Driver behaviour and acceptance of connected, cooperative and automated transport

Today's vehicles - in all modes of transport - are becoming increasingly connected and cooperative, as well as automated. This raises a number of issues about the role of the "driver" (or operator, rider, pilot, captain) in such vehicles (cars, trucks, powered-two-wheelers, trains, ships, planes, etc.). In particular, human-machine interaction is becoming increasingly complex in an environment with higher levels of both qualitative and quantitative information, automated data exchange (into and out of the vehicle) and increasing levels of automation (systems, operations, etc.).

However, developments in recent years have primarily focused on "hard" technological advances and the maturity of technology-driven transport/mobility concepts, outpacing and insufficiently addressing the "soft" human component in this evolution. Therefore the challenge relates to a number of inter-related themes, ranging from public acceptance of connectivity and automation (e.g. data privacy, role of the human), to the development of user-friendly and appropriate Human-Machine Interfaces (HMI), "driver"/vehicle interaction and ethical decision making, to "driver" training and certification for new technologies/levels of automation.

A clear challenge for the roll-out of connectivity and automation in transport remains the lack of a detailed, evidence-based assessment of real "driver" behaviour in connected and highly automated or autonomous vehicles (and possible mitigation solutions), accounting also for gender, age and ability, with and without the assistance of cross-modal Cooperative Intelligent Transport Systems (C-ITS), under various use cases (incl. technical failure) and in a range of operating environments (e.g. urban, rural, etc).

Scope

In order to meet this challenge, proposals should address at least 5 of the following aspects:

• Assess public acceptance across Europe for higher levels of connectivity and automation, relating to a number of public concerns, including data privacy, safety and security, consequences of the availability of 24/7 mobility, vehicle control, liability, ethics, new features such as driver alerts (various types of alarm), as well as the proliferation of new technology and related behaviours, particularly in view of different types of users ("drivers" / passengers, etc) – all elements enabling sensible use of connectivity and automation.
• Public acceptance of different user groups, including current non-drivers (i.e. the elderly, people with disabilities, children, etc.), which in higher levels of automation could travel alone in an automated vehicle.
• Perform simulations, correlate and analyse driver behaviour/reaction under different scenarios/use cases, including driver distraction/assistance, driver-vehicle interaction technology failures and/or conditions instigating accidents (either by the vehicle itself or by other/external factors), as well as in different operating environments (e.g. urban, rural, multimodal hub) with other users, utilising big data analytics, assessing impacts of traffic flows, schedule reliability and congestions and also developing appropriate mitigation solutions to enhance "driver" behaviour under such scenarios (including using visual and acoustic information).
• Demonstrate the relevance, differentiation and the required evolution/adaptation of "driver" behaviour in connected and automated vehicles for passenger and/or freight transport (considering in particular the value of life vs. the value of cargo and also time and comfort).
• Estimate the effects of "driver"-vehicle interaction on transport safety and whether these would be marginal compared to full automation (with no "driver" interaction), hence implying a need to accelerate efforts towards fully connected automation. The necessary timing and issues on the transition from conventional to automated vehicles should be examined (e.g. interaction between "drivers" of conventional and automated vehicles).
• Analyse the levels of Human-Machine Interfaces (HMI) across different types of vehicles, as well as the margins for further optimisation in order to enable information generation and dynamic processing in multiple real-time or changing conditions.
• Assess and elaborate common issues, approaches and lessons learned across all transport modes (e.g. HMI, "driver" behaviour, ethical decision making, etc.).
• Address explicitly the ethical and legal issues associated with "driver" and/or vehicle decision making processes under different circumstances, as well as explore solutions to overcome the ethical and legal challenges relating to connectivity and automation.
• Investigate new "driver" training needs and certification requirements for new technologies/levels of automation, including effects on employment and skills.
• Assess the regulatory state of art, with particular reference to any regulatory gap hindering the adoption of automated vehicles (cars, trains, ships, planes).
• Assess attitudes towards shared modes of transport and the inclusion of connected, cooperative and automated vehicles as part of fleets.

Research should be validated in a selected number of use cases through testing/trials/demonstrations, involving service providers and end users.

The Commission considers that proposals requesting a contribution from the EU of EUR 3 to 4 million each would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Expected Impact

Actions are expected to:

• Support the integration of higher levels of connectivity and automation in transport;
• Contribute to improved levels of safety and security in all modes of transport, in line with the Transport White Paper 2011 (e.g. Vision Zero);
• Contribute to the possible reduction of cost for industry and public authorities through an improved understanding of requirements and needs of different types of "drivers"/users in the context of connectivity and automation in all modes of transport;
• Contribute to a better user acceptance of innovative, cooperative, connected and highly automated transport systems;
• Enhance driver awareness and behaviour in a range of complex / urban operating environments.

Cross-cutting Priorities

• Socio-economic science and humanities
• Open Innovation