times per sec. with other vehicles on the road within radius of several hundred meters. The information consists of vehicle type, speed, position, and directional travel. When a motor bike ends up in a car's blind spot or changes lanes to pass, this technology informs the car that motor bike is approaching. If system identifies a potential dangerous situation, it can warn the rider by sounding an alarm and flashing a warning notice on the dash board. The blind spot warning system works similar to those implemented in a car. A radar sensor serves as the blind spot recognition system's electronic eye, registering objects in hard-to-sea areas. The small radar sensor will help to detect vehicles approaching and offer a warning ideally by illuminating light in the appropriate side mirror. This system keeps a lookout in all directions to add motorcyclist change lanes safely. The system is active as soon as the vehicle starts and it supports the rider in all relevant speed ranges. If the system detects another vehicle is dangerously close and the rider does not react to the situation, it warn rider by way of an acoustic or optical signal.

The streets of China, Asia, and India are filled with millions of motor bikes, manufacturers feel that autonomous technology built in to motor bikes can be a good solution to manage the movements of vehicles. Kawasaki, BMW, Honda, Yamaha, and Ford are making a lot of headway to bring the concept to fruition much sooner.

#### **7. Conclusions**

V2X communication benefits the environment by reducing traffic jams that increases pollution. The coordination between V2I will reduce unnecessary braking further reduce fuel consumption and emission. C-V2X will save millions of lives but it will take time to equip into vehicles on road. The mobile network operators (MNO) need to offer C-V2X services by extending their networks to accommodate the C-V2X applications. For the same, service agreement would be required for each vehicle. Embedded SIM (eSIM) can be soldered in to cellular device of vehicles. GSMA has developed such eSIM profile specifications. ADAS and V2X form full autonomous vehicles. From level of automation it can be seen that level 5 automation may take long time to achieve with above, but level 4 can be achieved in shorter time. Although full automation is a goal but perhaps a better solution is simply let AI complement the driver rather than replace the driver. While some learning and adaptation will be required by the human, the powerful combination of human/AI should be able to provide the best safety improvement everyone needs. With C-V2X, 5G cellular network, and AI the intelligent connected vehicles will stay at the forefront of the automotive industry. Growing manufacturers have come to the conclusion that C-V2X is superior to DSRC IEEE802.11p technology. Global shifting is towards C-V2X as C-V2X is superior in a sense it enables not only V2V services, but in addition V2N services are also possible.

### **Acknowledgements**

The author is thankful to Prof. Dinkar Prasad, Head, EE Dept., and Associate Dean, and Prof. Sandeep Sen, Dean of School of Engineering, Shiv Nadar University, G. Noida (UP) for his encouragement, and permission to publish this paper.

### **Author details**

Prem Chand Jain EE Department, School of Engineering, Shiv Nadar University, Greater Noida, UP, India

\*Address all correspondence to: premchand.jain@snu.edu.in

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**183**

June, 2017

*Trends in Next Generation Intelligent Transportation Systems*

[10] ----, "NB-IoT deployment guide to basic feature set requirements", GSMA,

[11] D. Porter, "100Base-T1 Ethernet:

[12] ---, IEEE standard for Ethernet amendment 1: Physical layer specifications and management

[13] ---, "SAE Standards", SAE International, March, 2017

networking", Texas Instruments White

parameters for 100Mbps operation over a single balanced twisted pair cable (100Base-T1)", IEEE Standard 802.3bw,

White Paper, 02 August 2017.

The evolution of automotive

Paper, April 2018, pp 1-10.

2015, pp 39-63.

*DOI: http://dx.doi.org/10.5772/intechopen.97690*

Karedal, C.F. Mecklenbräuker, "A survey on vehicle-to-vehicle propagation channels", Proceedings of the IEEE Wireless Communications, vol. 16, no.

[1] A.F. Molisch, F. Tufvesson, J.

[2] S. Biswas, R. Tatchikou, F. Dion,

communication protocols for enhancing

Communications Magazine, vol. 44, no.

[3] B. Hu, H. Gharavi, "A joint vehicle-

Corporation, International Journal of

[4] ---, "Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications", IEEE Standard

Telecommunications and information exchange between systems-Local and metropolitan area networks- Specific requirements-Part 11, IEEE Std. 802.11-

[5] Y.J. Li, "An overview of the DSRC/ WAVE technology", NICTA, NSW, Australia Report, 2015, pp 1-15.

[6] ----, "Initial cellular V2X standard

[7] A. Papathanassion, A. Khoryacu, "Cellular V2X as essential enabler of

transportation services", IEEE Future Networks Enabling 5G and Beyond,

[8] ----, "The case for cellular V2X for safety and cooperative driving-5GAA",

[9] ---, "LTE-M: Optimizing LTE for Internet of things", Nokia Network

White Paper, 2015, pp 1-16.

completed", 3GPP, Sept., 2016

superior global connected

5GAA, 23 Nov., 2016

"Vehicle-to-vehicle wireless

highway traffic safety", IEEE

vehicle and vehicle-roadside communication for highway traffic safety", Hindawi Publishing

Vehicular Technology, 2011

for Information technology-

2012, 6 Feb., 2012

**References**

6, 2009, pp 12-22.

1, 2006, pp 74-82.

*Trends in Next Generation Intelligent Transportation Systems DOI: http://dx.doi.org/10.5772/intechopen.97690*

#### **References**

*Self-Driving Vehicles and Enabling Technologies*

The author is thankful to Prof. Dinkar Prasad, Head, EE Dept., and Associate

Dean, and Prof. Sandeep Sen, Dean of School of Engineering, Shiv Nadar University, G. Noida (UP) for his encouragement, and permission to publish

**Acknowledgements**

this paper.

**182**

**Author details**

Prem Chand Jain

Greater Noida, UP, India

EE Department, School of Engineering, Shiv Nadar University,

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: premchand.jain@snu.edu.in

provided the original work is properly cited.

[1] A.F. Molisch, F. Tufvesson, J. Karedal, C.F. Mecklenbräuker, "A survey on vehicle-to-vehicle propagation channels", Proceedings of the IEEE Wireless Communications, vol. 16, no. 6, 2009, pp 12-22.

[2] S. Biswas, R. Tatchikou, F. Dion, "Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety", IEEE Communications Magazine, vol. 44, no. 1, 2006, pp 74-82.

[3] B. Hu, H. Gharavi, "A joint vehiclevehicle and vehicle-roadside communication for highway traffic safety", Hindawi Publishing Corporation, International Journal of Vehicular Technology, 2011

[4] ---, "Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications", IEEE Standard for Information technology-Telecommunications and information exchange between systems-Local and metropolitan area networks- Specific requirements-Part 11, IEEE Std. 802.11- 2012, 6 Feb., 2012

[5] Y.J. Li, "An overview of the DSRC/ WAVE technology", NICTA, NSW, Australia Report, 2015, pp 1-15.

[6] ----, "Initial cellular V2X standard completed", 3GPP, Sept., 2016

[7] A. Papathanassion, A. Khoryacu, "Cellular V2X as essential enabler of superior global connected transportation services", IEEE Future Networks Enabling 5G and Beyond, June, 2017

[8] ----, "The case for cellular V2X for safety and cooperative driving-5GAA", 5GAA, 23 Nov., 2016

[9] ---, "LTE-M: Optimizing LTE for Internet of things", Nokia Network White Paper, 2015, pp 1-16.

[10] ----, "NB-IoT deployment guide to basic feature set requirements", GSMA, White Paper, 02 August 2017.

[11] D. Porter, "100Base-T1 Ethernet: The evolution of automotive networking", Texas Instruments White Paper, April 2018, pp 1-10.

[12] ---, IEEE standard for Ethernet amendment 1: Physical layer specifications and management parameters for 100Mbps operation over a single balanced twisted pair cable (100Base-T1)", IEEE Standard 802.3bw, 2015, pp 39-63.

[13] ---, "SAE Standards", SAE International, March, 2017

### *Edited by Marian Găiceanu*

This book examines the development and technical progress of self-driving vehicles in the context of the Vision Zero project from the European Union, which aims to eliminate highway system fatalities and serious accidents by 2050. It presents the concept of Autonomous Driving (AD) and discusses its applications in transportation, logistics, space, agriculture, and industrial and home automation.

Published in London, UK © 2021 IntechOpen © metamorworks / iStock

Self-Driving Vehicles and Enabling Technologies

IntechOpen Book Series

Artificial Intelligence, Volume 6

Self-Driving Vehicles and

Enabling Technologies

*Edited by Marian Găiceanu*