**1. Introduction**

It is commonly acknowledged that in the near future most of the road vehicles will travel, on almost the totality of the road network, in an automated way (autonomous driving). The reason for such a forecast is easily understood: the influence of the driver on safety, energy efficiency and traffic fluidity is very high [1]. In fact about 93% of road accidents are originated by some kind of driving error, as recognition errors, decision errors and performance errors [1]. Under such point of view, automated driving can bring dramatic improvements by eliminating the

© 2016 The Author(s). Licensee InTech. 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.

influence of human factors, thus contributing to reduce serious and fatal road accidents, fuel waste and traffic congestion. The total elimination of road accidents, however, is not predicta‐ ble at the moment, but their reduction to very little numbers is reasonably attainable. In the vision of many researchers, a roadmap to full automated vehicles can be defined; for instance, organisation like the Society of Automotive Engineers (SAE) has defined some steps (SAE Level of progressive automation, **Figure 1**), ranging from Level 0 (no automation) to Level 5 (full automation) [2].


**Figure 1.** SAE levels of progressive automation as defined in SAE International Standard J3016.

Levels 0–2 (partial automation) require that the human driver be responsible for monitoring the driving environment, whereas in Levels 3–5 such task is performed by the automated driving system. Unless having reached a condition of full automation (Level 5), the driver must be involved in car driving, that is to say that the driver must be kept "in the loop." In fact in any intermediate level of automation, several driving modes will include the possibility or the necessity that the control of the vehicle is shifted from the automated system to the driver, or that the driver is willing to keep the control back. As explained in Refs. [3, 4], such operation must be carefully designed. Such issue will be particularly important in the case of Level 3 (conditional automation) in which the driver, due to the increasing number of automated driving modes, will be often called to take the control back. The driving task can be decomposed into three main activities: recognition, judgement and operation. In all of such activities errors are possible, likely to bring to some risks or even to accidents. Within SAE Level 0 (no automation), all of these tasks are performed by the driver, which can be defined as "conventional driving." If the implementation of Advanced Driver Assistance Systems (ADAS) is carried out, the driver can be assisted, or even substituted, by some automated or autonomous device or function, up to a level of full automation (SAE Level 5) in which recognition, judgement and operation are performed by the system taking full control. In intermediate levels of assistance (as, for instance, in SAE Levels 1 and 2) only recognition and/ or judgement are assisted so that the responsibility for operation remains with the driver. Far from being infallible (at least at the present state of the art) such devices can be of great help to decrease the probability of errors and, consequently, of accidents.

#### **1.1. Present advanced driver assistance systems**

influence of human factors, thus contributing to reduce serious and fatal road accidents, fuel waste and traffic congestion. The total elimination of road accidents, however, is not predicta‐ ble at the moment, but their reduction to very little numbers is reasonably attainable. In the vision of many researchers, a roadmap to full automated vehicles can be defined; for instance, organisation like the Society of Automotive Engineers (SAE) has defined some steps (SAE Level of progressive automation, **Figure 1**), ranging from Level 0 (no automation) to Level 5 (full

**Figure 1.** SAE levels of progressive automation as defined in SAE International Standard J3016.

Levels 0–2 (partial automation) require that the human driver be responsible for monitoring the driving environment, whereas in Levels 3–5 such task is performed by the automated driving system. Unless having reached a condition of full automation (Level 5), the driver must be involved in car driving, that is to say that the driver must be kept "in the loop." In fact in any intermediate level of automation, several driving modes will include the possibility or the necessity that the control of the vehicle is shifted from the automated system to the driver, or that the driver is willing to keep the control back. As explained in Refs. [3, 4], such operation must be carefully designed. Such issue will be particularly important in the case of Level 3 (conditional automation) in which the driver, due to the increasing number of automated driving modes, will be often called to take the control back. The driving task can be

automation) [2].

82 Autonomous Vehicle

As regards the present state of the art of driving assistance devices, their functions can be divided into three main categories:


Presently, two types of control can be considered:


Even if the control is took by the system, the driving responsibility remains to the driver: in the first case because the control is handed to the driver when conditions can become critical; in the second case, the driver is overridden only at pre-crash conditions (but only as regards braking) so that the accident consequences are mitigated.

In all of this assistance functions, it can be easily understood that a convenient interface (Human-Machine Interface (HMI)) between the generic device and the driver must be designed and implemented. HMI can be considered as the channel through which information are conveyed to a vehicle's occupant; HMI design is one of the main issues that must be properly allowed for [5], addressing, for instance, the definition of the correct stimulus (type: visual, acoustic, haptic, etc.; sequence; timing; priority; etc.). In addition, since it is to be expected a different communication efficiency as a function of age, experience, education, etc., the interface must be properly tailored and some adaptation is certainly needed. The necessity of standardisation is to be expected, as well as the definition of human models capable to help interpreting correctly the situation and act accordingly.

During the progression towards full automation (especially when high levels of automation, such as SAE Levels 2, 3 and 4, will be implemented), several issues should be addressed in order to obtain a fast and successful path to SAE Level 5; three main topics can be identified as follows:


The issues presented in the first two points are currently addressed by several standard practice and regulations (as, for instance, in [6, 7]).

Presently, most of the vehicles can be categorised as belonging to Level 0 of automation, but all the major car manufacturers (as well as tier one suppliers) offer, in their sales catalogues, devices that can be defined as Driver Assistance Systems (typical of SAE Level 1) and some of them show features that can be defined as partial automation.

In the Italian market, for instance, in the official sales catalogues of the end of 2015 as published by car magazines (basically Quattroruote, Italy), several automated assistance systems can be found, mainly belonging to the following categories:


It can be easily recognised that such functions will certainly be part of a hypothetic future full automated system: even if the methods used to obtain such functions are hardly imaginable, the functions itself are necessary and the interaction with the driver must be allowed for. As can be seen in **Table 1**, the above-mentioned devices are offered by a good number of manu‐ facturers on several models, both as standard equipment and as paid option; often they are included in a package together with other safety or comfort devices.


**Table 1.** Number of manufacturers and vehicle models offering ADAS devices in the Italian market in September 2015.

**Table 2** shows average price and standard deviation (SD) for the same devices as **Table 1**, for the models offering such devices as paid option; as can be seen, when a device is included in a package, its price can be much higher. Price is a matter that can influence user acceptance and delay the diffusion of such safety devices.


**Table 2.** Average price (€) and standard deviation of some ADAS devices in the Italian market in September 2015.

#### **1.2. User acceptance**

properly allowed for [5], addressing, for instance, the definition of the correct stimulus (type: visual, acoustic, haptic, etc.; sequence; timing; priority; etc.). In addition, since it is to be expected a different communication efficiency as a function of age, experience, education, etc., the interface must be properly tailored and some adaptation is certainly needed. The necessity of standardisation is to be expected, as well as the definition of human models capable to help

During the progression towards full automation (especially when high levels of automation, such as SAE Levels 2, 3 and 4, will be implemented), several issues should be addressed in order to obtain a fast and successful path to SAE Level 5; three main topics can be identified

**–** Definition of suitable strategies for shifting control from the driver to the system and vice versa. Design of proper HMI systems will be of fundamental importance, also aiming at

**–** Definition of procedures aimed at obtaining the functional assessment of the instrumental

**–** Obtaining a wide user acceptance rate in order to accelerate the penetration in the market

The issues presented in the first two points are currently addressed by several standard

Presently, most of the vehicles can be categorised as belonging to Level 0 of automation, but all the major car manufacturers (as well as tier one suppliers) offer, in their sales catalogues, devices that can be defined as Driver Assistance Systems (typical of SAE Level 1) and some of

In the Italian market, for instance, in the official sales catalogues of the end of 2015 as published by car magazines (basically Quattroruote, Italy), several automated assistance systems can be

It can be easily recognised that such functions will certainly be part of a hypothetic future full automated system: even if the methods used to obtain such functions are hardly imaginable, the functions itself are necessary and the interaction with the driver must be allowed for. As can be seen in **Table 1**, the above-mentioned devices are offered by a good number of manu‐ facturers on several models, both as standard equipment and as paid option; often they are

interpreting correctly the situation and act accordingly.

carrying out such operation in a seamless manner.

practice and regulations (as, for instance, in [6, 7]).

found, mainly belonging to the following categories:

them show features that can be defined as partial automation.

**–** Autonomous emergency braking/forward collision warning (AEB/FCW).

included in a package together with other safety or comfort devices.

part of the automated system.

**–** Adaptive cruise control (ACC),

**–** Road sign recognition (RSR),

**–** Blind spot monitoring systems (BSM),

**–** Lane departure warning systems (LDWS),

of automated systems.

as follows:

84 Autonomous Vehicle

Though many researchers are very optimistic on the large implementation of full automation in the near future [8], many factors can slow down the process. A survey conducted by IEEE among its members [8] revealed that in the vision of many experts in the field, six main obstacles to the rapid diffusion of autonomous vehicles can be identified, i.e., technology, cost, infrastructure, policy, liability and user acceptance. According to this source, the first three points should represent a minor problem; technology is rapidly improving as regards both efficiency and reliability, whereas cost is a problem that must be shared among private and public stakeholders, also taking into consideration the potential benefit of accidents reduction, as well as medical and social costs. The implementation of proper infrastructures is of the greatest importance (it is difficult to imagine an effective implementation of driving automa‐ tion without, e. g., V2V and V2I communications) so that in relatively short terms it can be predicted that the largest diffusion of such systems will take place first in advanced geograph‐ ical areas, such as North America, Europe and parts of Asia. The last three points, instead, will play a decisive role; policymakers can boost or slow down the process since many matters require political decisions and a proper legislation will most probably be necessary, for instance as regards the realisation of the needed infrastructures and the settlement of issues related to legal liability. This last point can be particularly important: who will be responsible when an accident happens, as certainly will? It can be imagined that the involvement of car manufacturers and their suppliers will be greater, in a context that will also involve insurance companies, governments and customers [9–11]. User acceptance will play a fundamental role; in reference [12], for instance, a worldwide survey was carried out in order to understand how autonomous vehicles will be accepted, comparing all levels of automation (from conventional driving to full automation). In this study, the major concerns of future customers were indicated, including legal issues, cost (22% declared themselves unwilling to pay any addi‐ tional sum for an automated vehicle), security (regarding especially software being subject to hacking), privacy concerns (vehicles are subject to be constantly monitored) and driving pleasantness, etc. Geographical differences were also pointed out. In reference [13], the intention of French drivers to use a partially or fully automated vehicle was investigated. In reference [14], the possible effect of motion sickness on user acceptance is investigated, and the necessity of considering such issue during the design and development phase is emphas‐ ised. Thus, if a fast and successful introduction in the global market is desired, such systems must be implemented in such a way as aiming at high performance and high user acceptance, and such steps require the most complete understanding of driving behaviour: in other words, a driver model (or better, driver models) must be set up.

#### **1.3. The role of simulation**

In the initial phase of the development of ADAS, it is a common practice to carry out testing in controlled environment, namely, by staged driving sessions or using driving simulators. Since their introduction, driving simulators have been widely used to study safety and human factor-related issues. Since the first appearance of advanced driving simulators they were extensively used to investigate over safety issues [15, 16] and also as an important tool in the design and assessment of advanced driving assistance systems [17, 18].

The use of simulators presents numerous advantages:


On the other hand, the driving scenario must be carefully designed in order to obtain a sufficient representativeness of the results, and often a validation activity must be carried out, for instance by carrying out staged tests in controlled environments or by monitoring real-life driving. Moreover, not all the drivers are able to drive comfortably in a driving simulator. Although some of the testing activities regarding ADAS development can be carried out using static simulators, the use of an advanced immersive driving simulator allows to have all the needed functionalities together with a sufficiently realistic testing condition.

In the present chapter, a simulator experimental study is presented, aimed at understanding drivers' behaviour when a sudden hazardous situation with pedestrians is presented; for such aim, 69 young drivers were submitted to different virtual driving scenarios. The experimen‐ tation, far to be definitive, will anyway provide useful information for setting up a driver model as well as for determining HMI requirements.
