**1. Introduction**

Evolution has always been a fundamental component of life and technology developments have always represented a fundamental step in human civilization evolution. In fact, it is possible to say that technology speeds up everyday life thanks to the continuous introduction of innovative techniques, new devices and new perspectives. This results in turn in huge modifications in human activities perception, due to the time involved, their safety and in general their degree of difficulty.

Among the various cases of the daily life, one of the most discussed and interesting issue of the last years is related to automated or self-driving vehicles (AVs). The introduction of such vehicles resulted in the fact that nowadays car company cannot think of just projecting the mechanical parts or the basic electronic used in the vehicle, but are also involved in the project of sensors, integration issues and in the development of the related software.

In this way the integration of electronic components has become a necessary part in the vehicle development, in order to obtain an increase in safety and in easiness of the driving experience (e.g. Anti-Breaking Systems, Hydraulic Break Assist, Electronic Stability Control, etc.), as well as a reduction of impacts such as air

pollution, noise, fuel consumption. This resulted in a major cooperation between companies coming from different backgrounds and in the creation of partnerships and joint ventures among them.

These effects result in a renewed impulse in the research related to the vehicles, due to the growing mingling among the various sectors of the industry. The common goal is to develop new models or update the old ones to simulate real life situations and predict the future developments of the automotive and, in general, of transportation research field. Considering the field of transportation systems engineering, it is possible to state that right now the main focus is to achieve a deeper understanding of the hardware and software involvement in this new kind of vehicles. This, in turn, allows to obtain better models developments and more reliable scenario assessment. These issues are often accentuated by the impossibility of retrieving commercial standards, due to the fact that, in some cases, they are not yet available, or the vehicles are still prototypes.

New technologies for automated vehicles look very appealing, but, it may easily be anticipated that the time needed to turn the existing stock of traditional vehicles (TVs) into the new ones will last several years during which mixed traffic is expected, requiring ad hoc tools for analysis and design [1].

Moreover, the likely effects on congestion, and more generally traffic management and control, are not necessarily positive. Some of them are enlisted below, together with indications of needs of new models:


On the other hand, some positive social impacts may also be anticipated such as

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*Advanced Vehicles: Challenges for Transportation Systems Engineering*

• easier integration with medium/long-distance transportation.

• providing an analysis on sensors used in the automotive field,

• increase of generated flows, due to increase of mobility index and reference

• discussing the most likely positive and negative effects of mixed flow expected

• reviewing the most effective tools already available for macroscopic analysis of

A vehicle classification based on available sensors is surely helpful to support specification and calibration of models for transportation systems analysis, thus a sensor critical analysis is carried out in Section 2, supporting the discussion of classification issues in the same Section 2. Section 3 discusses the main tools for the analysis of transportation systems with mixed flow. Section 4 reports some conclusions.

During the last years, electronic systems assumed a growing importance in the development of assisted and automated systems. In particular, the research has been

• the development of new algorithms and the improvement of the already existing ones, at the end of obtaining more compact, less consuming and, above all, faster implementations, in order to fit the needs of the automotive industry;

• the development of "ad hoc" sensors capable of operating in the various environments and having performances suitable to detect, intervene and advice the driver in time, making it possible for the human or autonomous driver to take

This work starts from the sensors evolution to give an insight of the different techniques and sensors families used in nowadays autonomous vehicles, in order to gain insight on the different issues related to their development and provide ideas useful to better integrate them into the traffic models, obtaining more fitting

First of all, it is possible to define four types of sensors and related systems used

*DOI: http://dx.doi.org/10.5772/intechopen.94105*

The main goals of this paper are:

in the near future, as briefly outlined above,

• analyzing the main classifying criteria,

multi vehicle type transportation systems.

**2. Sensors analysis and vehicle classification**

the best decision due to the particular conditions.

focused around two main topics:

models and better results.

in nowadays smart vehicles:

• Image sensors and processors,

• Radar sensors and systems,

• Lidar sensors and systems,

• Ultrasonic sensors and systems.

population,


The main goals of this paper are:

*Models and Technologies for Smart, Sustainable and Safe Transportation Systems*

and joint ventures among them.

yet available, or the vehicles are still prototypes.

together with indications of needs of new models:

increase of vehicle (car) demand flows,

(need of new model split models)

generation and distribution models)

expected, requiring ad hoc tools for analysis and design [1].

pollution, noise, fuel consumption. This resulted in a major cooperation between companies coming from different backgrounds and in the creation of partnerships

New technologies for automated vehicles look very appealing, but, it may easily be anticipated that the time needed to turn the existing stock of traditional vehicles (TVs) into the new ones will last several years during which mixed traffic is

• increase of max density, since AVs may be shorter on the average,

• decrease of speed dispersion, useful for more effective traffic control,

• decrease of the number of vehicles on streets with shared vehicles, since the number of trips per vehicle increases, and a decrease of the number of vehicles parked along the sidewalk might be anticipated, leading to an increase of

• increase of vehicle x km due to empty movements, if shared vehicles spread, due to longer paths and of change of effective origin and destination,

• decrease of the number of users per car, if shared vehicles spread, leading to an

• change of modal split leading to an increase of car flows with respect to transit

• increase of generated flows, due to increase of mobility index and reference population, likely including mobility-impaired people (need of new trip

On the other hand, some positive social impacts may also be anticipated such as

• less pollution and noise (greater effect with electric powered vehicles),

• discrete space / time access for AVs vs. continuous access for TVs,

• increase of capacity, since safety distance may be shorter,

Moreover, the likely effects on congestion, and more generally traffic management and control, are not necessarily positive. Some of them are enlisted below,

These effects result in a renewed impulse in the research related to the vehicles, due to the growing mingling among the various sectors of the industry. The common goal is to develop new models or update the old ones to simulate real life situations and predict the future developments of the automotive and, in general, of transportation research field. Considering the field of transportation systems engineering, it is possible to state that right now the main focus is to achieve a deeper understanding of the hardware and software involvement in this new kind of vehicles. This, in turn, allows to obtain better models developments and more reliable scenario assessment. These issues are often accentuated by the impossibility of retrieving commercial standards, due to the fact that, in some cases, they are not

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• increase of safety,

capacity.


A vehicle classification based on available sensors is surely helpful to support specification and calibration of models for transportation systems analysis, thus a sensor critical analysis is carried out in Section 2, supporting the discussion of classification issues in the same Section 2. Section 3 discusses the main tools for the analysis of transportation systems with mixed flow. Section 4 reports some conclusions.
