Tyre-Road Friction Coefficient Estimation using Maximum Entropy

点击翻译按钮获取中文摘要

Current trends toward automation include the automation of heavy goods vehicles. Heavy goods vehicles have long stopping distances which depend on the state of the road ahead of them. Computer vision can be used to determine the properties of the road ahead of the vehicle, allowing the possibility of determining where the vehicle should go in an emergency stopping manoeuvre. However, the estimate provided by computer vision of the properties of the road is an estimate, meaning that it has some uncertainty associated with it. Without taking this uncertainty into account, the actual stopping distance of the vehicle might be much longer than anticipated. The internal architecture for making vehicle motion planning decisions, integrating estimates of friction properties from the computer vision system, has not been clearly defined. In addition, a method is required for defining and understanding the uncertainty of the friction property estimates from the computer vision system and building this into the stopping distance estimation algorithm. This overseas travel grant seeks to fund a visit to Chalmers University of Technology in Gothenburg, Sweden. The grant will enable close collaboration between Dr Midgley and the vehicle dynamics group at Chalmers. It will also allow technical discussions with Volvo Trucks, who have an interest in the area of heavy vehicle automation. Dr Midgley will be able to work intensively on the architecture and distance estimation problems, while communicating freely with researchers from Chalmers and Volvo Trucks, and build links for future collaborative research projects.