详情

Data-Driven Motion Control of Autonomous Vehicles in GPS-Unreliable Environments

项目名称：	Data-Driven Motion Control of Autonomous Vehicles in GPS-Unreliable Environments
摘要：	In this project, a novel data-driven strategy will be proposed for autonomous vehicle (AV) motion control when a global positioning system (GPS) signal is not reliable. In recent years, data-driven approaches such as reinforcement learning (RL) and adaptive dynamic programming (ADP) algorithms have been widely adopted in solving dynamic programming problems. However, there is seldom any related application in AV control systems when a GPS signal is not reliable, where technical difficulties occur due to the unavailability of the vehicle location, orientation and certain critical vehicle states. An AV’s complex operation environment, external disturbances, system nonlinearities, modeling and non-structural uncertainties also lead to challenges for reliable motion control. To this end, this project will develop an enhanced ADP approach for AV motion control when the GPS signal is not reliable, based on the estimation results for the sideslip angle and tire-road friction coefficient. The dependable inputs will be signals collected/measured from on-board sensing results. The innovations of this research are: (1) an adaptive and cost-efficient estimation scheme will be proposed to estimate the tire road friction coefficient and sideslip angle simultaneously based on on-board sensors; (2) a novel learning-based adaptive motion control strategy will be proposed based on the sensing results and obtained estimation results to solve the tracking control with guaranteed prescribed performance.
状态：	Active
资金：	100000
资助组织：	Pacific Northwest Transportation Consortium<==>Office of the Assistant Secretary for Research and Technology
项目负责人：	Hu, Chuan
执行机构：	Alaska University Transportation Center
开始时间：	20210616
预计完成日期：	20220615
主题领域：	Data and Information Technology；Highways；Safety and Human Factors；Vehicles and Equipment