Shared Control in Advanced Driver Assistance Systems Based on Risk Predictive Driving Intelligence Model
Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology
*The organization and the title are those when awarded
Research summary
Autonomous vehicle technologies are expected to exhibit safety performance to avoid traffic accidents and to improve driver comfort as driving effort reduces.
Recent driver assistance systems have reached their limits in specific situations.
Dr.Pongsathorn Raksincharoensak proposes a motion planning and control system to enable a driver to operate a vehicle more safely with optimal reactive forces through the steering and pedals. Based on reference data from hazard anticipation testing of experienced drivers, this technology aims to minimize traffic accident risk.
This technology is expected to be extended for the shared-control human-machine interface technology that is adaptable to individual characteristic of drivers and traffic situations.
Such an example of this technology can be applied to interface design for robots and appliances.
