CogShift and Game-Theoretic Method for Driver-Automation Collaboration
Although few will doubt that the future of vehicles will be fully autonomous, it is arguable that a few middle steps (such as SAE Level 3 and 4) will be inevitable through this process, in which human drivers are in the control loop. Howe to tackle the driver-automation collaboration problem in a safe and user-friendly manner is therefore very crucial. This presentation shares a probable first step of a solution to this question with the application of game-theoretic modelling method. Results from the research on driver behaviours interacting with a collision avoidance system will be presented as a case.
Huaji Wang is a Research Fellow in Automated Driving at Cranfield University, UK. He is in charge of managing a collaborative research project between Cranfield and UCL for developing driver-cognition-based optimal control authority shifting methods for adaptive automated driving (CogShift). This project is jointly funded by Jaguar Land Rover and EPSRC UK. He used to research in vehicle dynamics and control at Jilin University, China. His current research interest is to apply game theory in designing safer and more user-friendly driver-automation collaboration systems. This is inspired by his PhD project at University of Cambridge about game-theoretic modelling of driver-automation interactions.