| Summary: |
Objectives/Activities: The road transport system is very dynamic and complex involving human-technology interaction and cooperation, together with numerous social interactions in the traffic. In opposition to other transport modes (e.g. railway, maritime, aviation), in which highly trained and competent professionals drive or pilot different vehicles, the road transport system is totally open, accommodating an enormous variety of users evolving on the road environment. In-vehicle technologies represent a potential to increase safety and possibly save lives. However, there is still much to investigate and learn about human-automation interaction during the long run towards a fully connected and automated road transport system.
AUTODRIVING project aims (1) to study the driver's activity and behaviour during the autonomous driving, including (2) the research of the takeover of vehicle control task under different circumstances, which is expected to be the riskiest driving task in autonomous vehicles, and (3) the identification of his/her understanding of the system functioning. To achieve these goals, a national survey following focus groups interviews will be conducted. Additionally, driving simulator experiments will be undertaken to analyse driver behaviour under several specific scenarios of autonomous driving.
Results/Impact: Two main outputs are expected at the end of AUTODRIVING project: (i) the knowledge of the mental representation of autonomous driving, its concerns and expectations of different groups of population (age, gender, professional and non-professional drivers, etc); (ii) the description of driver behaviour under safety-critical events, using behaviour models. Consequently, these project outcomes will support on one hand, recommendations to guide policy actions at different society levels and on the other hand, will support the development of ADAS (e.g. the notification interval to the takeover), which are foreseen to be tailored to the  |
Summary
Objectives/Activities: The road transport system is very dynamic and complex involving human-technology interaction and cooperation, together with numerous social interactions in the traffic. In opposition to other transport modes (e.g. railway, maritime, aviation), in which highly trained and competent professionals drive or pilot different vehicles, the road transport system is totally open, accommodating an enormous variety of users evolving on the road environment. In-vehicle technologies represent a potential to increase safety and possibly save lives. However, there is still much to investigate and learn about human-automation interaction during the long run towards a fully connected and automated road transport system.
AUTODRIVING project aims (1) to study the driver's activity and behaviour during the autonomous driving, including (2) the research of the takeover of vehicle control task under different circumstances, which is expected to be the riskiest driving task in autonomous vehicles, and (3) the identification of his/her understanding of the system functioning. To achieve these goals, a national survey following focus groups interviews will be conducted. Additionally, driving simulator experiments will be undertaken to analyse driver behaviour under several specific scenarios of autonomous driving.
Results/Impact: Two main outputs are expected at the end of AUTODRIVING project: (i) the knowledge of the mental representation of autonomous driving, its concerns and expectations of different groups of population (age, gender, professional and non-professional drivers, etc); (ii) the description of driver behaviour under safety-critical events, using behaviour models. Consequently, these project outcomes will support on one hand, recommendations to guide policy actions at different society levels and on the other hand, will support the development of ADAS (e.g. the notification interval to the takeover), which are foreseen to be tailored to the driver characteristics, by automotive and software industry and R&D agents.
The AUTODRIVING team structure follows the strategy of a trans-disciplinary scientific approach and thus, covering scientific areas such as transport and safety engineering, ICT and ITS engineering, psychology and ergonomics sciences. |