SWOV Catalogus


Mediating between human driver and automation : state-of-the-art and knowledge gaps. Deliverable 1.1 of the H2020 project MEDIATOR (MEdiating between Driver and Intelligent Automated Transport systems on Our Roads).
20210374 ST [electronic version only]
Christoph, M. Cleij, D. Jansen, R. Kint, S. van der Mons, C. Nes, C.N. van Schagen, I.N.L.G. van Varotto, S.F. Zwart, R. de Santhià, T. Chandan, T. Karlsson, J. Muthumani, A. Borowsky, A. Kahana-Levy, N. Oron-Gilad, T. Beggiato, M. Rauh, N. Bakker, B. Egmond, R. van Farah, H. Grondelle, E. van Ridder, H. de Spaan, M.T.J. Florentino, A. Skeie, S.A. Dijk, H. van Miltenburg, M. van Oever, D. van den Ahlström, C. & Hecker, F.
[Brussels, European Commission], 2019, VII + 146 p., ref. ; Grant agreement No 814735

Samenvatting MEDIATOR (MEdiating between Driver and Intelligent Automated Transport systems on Our Roads) is a 4-year project led by SWOV. It started in May 2019. MEDIATOR will develop a mediating system for drivers in semi-automated and highly automated vehicles, resulting in safe, real-time switching between the human driver and automated system based on who is most fit to drive. MEDIATOR pursues a paradigm shift away from a view that prioritises either the driver or the automation, instead integrating the best of both. The current report is the first Deliverable of the project. It aims to define what we need to know to assess the fitness of the human driver and the automation, what we already know based on the available literature, and what are the research gaps that need to be bridged in order to develop the Mediator system. Information and approaches of existing Mediator-like systems in road and in other transport domains were also considered. In a more or less iterative process the review of needed and available knowledge helped to further elaborate a set of feasible functional requirements for three use cases. The results form the basis for the concrete design and work plan for the technical development of the various components of the Mediator system and their interaction. The results also form the basis for the definition of a series of targeted experiments to fill the most prominent research gaps in the area of human fitness, automation fitness, and HMI, in order to make the best possible decision for a transfer of control, and define the best means of communication to the driver. In separate chapters, this deliverable discusses the assessment of human fitness, the assessment of the fitness of the automation, the HMI requirements, the decision making logic, and the functional requirements in relation to the identified use cases. (Author/publisher)
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