Trajectory Planning and Tracking for Four-Wheel Independent Drive Intelligent Vehicle Based on Model Predictive Control

Author:

Wu Haidong1,Long Xiang1,Lu Dang1

Affiliation:

1. Jilin University

Abstract

<div class="section abstract"><div class="htmlview paragraph">This paper proposes a dynamic obstacle avoidance system to help autonomous vehicles drive on high-speed structured roads. The system is mainly composed of trajectory planning and tracking controllers. The potential field (PF) model is introduced to establish a three-dimensional potential field for structured roads and obstacle vehicles. The trajectory planning problem that considers the vehicle’s and tires’ dynamics constraints is transformed into an optimization problem with muti-constraints by combining the model predictive control (MPC) algorithms. The trajectory tracking controller used in this paper is based on the 7 degrees of freedom (DOF) vehicle model and the UniTire tire model, which was discussed in detail in previous work [<span class="xref">25</span>, <span class="xref">26</span>]. The controller maintains good trajectory tracking performance even under extreme driving conditions, such as roads with poor adhesion conditions, where the car’s tires enter the nonlinear region easily. The innovation of this paper lies in introducing a high-fidelity vehicle model and a muti-conditions UniTire tire model with high precision obtained after parameter identification through tire test data. In addition, the nonlinear relationship between tire lateral force and slip angle is expressed as a linear function. This method updates the equivalent cornering stiffness in the linear function by solving the slope of the secant of the tire cornering characteristic curve at the current moment online, which solves the problem of high computational complexity caused by applying complex tire models in the control system. The co-simulation results of Simulink and CarSim show that the designed system has good dynamic obstacle avoidance and driving stability performance under driving conditions with high speed and poor road adhesion.</div></div>

Publisher

SAE International

Subject

Artificial Intelligence,Mechanical Engineering,Fuel Technology,Automotive Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3