Trajectory tracking control of autonomous vehicles based on event-triggered model predictive control

IF 2.3 4区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IET Intelligent Transport Systems Pub Date : 2024-11-20 DOI:10.1049/itr2.12589

Jindou Zhang, Zhiwen Wang, Long Li, Kangkang Yang, Yanrong Lu

{"title":"Trajectory tracking control of autonomous vehicles based on event-triggered model predictive control","authors":"Jindou Zhang, Zhiwen Wang, Long Li, Kangkang Yang, Yanrong Lu","doi":"10.1049/itr2.12589","DOIUrl":null,"url":null,"abstract":"<p>This paper presents a lateral control scheme based on event-triggered model predictive control for trajectory tracking of autonomous vehicles. Firstly, the augmentation system is constructed based on the known road curvature information, and the model predictive controller is utilized to obtain the optimal control sequence. Then, an event-triggered mechanism is introduced to improve the real-time performance of the control system. The strategy targets to reduce the computational complexity and solving frequency of the optimization problem. In addition, a contraction constraint is structured using the backstepping control strategy to ensure the stability of the control system. Finally, experiments are conducted through the CarSim/Simulink joint simulation platform, and compared with the traditional model predictive control, the method proposed in this paper has better tracking accuracy and improves the real-time performance of the control system.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 S1","pages":"2856-2868"},"PeriodicalIF":2.3000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12589","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Intelligent Transport Systems","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12589","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

Abstract

This paper presents a lateral control scheme based on event-triggered model predictive control for trajectory tracking of autonomous vehicles. Firstly, the augmentation system is constructed based on the known road curvature information, and the model predictive controller is utilized to obtain the optimal control sequence. Then, an event-triggered mechanism is introduced to improve the real-time performance of the control system. The strategy targets to reduce the computational complexity and solving frequency of the optimization problem. In addition, a contraction constraint is structured using the backstepping control strategy to ensure the stability of the control system. Finally, experiments are conducted through the CarSim/Simulink joint simulation platform, and compared with the traditional model predictive control, the method proposed in this paper has better tracking accuracy and improves the real-time performance of the control system.

Abstract Image

查看原文本刊更多论文

基于事件触发模型预测控制的自动驾驶汽车轨迹跟踪控制

提出了一种基于事件触发模型预测控制的自动驾驶汽车轨迹跟踪横向控制方案。首先，基于已知的道路曲率信息构建增强系统，利用模型预测控制器获得最优控制序列；然后，引入事件触发机制，提高控制系统的实时性。该策略旨在降低优化问题的计算复杂度和求解频率。此外，利用回溯控制策略构造了一个收缩约束，以保证控制系统的稳定性。最后，通过CarSim/Simulink联合仿真平台进行了实验，与传统的模型预测控制相比，本文提出的方法具有更好的跟踪精度，提高了控制系统的实时性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IET Intelligent Transport Systems 工程技术-运输科技

CiteScore

6.50

自引率

7.40%

发文量

159

审稿时长

3 months

期刊介绍： IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf