Deliverables

Due July 2022.

Due November 2022.

Focussing on the consequences of large-scale CAV adoption, D3.1 combines results from Tasks 3.1, 3.2 and 3.3 and presents the outcomes of the first survey conducted in WP3, embedded in the context of existing literature. The aim is to provide user-centered recommendations based on survey results and literature on CAV adoption consequences.

Results of the survey replicate and extend previous findings, both by employing a stratified sample across multiple countries (Germany, France, Italy and UK) and providing results from the subpopulations (car-sharing users, professional drivers, people with visual impairments, and road cousers).

We investigated which anticipated consequences are the most importantly rated by participants, and which tend to be seen favorably or unfavorably by respondents. Our results provide instructive information on how to design CAV systems.

While positive consequences were expected in the context of road safety, stress reduction, enjoyment and life quality, negative consequences were expected in the areas of privacy and driving fun. Environmental issues could be somewhat ambiguous, mostly due to the necessary distinction between CAV usage as private cars vs in public transport context of busses. Participation in social life turned out to rank at a relatively high importance for respondents across the board, though expectations for improvement due to CAV adoption were neutral. While country differences were less pronounced, some differing expectations were uncovered in the subpopulations: An increase in cost was particularly worrisome for respondents with visual impairments, while the potential for social life and economic participation ranked particularly high in importance for them. Car-sharing users were sensitive to privacy consequences and the potential positive impact of CAVs on safety. Comfort improvements were more prominently featured in responses from professional drivers. Especially with regards to busses, respondents expected improvements for scenery and traffic congestion.

These aspects are discussed in the context of existing literature and policy recommendations.

The PAsCAL project, funded under the "Horizon 2020" Research and Innovation program, has the goal to provide insights and develop a better understanding about citizens’ and stakeholders’ expectations for connected and automated vehicles (CAVs), and the acceptance of CAVs.

The following document, D3.2, aims to introduce the user-centered research conducted in the context of WP3, which is the Work Package in charge of studying attitudes of citizens towards Connected and Autonomous Vehicles (CAVs) and assess which consequences are expected from CAV introduction into different traffic scenarios. The results of this research are presented in this 360° Acceptance Map. It delivers a multidimensional analysis indicating who accepts what types of CAVs, detailing also where and why.

The data introduced in the survey results sections below are based on data collection conducted using the Connected and Autonomous Vehicle Acceptance Assessment Tool (CAVA) developed in WP3 over the course of the PAsCAL project, which is also presented in-depth in D3.3, the companion deliverable to D3.2. The aim of the CAVA is to measure CAV acceptance via evaluation of expected CAV consequences. First results from descriptive insights of the data collected indicate that there are variations on almost all levels of analysis, though the overall acceptance tends towards ambivalent neutrality. In terms of motivators, safety and ease of use seem the most important factors, though gains in independence and expectations with regards to sustainability should not be overlooked.

Across socio-demographic strata, age, gender and education levels play roles, with older individuals, and women more sceptical of CAV adoption, and university level educated individuals more willing to adopt CAVs. Across countries, participants from Eastern and Southern countries such as Hungary, Spain, Portugal and Italy seem to be more optimistic and willing to adopt CAVs than participants from Central European countries such as France, Austria and Germany. Furthermore, experience with public transport, car sharing and ride hailing seems to go together with higher acceptance, though currently, for a variety of reasons, a slight preference for personal, owned vehicles can be observed among participants. Introduction as part of shared mobility is seen as beneficial in terms of affordability and sustainability. Finally, more optimistic expectations are reported by participants with visual impairments, and a higher willingness to use CAVs.

Recommendations that can be gained from this research will allow insights into potential impacts of interventions as well as help data collection related to CAVs.

Due November 2021.

Due August 2022.

Disclaimer: This deliverable has not yet been reviewed by the European Commission.

The aim of the PAsCAL project, funded under the "Horizon 2020" Research and Innovation program, is to improve the understanding of the implications of connected and automated vehicles (CAVs) on society. The project will create a "Guide2Autonomy" to capture this new knowledge. Outcomes from the project will contribute to the training of future drivers and passengers and will help decision-makers to move towards the new forms of individual and collective mobility made possible by the spread of driverless cars.

During the PAsCAL project, the perceptions and expectations of citizens regarding the new autonomous and connected driving technologies will be examined, trying to better understand their fears and concerns and to help to prepare solutions that will be able to bridge the anticipated emotional and cultural gaps. If these are not tackled, the barriers to adoption, inherent in the world of CAVs, may not be removed.

Likewise, the behaviour of drivers in semi-autonomous vehicles and that of all other road users will be studied, again to identify the main obstacles that will need to be removed in order to make man-machine interaction commonplace, whilst being as safe as possible.

To these purposes, specific surveys have been prepared in WP3 and accurate behavioural analyses are carried out in WP4 with extensive use of modern technologies, such as driving simulators and virtual reality platforms.

The results of the simulation experiments will provide a better understanding of the reasons for the distrust towards CAVs expressed by many European citizens. They will describe reactions and behaviours in situations that are still completely new and yet to be determined. They will allow useful conclusions to be drawn in terms of vehicle design, humanmachine interface layout, and the more holistic organization of the transport system.

All of this new knowledge will be incorporated into the "Guide2Autonomy" which will be made available to all relevant stakeholders. Specific anticipated items for inclusion will be how best to train CAV users (the current "drivers"), the necessary certifications that must be obtained and any new traffic rules to be adopted. It is hoped that all of this will assist with a smooth transition to wide-scale CAV adoption.

A specific focus, as part of the PAsCAL project, will be reserved for people who are currently unable to drive traditional vehicles; Blind or partially sighted citizens are a specific case considered by the project. For these road users, connected autonomous driving offers numerous advantages in terms of freedom of movement and increased personal autonomy.

In addition to the behavioural surveys and virtual journey experiences conducted using simulators, PAsCAL will finally create 5 road-transport pilot projects, conducted in different countries of the European Union. The pilot projects will focus respectively on: autonomous high-capacity buses; user training through driving schools and driving academies; different types of connected shared vehicles; autonomous bus lines and, last but not least, applications that allow people with disabilities to travel, thanks to new autonomous driving technologies within a transport network.

The current document presents the simulation scenarios and the corresponding experimental protocols that define the 5 experiments WP4 is made of. From their initial design to the details of their implementation.

The common background is presented in chapter 2, including the positioning of WP4 within the PAsCAL project, a recall of the WP4 objectives, the presentation of the simulators involved then how the research questions and the scenarios were imagined then chosen.

Much more details about the scenarios development and the experimental protocols (scientific definition, recruitment of the subjects, technical information about the simulation systems, measurement tools including questionnaires…) for each of the 5 experiments are exposed in chapter 3.

Additional information about deviations and references are provided in chapters 4 and 5.
 

PAsCAL is a user-centric research project aimed at accelerating the userfriendly evolution of connected, cooperative, and automated vehicles and transport systems, by addressing important issues relating to the role of humans in this evolution, in particular appropriate interactions of the autonomous vehicle with different road users including non-drivers. The difficulty to reproduce in reality safety-critical situations on the road, which involve highly automated vehicles, leads to the development of driving
simulators to be used as an interactive virtual reality tool for the human factors studies in the project.

This deliverable reports the findings of five simulation experiments ranging from professional driving simulation to home study kits, from drivers to pedestrians, and from road to air.

While these experiments have different settings, targeted users and levels of automation as described, they carry out several common tasks including:

1. Correlate and analyse driver behaviour/reaction under different scenarios;
2. Assess the acceptance of new interfaces integrated in the simulators, including information feedback and entertainment systems;
3. Put forward recommendations describing ways to improve the CAVs design, so they will be useful and acceptable to future real users, and the future drivers’ trainings;
4. Produce guidelines for WP6 pilot specifications (e.g., to design new use cases involving autonomous public transport and to define some variables which deserve to be tested in real conditions).

Disclaimer: This deliverable has not yet been reviewed by the European Commission.

The PAsCAL project funded under the "Horizon 2020" Research and Innovation program aims to improve the understanding of the implications of connected and automated vehicles (CAVs) on society. The project will create a "Guide2Autonomy" to capture this new knowledge. Outcomes from the project will contribute to the training of future drivers and passengers and will help decision-makers to move towards the new forms of individual and collective mobility made possible by the spread of driverless cars.

To fulfil these purposes, specific surveys have been prepared in WP3 and behavioural analyses are carried out in WP4 with using modern technologies, such as driving simulators and virtual reality platforms. WP5 will bring elements on how best to train CAV users (the current "drivers"), as well as the necessary certifications that must be obtained and any new traffic rules to be adopted.

In addition, PAsCAL will finally create, in WP6, five road-transport pilot projects, conducted in different countries of the European Union. One of these will specifically try to verify the results of WP5.
All the collected data will be then analysed in WP7 in terms of impacts and KPI.
All this new knowledge will be incorporated in WP8 into the "Guide2Autonomy", which will be available to all relevant stakeholders.

In all this context, the current document aims to present the requirements and competence and cognitive/affective models for CAV relevant training situations.

The whole document is broken down in 6 sections.

Following the Introduction section, section 2 presents the requirements of a CAV environment in which the takeover phase and driver behaviour are key. These requirements propose several ways and variables to investigate facilitators or barriers of a safe takeover, such as autonomy levels, driver factors and two types of road educational environment (an urban scenario and a highway scenario).

Then, section 3 details the competence and cognitive models of Home Study Simulator drivers dealing with several conditions.

To perform an efficient and timely takeover, the models enlisted in Section 3 detail the knowledge and skills related to the CAV, the Situation Awareness a driver has to demonstrate before, during and after a takeover, including the cognitive, affective and emotional resources regulation at every moment.

The document ends with a concluding section followed by related scientific references and a series of annexes.

Both cognitive and competence models will be inputs to develop the road education modules for drivers and trainers in a CAV environment that will be described in D5.2 and D5.3.