Prof Wen-Hua Chen
Loughborough University, UK
Fellow of IEEE
EPSRC Established Career Fellow
Chair in Autonomous Vehicles
A short introduction to Prof Wen-Hua Chen:
Dr Wen-Hua Chen holds Professor in Autonomous Vehicles in the Department of Aeronautical and Automotive Engineering at Loughborough University, UK. Prof. Chen has a considerable experience in control, signal processing and artificial intelligence and their applications in aerospace and automotive systems. In the last 15 years, he has been working on the development and application of unmanned aircraft system and intelligent vehicle technologies, spanning autopilots, situational awareness, decision making, verification. He is a Chartered Engineer, and a Fellow of IEEE, the Institution of Mechanical Engineers, and the Institution of Engineering and Technology, UK. Recently Prof Chen was awarded an EPSRC (Engineering and Physical Science Research Council) Established Career Fellowship to develop advanced analysis and design tools to enable high levels of automation such as intelligent vehicles.
Speech Title: Goal-Oriented Control Systems (GOCS): a new framework for intelligent vehicle control?
There is a huge aspiration about intelligent vehicle technologies including ADAS and driverless cars. Despite of all the significant progress so far, there are still many fundamental challenges that must be addressed before the potential of intelligent vehicles could be fully realized. Among others, verification of the safety of technologies, the interaction of many sophistic functions involved in intelligent vehicles, and the complexity of driving environments and human factors are on the top list. This talk argues, to address these challenges, it is more important to take a system level approach, rather than only at the algorithm level. A Goal-Oriented Control System (GOCS) is proposed to facilitate the analysis and design of intelligent vehicles at a system level where feedback plays a central role. Examples are given to illustrate how it helps to understand the interaction between different core functions (e.g. the interaction between optimization algorithms (e.g. for path planning and machine learning) and physical dynamics). Another feature of this framework is to promote goal-oriented approaches, moving away from scenario-based description approaches. It is the control system to decide, given all the available information for a specific scenario, what is the best course of action to achieve the driving goal while respecting to all the constraints such as safety, and the rules of the road. The talk concludes with discussion on future research in this area.
ICoIV Past Speakers
University of Michigan