多车辆分布式模型预测交叉口控制

M. Kloock, Patrick Scheffe, S. Marquardt, Janis Maczijewski, Bassam Alrifaee, S. Kowalewski
{"title":"多车辆分布式模型预测交叉口控制","authors":"M. Kloock, Patrick Scheffe, S. Marquardt, Janis Maczijewski, Bassam Alrifaee, S. Kowalewski","doi":"10.1109/ITSC.2019.8917117","DOIUrl":null,"url":null,"abstract":"This paper investigates intersection control of multiple vehicles using a Model Predictive Control (MPC) framework. Vehicles follow pre-defined paths across the intersection and adjust their velocities to ensure collision-free passage while maximizing an objective. We choose a non-cooperative Distributed Model Predictive Control (DMPC) approach, where priorities need to be assigned to vehicles. The algorithm we present sets these priorities automatically by evaluating the vehicles’ time to react to stop before entering the intersection. We demonstrate our method in simulations of multiple vehicles and continuous traffic. It produces near-optimal velocity profiles and reduces the computation time in comparison to centralized MPC while avoiding vehicle collisions and deadlocks.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"7 1","pages":"1735-1740"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Distributed Model Predictive Intersection Control of Multiple Vehicles\",\"authors\":\"M. Kloock, Patrick Scheffe, S. Marquardt, Janis Maczijewski, Bassam Alrifaee, S. Kowalewski\",\"doi\":\"10.1109/ITSC.2019.8917117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates intersection control of multiple vehicles using a Model Predictive Control (MPC) framework. Vehicles follow pre-defined paths across the intersection and adjust their velocities to ensure collision-free passage while maximizing an objective. We choose a non-cooperative Distributed Model Predictive Control (DMPC) approach, where priorities need to be assigned to vehicles. The algorithm we present sets these priorities automatically by evaluating the vehicles’ time to react to stop before entering the intersection. We demonstrate our method in simulations of multiple vehicles and continuous traffic. It produces near-optimal velocity profiles and reduces the computation time in comparison to centralized MPC while avoiding vehicle collisions and deadlocks.\",\"PeriodicalId\":6717,\"journal\":{\"name\":\"2019 IEEE Intelligent Transportation Systems Conference (ITSC)\",\"volume\":\"7 1\",\"pages\":\"1735-1740\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Intelligent Transportation Systems Conference (ITSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2019.8917117\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2019.8917117","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25

摘要

本文利用模型预测控制(MPC)框架研究了多车辆的交叉口控制问题。车辆沿着预先定义的路径穿过十字路口,并调整速度以确保无碰撞通过,同时最大化目标。我们选择了一种非合作的分布式模型预测控制(DMPC)方法,其中需要为车辆分配优先级。我们提出的算法通过评估车辆在进入十字路口之前做出反应的时间来自动设置这些优先级。我们在多车连续交通的仿真中验证了我们的方法。与集中式MPC相比,它产生了接近最佳的速度曲线,减少了计算时间,同时避免了车辆碰撞和死锁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Model Predictive Intersection Control of Multiple Vehicles
This paper investigates intersection control of multiple vehicles using a Model Predictive Control (MPC) framework. Vehicles follow pre-defined paths across the intersection and adjust their velocities to ensure collision-free passage while maximizing an objective. We choose a non-cooperative Distributed Model Predictive Control (DMPC) approach, where priorities need to be assigned to vehicles. The algorithm we present sets these priorities automatically by evaluating the vehicles’ time to react to stop before entering the intersection. We demonstrate our method in simulations of multiple vehicles and continuous traffic. It produces near-optimal velocity profiles and reduces the computation time in comparison to centralized MPC while avoiding vehicle collisions and deadlocks.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信