Project description
Optimising the safety potential of vehicle automation
The transition to full automation comes with its risks, particularly when switching between a human driver and an automated system, with the possibility of the latter not always functioning. Because of this, automated transport systems must be able to intelligently assess the strengths and weaknesses of the driver and system, choosing the best controller. The EU-funded MEDIATOR project will develop a mediating system for road transport to provide a safe, real-time switching between the driver and system based on the fittest to drive. To do this, it will use state-of-the-art knowledge and develop and adapt available technologies for real-time data collection, storage and analysis, incorporating the latest artificial intelligence techniques.
Objective
Problem: Automated transport technology is developing rapidly for all transport modes, with huge safety potential. However, the transition to full automation brings new risks, such as misuse, overreliance, reduced situational awareness and mode confusion. The driving task changes to a more supervisory role, reducing the task load and potentially leading to degraded performance. Similarly, the automated system may not (yet) function in all situations; it must intelligently assess the strengths and weaknesses of both driver and system and select the best control mode according to the context.
Solution: MEDIATOR proposes an intelligent ‘mediating’ support system for road transport, enabling safe, real-time switching between human driver and system. It will constantly evaluate driving context, driver state and vehicle automation status, personalising its technology to the driver’s general competence.
Approach: MEDIATOR pursues a paradigm shift away from a view that prioritises either the driver or the automation, instead integrating the best of both. It will use state-of-the-art knowledge, including that from other transport modes, and develop new knowledge about human behaviour and human-machine interaction. It will apply the latest artificial intelligence technology to evaluate driver state, automation status and driving context in real time. It will produce several prototypes in the lab and in actual vehicles, for evaluation in simulation, simulator and on-road studies—as well as several tools for further exploitation.
Impact: MEDIATOR will optimise the safety potential of vehicle automation, especially during the transition to full automation. It will reduce future as well as current risks (such as inattention or fatigue). MEDIATOR will facilitate market exploitation by actively involving the automotive industry during the development process. Further, the involvement of experts from other transport modes will maximise the transfer of knowledge to these domains.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- social sciencessociologyindustrial relationsautomation
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineering
- social sciencessocial geographytransport
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
2492 JP 'S-GRAVENHAGE
Netherlands
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.