{"title":"典型城市道路网络中控制非循环交通灯的方法","authors":"M. Ruchaj, R. Stanisławski","doi":"10.1109/MMAR.2011.6031378","DOIUrl":null,"url":null,"abstract":"This paper presents a comparison of five algorithms used to control acyclic traffic lights at intersections of roads in an urban road network. The following algorithms are selected: Most Cars characterized by low computational complexity, the author's algorithm called In-and-Outbound Lane Control, which is an efficient modification of the Most Cars, Local Hill-Climbing algorithm (LHC), the reinforcement learning RL 1 Bucket 2.0 algorithm and the neural network GenNeural algorithm.","PeriodicalId":440376,"journal":{"name":"2011 16th International Conference on Methods & Models in Automation & Robotics","volume":"298 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Approaches to control acyclic traffic lights in an exemplary urban road network\",\"authors\":\"M. Ruchaj, R. Stanisławski\",\"doi\":\"10.1109/MMAR.2011.6031378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a comparison of five algorithms used to control acyclic traffic lights at intersections of roads in an urban road network. The following algorithms are selected: Most Cars characterized by low computational complexity, the author's algorithm called In-and-Outbound Lane Control, which is an efficient modification of the Most Cars, Local Hill-Climbing algorithm (LHC), the reinforcement learning RL 1 Bucket 2.0 algorithm and the neural network GenNeural algorithm.\",\"PeriodicalId\":440376,\"journal\":{\"name\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"volume\":\"298 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2011.6031378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 16th International Conference on Methods & Models in Automation & Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2011.6031378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
本文介绍了城市道路网络中用于控制道路交叉口无环交通灯的五种算法的比较。选择以下算法:计算复杂度低的Most Cars,作者的In-and-Outbound Lane Control算法,这是Most Cars的有效改进,Local hill - climb algorithm (LHC),强化学习RL 1 Bucket 2.0算法和神经网络GenNeural算法。
Approaches to control acyclic traffic lights in an exemplary urban road network
This paper presents a comparison of five algorithms used to control acyclic traffic lights at intersections of roads in an urban road network. The following algorithms are selected: Most Cars characterized by low computational complexity, the author's algorithm called In-and-Outbound Lane Control, which is an efficient modification of the Most Cars, Local Hill-Climbing algorithm (LHC), the reinforcement learning RL 1 Bucket 2.0 algorithm and the neural network GenNeural algorithm.