采用改进型可变间距策略的协同自适应巡航控制系统

Chunguo Zhou, Zhicheng Zeng, Jin Mao, Tengfei Zheng, Chao Liu
{"title":"采用改进型可变间距策略的协同自适应巡航控制系统","authors":"Chunguo Zhou, Zhicheng Zeng, Jin Mao, Tengfei Zheng, Chao Liu","doi":"10.1177/09544070241271830","DOIUrl":null,"url":null,"abstract":"To further improve the safety, tracking, comfort, fuel economy, and platoon fluctuation of the cooperative adaptive cruise control (CACC) system, and alleviate traffic congestion, an improved model predictive control (MPC) algorithm considering multi-objective optimization is designed. An error compensation prediction constant time headway spacing strategy considering relative velocity, relative acceleration, and preceding vehicle distance error is proposed. The spacing strategy is introduced into the prediction model of MPC to optimize the prediction accuracy, improve the response-ability of the rear vehicle to the change of the lead state, and better coordinate the conflicting multiple objectives. The asymptotic stability of the CACC system under the improved MPC algorithm is proved by the Lyapunov stability theory, and the evaluation index is established to quantify the comprehensive performance of the CACC system. The numerical simulation is carried out under rapid acceleration and deceleration conditions, and the results show that the improved model predictive control algorithm can improve the safety, tracking, comfort, fuel economy, and road capacity of the CACC system. To simulate real traffic scenarios, co-simulation is carried out under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) condition, which further verifies the rationality and effectiveness of the algorithm.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"117 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative adaptive cruise control system with improved variable spacing strategy\",\"authors\":\"Chunguo Zhou, Zhicheng Zeng, Jin Mao, Tengfei Zheng, Chao Liu\",\"doi\":\"10.1177/09544070241271830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To further improve the safety, tracking, comfort, fuel economy, and platoon fluctuation of the cooperative adaptive cruise control (CACC) system, and alleviate traffic congestion, an improved model predictive control (MPC) algorithm considering multi-objective optimization is designed. An error compensation prediction constant time headway spacing strategy considering relative velocity, relative acceleration, and preceding vehicle distance error is proposed. The spacing strategy is introduced into the prediction model of MPC to optimize the prediction accuracy, improve the response-ability of the rear vehicle to the change of the lead state, and better coordinate the conflicting multiple objectives. The asymptotic stability of the CACC system under the improved MPC algorithm is proved by the Lyapunov stability theory, and the evaluation index is established to quantify the comprehensive performance of the CACC system. The numerical simulation is carried out under rapid acceleration and deceleration conditions, and the results show that the improved model predictive control algorithm can improve the safety, tracking, comfort, fuel economy, and road capacity of the CACC system. To simulate real traffic scenarios, co-simulation is carried out under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) condition, which further verifies the rationality and effectiveness of the algorithm.\",\"PeriodicalId\":54568,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering\",\"volume\":\"117 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1177/09544070241271830\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544070241271830","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0

摘要

为进一步提高协同自适应巡航控制系统(CACC)的安全性、跟踪性、舒适性、燃油经济性和排量波动性,缓解交通拥堵,设计了一种考虑多目标优化的改进型模型预测控制(MPC)算法。提出了一种考虑相对速度、相对加速度和前车距离误差的误差补偿预测恒定时间车头间距策略。该间隔策略被引入 MPC 预测模型,以优化预测精度,提高后车对前车状态变化的响应能力,并更好地协调相互冲突的多目标。利用李雅普诺夫稳定性理论证明了改进 MPC 算法下 CACC 系统的渐近稳定性,并建立了评价指标来量化 CACC 系统的综合性能。在急加速和急减速条件下进行了数值仿真,结果表明改进的模型预测控制算法可以提高 CACC 系统的安全性、跟踪性、舒适性、燃油经济性和道路通行能力。为模拟真实交通场景,在全球统一轻型车辆测试循环(WLTC)条件下进行了协同仿真,进一步验证了算法的合理性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Cooperative adaptive cruise control system with improved variable spacing strategy
To further improve the safety, tracking, comfort, fuel economy, and platoon fluctuation of the cooperative adaptive cruise control (CACC) system, and alleviate traffic congestion, an improved model predictive control (MPC) algorithm considering multi-objective optimization is designed. An error compensation prediction constant time headway spacing strategy considering relative velocity, relative acceleration, and preceding vehicle distance error is proposed. The spacing strategy is introduced into the prediction model of MPC to optimize the prediction accuracy, improve the response-ability of the rear vehicle to the change of the lead state, and better coordinate the conflicting multiple objectives. The asymptotic stability of the CACC system under the improved MPC algorithm is proved by the Lyapunov stability theory, and the evaluation index is established to quantify the comprehensive performance of the CACC system. The numerical simulation is carried out under rapid acceleration and deceleration conditions, and the results show that the improved model predictive control algorithm can improve the safety, tracking, comfort, fuel economy, and road capacity of the CACC system. To simulate real traffic scenarios, co-simulation is carried out under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) condition, which further verifies the rationality and effectiveness of the algorithm.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.40
自引率
17.60%
发文量
263
审稿时长
3.5 months
期刊介绍: The Journal of Automobile Engineering is an established, high quality multi-disciplinary journal which publishes the very best peer-reviewed science and engineering in the field.
期刊最新文献
Comparison of simplex and duplex drum brakes linings with transverse slots in vehicles Scenario-aware clustered federated learning for vehicle trajectory prediction with non-IID data Vehicle trajectory prediction method integrating spatiotemporal relationships with hybrid time-step scene interaction Research on Obstacle Avoidance Strategy of Automated Heavy Vehicle Platoon in High-Speed Scenarios Cooperative energy optimal control involving optimization of longitudinal motion, powertrain, and air conditioning systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1