Much R&D is focused on an increasing variety of advanced driver assistance systems (ADAS) to be introduced in road traffic. These systems involve the assistance and/or automation of various basic driving tasks such as vehicle following, lane keeping, lane changing, proper speed keeping, all based on modern technology for sensing, data processing, data transmission, operational decision making and task actuation. The full and integrated application of these systems implies full automation of vehicle driving, called automated vehicle guidance (AVG). Research in the past, indicates that most driver assistance systems are very difficult to apply. This is mainly due to complex design issues related to the development of these systems. The complexity of design is caused by the rich variety of infrastructure and traffic situations. Driver assistance systems should be easy to handle in a reliable and accurate way, tuned to the variety in driver behaviour that is generated by the variety in traffic situations. The design of such systems requires a system approach that is opposite to the technology driver approach. Research indicates a lack of sufficient conceptual and empirical knowledge of this behaviour. Improvement of this knowledge is necessary to better develop efficient and effective driver assistance systems. Moreover, better knowledge helps to improve the evaluation of the performance of these systems, the necessary certification and the arrangement of liability for system development, system application and system failure. The BAMADAS programme, therefore aims at: 1. Improving the theoretical, empirical and design knowledge regarding road vehicle driver behaviour in interaction with advanced driver assistance systems; 2. The transfer of this knowledge to deployment strategies for driver assistance systems focusing on infrastructure design and traffic management; 3. The improvement of the knowledge regarding system certification and liability regulation in a multi-actor environment. (Author/publisher)
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