Optimal Trajectory Planning and Control for Automatic Lane Change of in Wheel Motor Driving Vehicles on Snow and Ice Roa
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ptimal Trajectory Planning and Control for Automatic Lane Change of in Wheel Motor Driving Vehicles on Snow and Ice Roads Zhongyang Wanga, Di Tana, *, Guangcheng Gea, and Shuaishuai Liua aSchool
of Transportation and Vehicle Engineering Shandong University of Technology, Zibo, 255049 China *e-mail: [email protected] Received December 23, 2019; revised March 12, 2020; accepted March 17, 2020
Abstract—In the process of vehicles changing lanes, ice and snow pavement is a very common special working condition, and the research on automatic lane change is usually based on medium and high adhesion coefficient roads. Aiming at the special situation of low adhesion coefficient of ice and snow pavement, this paper studies the process of automatic lane change of vehicles on low adhesion roads driven by the front drive automobile driven by in-wheel motor. First, a dynamic model of a front drive automobile driven by in-wheel motor is established. Then, the trajectory planning is performed based on the fifth-degree polynomial method; the lateral acceleration threshold to ensure the safety of the lane change is deduced; the optimization function of the lane change time and the longitudinal driving displacement is established; and the optimal trajectory to ensure the safety and the lane change efficiency is obtained. Finally, the controller is established based on the fuzzy adaptive PID control algorithm, and the driving torque of the hub motor is distributed through the torque distribution strategy to perform the trajectory tracking control of the vehicle. Simulation results show that the vehicle can safely and smoothly change lanes along the planned trajectory. Keywords: Ice and snow road, in wheel motor vehicle, automatic lane change, trajectory planning, safety, tracking control DOI: 10.3103/S0146411620050090
1. INTRODUCTION Changing lanes is a common traffic behavior and the main cause of traffic accidents, especially in lowadhesion roads such as ice and snow, and thus the safety of changing lanes is even more important. Smart vehicles can effectively avoid traffic accidents caused by human error during lane change, reduce the severity of traffic accidents, and even prevent accidents in time before potential traffic accidents occur. Therefore, intelligent vehicle automatic lane change has attracted much attention in recent years. The intelligent vehicle’s lane change trajectory planning and tracking control during the lane change process are the key technologies to ensure the safe and effective vehicle lane change. At present, for trajectory planning methods of automatic lane change, there are methods based on parameterization, dynamic planning, and optimization algorithms [1]. Parameter-based trajectory planning methods include B-spline curves, β-spline curves, polynomial equation curves, and differential flat systems. The B-spline curve connects the curves through multiple control points to satisfy the continuous condition of the curve for trajectory planning [2, 3]. The β-spline curve is the development and promotion of
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