道路交通干线的信号协调控制技术研究
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摘要
干线交通信号协调控制是智能交通系统的重要组成部分,在缓解交通拥挤、提高路口路网的通行效率方面发挥着重要作用。本文以城市道路干线为主要研究对象,开展了对干线信号协调控制的研究,侧重研究了基于相位差优化的干线信号协调控制的实现方法。
论文在详细介绍道路交通信号控制基本理论的基础上,研究和分析了干线信号协调控制常用的两种方法:最大绿波带法和最小延误法。通过分析车辆在城市干线交叉口的双向延误规律,从相对相位差的约束条件出发,以干线总延误最小为目标,建立了基于相位差优化的城市干线交通信号协调控制模型。
在本文建立的相位差优化模型的基础上,讨论了干线交通控制参数的分层控制思想,以消除干线信号协调控制时输入参数与输出之间的耦合。并分析了城市干线交通信号的动态协调控制,给出了控制参数的动态调整表达式。
对自适应遗传算法进行了理论研究,并实现其C++编程。在VC++6.0编程环境下,实现了干线交通信号协调控制的实验软件设计。在该实验软件上对本文建立的干线信号协调控制模型进行研究,得到优化后的相位差和干线总延误,并将所得结果同定时控制的结果进行比较分析。
实验结果表明相位差优化后的干线总延误均小于定时控制的干线总延误,对干线上交叉口支路方向的延误影响也较小。证明了本文所建模型的有效性,所使用的自适应遗传算法在运算速度上能满足城市干线交通动态协调控制中相位差优化的实时性要求。
Arterial traffic signal coordination control is an important part of intelligent transportation system (ITS), and it plays a significant role in relieving traffic congestion and improving traffic efficiency of intersections and highway network. In this paper, urban traffic artery is served as major research object, then arterial signal coordination control is studied, and its realizable method based on offset optimization is mainly researched.
The paper introduces basic theories of road traffic signal control at length, then method of maximum green-wave band and method of minimum delay are studied and analyzed, which are two common methods of arterial signal coordination control. Aiming at the minimal delay of vehicles at arterial crossings, the paper proposes a mode based on offset optimization for urban arterial traffic signal coordination control using constraint conditions of relative offset by analyzing the two-way rules of traffic delay at the intersections.
Base on the offset optimization model built in this paper, we discuss layering control concept of arterial traffic control parameters, which will eliminate couplings of input parameters with output. Moreover, dynamic coordination control of urban arterial traffic signal is analyzed, and computed expressions of control parameters are given.
The theories of adaptive genetic algorithm (AGA) are studied in this paper, and its C++ codes are achieved. Meanwhile, experimental software of urban arterial traffic signal coordination control is designed by using visual c++ 6.0. Then experimental studies of urban arterial traffic signal coordination control model built in this paper are completed through using the above experimental software, then get the optimal offsets and arterial delay, and compare its performance with one of timing control.
Results show the arterial delay is obviously less than one in timing control, and there is little impact to delay of arterial intersections in slip directions. Which proves the validity of the model built in this paper, and the fast speed of AGA could satisfy the real-time demands of offset optimization in urban arterial traffic dynamic coordination control.
论文在详细介绍道路交通信号控制基本理论的基础上,研究和分析了干线信号协调控制常用的两种方法:最大绿波带法和最小延误法。通过分析车辆在城市干线交叉口的双向延误规律,从相对相位差的约束条件出发,以干线总延误最小为目标,建立了基于相位差优化的城市干线交通信号协调控制模型。
在本文建立的相位差优化模型的基础上,讨论了干线交通控制参数的分层控制思想,以消除干线信号协调控制时输入参数与输出之间的耦合。并分析了城市干线交通信号的动态协调控制,给出了控制参数的动态调整表达式。
对自适应遗传算法进行了理论研究,并实现其C++编程。在VC++6.0编程环境下,实现了干线交通信号协调控制的实验软件设计。在该实验软件上对本文建立的干线信号协调控制模型进行研究,得到优化后的相位差和干线总延误,并将所得结果同定时控制的结果进行比较分析。
实验结果表明相位差优化后的干线总延误均小于定时控制的干线总延误,对干线上交叉口支路方向的延误影响也较小。证明了本文所建模型的有效性,所使用的自适应遗传算法在运算速度上能满足城市干线交通动态协调控制中相位差优化的实时性要求。
Arterial traffic signal coordination control is an important part of intelligent transportation system (ITS), and it plays a significant role in relieving traffic congestion and improving traffic efficiency of intersections and highway network. In this paper, urban traffic artery is served as major research object, then arterial signal coordination control is studied, and its realizable method based on offset optimization is mainly researched.
The paper introduces basic theories of road traffic signal control at length, then method of maximum green-wave band and method of minimum delay are studied and analyzed, which are two common methods of arterial signal coordination control. Aiming at the minimal delay of vehicles at arterial crossings, the paper proposes a mode based on offset optimization for urban arterial traffic signal coordination control using constraint conditions of relative offset by analyzing the two-way rules of traffic delay at the intersections.
Base on the offset optimization model built in this paper, we discuss layering control concept of arterial traffic control parameters, which will eliminate couplings of input parameters with output. Moreover, dynamic coordination control of urban arterial traffic signal is analyzed, and computed expressions of control parameters are given.
The theories of adaptive genetic algorithm (AGA) are studied in this paper, and its C++ codes are achieved. Meanwhile, experimental software of urban arterial traffic signal coordination control is designed by using visual c++ 6.0. Then experimental studies of urban arterial traffic signal coordination control model built in this paper are completed through using the above experimental software, then get the optimal offsets and arterial delay, and compare its performance with one of timing control.
Results show the arterial delay is obviously less than one in timing control, and there is little impact to delay of arterial intersections in slip directions. Which proves the validity of the model built in this paper, and the fast speed of AGA could satisfy the real-time demands of offset optimization in urban arterial traffic dynamic coordination control.
引文
[1]中国公安部交通管理局[EB/OL].http://www.mps.gov.cn/n16/n85753/n85870/index.html, 2010-07-09.
[2]袁振洲.道路交通管理与控制[M].北京:人民交通出版社,2007.
[3]马强.城市干线协调控制与Petri网建模仿真[D].武汉:华中科技大学硕士学位论文,2007.
[4]刘智勇.智能交通控制理论及其应用[M].北京:科学出版社,2003.
[5]邹智军,杨东援.道路交通仿真研究综述[J].交通运输工程学报,2001,1(2):88-91.
[6]邹智军.新一代交通仿真技术综述[J].系统仿真学报,2010,22(9):2037-2042.
[7]魏明.交通仿真的发展及研究现状[J].系统仿真学报,2003,15(8):1179-1183.
[8]我国智能交通的现状及发展趋[EB/OL].http://www.feicheng.gov.cn/contents/291/33458.html, 2010-07-01.
[9]李晓红.城市干线交通信号协调优化控制及仿真[D].大连:大连理工大学硕士学位论文, 2007.
[10] Park B, Rouphail NM., Sacks J. Assessment of stochastic signal optimization method using microsimulation[J].Transportation Research Record,2001:40-45.
[11] Halim Ceylan, Michael G.H. Bell. Traffic signal timing optimization based on genetic algorithm approach, including drivers’routing[J].Transportation Research,2004,(38):329-342.
[12] Shenoda, Machemehl. Development of a Phase-by-Phase, Arrival-Based, Delay-Optimized Adaptive Traffic Signal Control Methodology with Metaheuristic Search[R]. United States: Southwest Region University, 2006:102-112.
[13] Balaji, German, Srinivasan. Urban traffic signal control using reinforcement learning agents[J]. IET Intelligent Transport Systems, 2010, 4(3):177-188.
[14] Redman, Howe. Evaluating multi-agent traffic controllers[C]. Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, 2010:80-85.
[15]万绪军,陆化普.线控系统中相位差优化模型的研究[J].中国公路学报,2001,14(2):99-102.
[16]常云涛,彭国雄.基于遗传算法的城市干道协调控制[J].交通运输工程学报,2003, 3(2):106-112.
[17]朱文兴,贾磊.城市交通主干路相位差优化研究[J].计算机工程与应用,2005,20:212-214.
[18]王俊刚,于泉,高颖等.变带速干线协调控制模型研究[J].公路交通科技,2005,22(4):108-111.
[19]马凤伟,刘智勇.城市交通干线的Q-学习控制算法[J].五邑大学学报(自然科学版),2007, 21(3):16-22.
[20]臧利林,贾磊,罗永刚.交通干线相邻交叉口动态协调控制研究[J].公路交通科技,2007,24(7):103-106.
[21]沈国江,许卫明.交通干线动态双向绿波带控制技术研究[J].浙江大学学报(工学版),2008, 42(9):1625-1630.
[22]吴恩,杨晓光,吴震等.基于遗传算法的干线协调控制参数共同优化[J].同济大学学报(自然科学版),2008,36(7):921-926.
[23]李晓红,沈岚,肖鹏.城市交通干线的协调优化控制模型[J].大连工业大学学报,2009, 28(1):61-65.
[24]卢凯,徐建闽,叶瑞敏.经典干道协调控制信号配时数解算法的改进[J].公路交通科技,2009, 26(1):120-124.
[25]张菁,巨永锋.城市交通干线多路口协调控制[J].长安大学学报(自然科学版),2009, 29(1):82-87.
[26]李乐,史忠科.基于遗传算法改进的交通干线信号优化研究[J].计算机仿真,2009, 26(1):260-263.
[27] Xiangjie Kong, Feng Xia, Chuang Lin, Guojiang Shen. Urban Arterial Traffic Intelligent Coordination Control Technique and Its Application[R].Proceedings of the 8th World Congress on Intelligent Control and Automation, 2010:5042-5047.
[28] Lanyu Zhang, Hui Wang, Ming He, Hong Liu. The influencing factors to Arterial coordinate control system[J]. E-Product E-Service and E-Entertainment (ICEEE), 2010:1-3.
[29] JTG B01-2003.公路工程技术标准[S],2004-01-29.
[30]骆勇.城市道路信号交叉口配时系统优化设计[J].计算机工程与应用,2009,45(21):229-231.
[31]胡浩.饱和交通干线的信号协调控制算法研究[D].武汉:华中师范大学硕士学位论文,2009.
[32]朱阳,李雨恒,张瑆.城市道路交通信号实时优化控制[J].数学的实践与认识,2009, 39(16):82-92.
[33]王秋平,谭学龙,张生瑞.城市单点交叉口信号配时优化[J].交通运输工程学报,2006, 6(2):60-64.
[34]李瑞敏.城市道路交通管理[M].北京:人民交通出版社,2009.
[35]徐吉万,徐冬玲.城市交通的计算机控制和管理[M].上海:测绘出版社,1988.
[36] Ma Yingying,Yang Xiaoguang, Zhong Zhangjian. Offline Offset Models for Coordinated Signal Control[R].Beijing: Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems, 2008:111-114.
[37]马永光.城市交通干线信号优化控制方法的研究[D].天津:天津大学硕士论文,2007.
[38]陈宁宁,何兆成,余志.考虑动态红灯排队消散时间的改进MAXBAND模型[J].武汉理工大学学报(交通科学与工程版),2009,33(5):843-847.
[39] Lu Shoufeng, Liu Ximin, Dai Shiqiang. Revised MAXBAND Model for BandwidthOptimization of Traffic Flow Dispersion[J].2008 ISECS International Colloquium on Computing, Communication, Control, and Management, 2008:85-89.
[40] Li Xiaohong, Tan Guozhen, Chen Chao. Urban Arterial Road Green-wave Control Based on Genetic Algorithm[R].Chongqing:Proceedings of the 7th World Congress on Intelligent Control and Automation,2008:3087-3092.
[41]卢凯,徐建闽.干道协调控制相位差模型及其优化方法[J].中国公路学报,2008,21(1):83-88.
[42]王殿海,李凤,宋现敏.干线协调控制中公共周期优化方法研究[J].交通信息与安全,2009, 27(5): 10-13.
[43]王小平,曹立明.遗传算法—理论、应用与软件实现[M].西安:西安交通大学出版社,2002.
[44]王晶,杨建军.具有局部搜索能力的自适应变异遗传算法[J].北京化工大学学报,2003, 30(6):80-83.
[45] Sun Yan, Sun Zheng. Using Orthogonal Genetic Algorithm to Optimize Location of Traffic Counting Points[J].Proceedings of the 26th Chinese Control Conference,2007:75-78.
[46] Srinivas, Patnaik. Adaptive Probabilities of Crossover Genetic in Mutation and Algorithms[J]. IEEE Transactions on Systems, Main and Cybernetic, 1994, 24(4):656-667.
[47] LI Taoshen, GE Zhihui. Adaptive Genetic Algorithm for Multiple QoS Anycast Routing[J]. Intelligent Computing and Intelligent Systems, 2009:772-776.
[48] Siyan Wang, Guoli Zhang. A Self-adaptive Genetic Algorithm Based on Region Balance Variation[J]. Second International Workshop on Knowledge Discovery and Data Mining, 2009: 104-107.
[49]石山,励庆孚,王兴华.基于自适应遗传算法的无刷直流电机的优化设计[J].西安交通大学学报,2002,36(12):1215-1218.
[50] YAN Tai-shan. Adaptive Genetic Algorithm Simulating Human Reproduction Mode and Its Application in Multi-peak Function Optimization[J].Intelligent Systems and Applications, 2009: 1-4.
[51] Yingjie Xing, Zhentong Chen, Jing Sun and Long Hu. An Improved Adaptive Genetic Algorithm for Job-Shop Scheduling Problem[J].Third International Conference on Natural Computation, 2007,(4):287-291.
[52]沈颖,朱翀,徐英俊.道路饱和度计算方法研究[J].交通标准化,2007,(1):125-129.
[2]袁振洲.道路交通管理与控制[M].北京:人民交通出版社,2007.
[3]马强.城市干线协调控制与Petri网建模仿真[D].武汉:华中科技大学硕士学位论文,2007.
[4]刘智勇.智能交通控制理论及其应用[M].北京:科学出版社,2003.
[5]邹智军,杨东援.道路交通仿真研究综述[J].交通运输工程学报,2001,1(2):88-91.
[6]邹智军.新一代交通仿真技术综述[J].系统仿真学报,2010,22(9):2037-2042.
[7]魏明.交通仿真的发展及研究现状[J].系统仿真学报,2003,15(8):1179-1183.
[8]我国智能交通的现状及发展趋[EB/OL].http://www.feicheng.gov.cn/contents/291/33458.html, 2010-07-01.
[9]李晓红.城市干线交通信号协调优化控制及仿真[D].大连:大连理工大学硕士学位论文, 2007.
[10] Park B, Rouphail NM., Sacks J. Assessment of stochastic signal optimization method using microsimulation[J].Transportation Research Record,2001:40-45.
[11] Halim Ceylan, Michael G.H. Bell. Traffic signal timing optimization based on genetic algorithm approach, including drivers’routing[J].Transportation Research,2004,(38):329-342.
[12] Shenoda, Machemehl. Development of a Phase-by-Phase, Arrival-Based, Delay-Optimized Adaptive Traffic Signal Control Methodology with Metaheuristic Search[R]. United States: Southwest Region University, 2006:102-112.
[13] Balaji, German, Srinivasan. Urban traffic signal control using reinforcement learning agents[J]. IET Intelligent Transport Systems, 2010, 4(3):177-188.
[14] Redman, Howe. Evaluating multi-agent traffic controllers[C]. Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, 2010:80-85.
[15]万绪军,陆化普.线控系统中相位差优化模型的研究[J].中国公路学报,2001,14(2):99-102.
[16]常云涛,彭国雄.基于遗传算法的城市干道协调控制[J].交通运输工程学报,2003, 3(2):106-112.
[17]朱文兴,贾磊.城市交通主干路相位差优化研究[J].计算机工程与应用,2005,20:212-214.
[18]王俊刚,于泉,高颖等.变带速干线协调控制模型研究[J].公路交通科技,2005,22(4):108-111.
[19]马凤伟,刘智勇.城市交通干线的Q-学习控制算法[J].五邑大学学报(自然科学版),2007, 21(3):16-22.
[20]臧利林,贾磊,罗永刚.交通干线相邻交叉口动态协调控制研究[J].公路交通科技,2007,24(7):103-106.
[21]沈国江,许卫明.交通干线动态双向绿波带控制技术研究[J].浙江大学学报(工学版),2008, 42(9):1625-1630.
[22]吴恩,杨晓光,吴震等.基于遗传算法的干线协调控制参数共同优化[J].同济大学学报(自然科学版),2008,36(7):921-926.
[23]李晓红,沈岚,肖鹏.城市交通干线的协调优化控制模型[J].大连工业大学学报,2009, 28(1):61-65.
[24]卢凯,徐建闽,叶瑞敏.经典干道协调控制信号配时数解算法的改进[J].公路交通科技,2009, 26(1):120-124.
[25]张菁,巨永锋.城市交通干线多路口协调控制[J].长安大学学报(自然科学版),2009, 29(1):82-87.
[26]李乐,史忠科.基于遗传算法改进的交通干线信号优化研究[J].计算机仿真,2009, 26(1):260-263.
[27] Xiangjie Kong, Feng Xia, Chuang Lin, Guojiang Shen. Urban Arterial Traffic Intelligent Coordination Control Technique and Its Application[R].Proceedings of the 8th World Congress on Intelligent Control and Automation, 2010:5042-5047.
[28] Lanyu Zhang, Hui Wang, Ming He, Hong Liu. The influencing factors to Arterial coordinate control system[J]. E-Product E-Service and E-Entertainment (ICEEE), 2010:1-3.
[29] JTG B01-2003.公路工程技术标准[S],2004-01-29.
[30]骆勇.城市道路信号交叉口配时系统优化设计[J].计算机工程与应用,2009,45(21):229-231.
[31]胡浩.饱和交通干线的信号协调控制算法研究[D].武汉:华中师范大学硕士学位论文,2009.
[32]朱阳,李雨恒,张瑆.城市道路交通信号实时优化控制[J].数学的实践与认识,2009, 39(16):82-92.
[33]王秋平,谭学龙,张生瑞.城市单点交叉口信号配时优化[J].交通运输工程学报,2006, 6(2):60-64.
[34]李瑞敏.城市道路交通管理[M].北京:人民交通出版社,2009.
[35]徐吉万,徐冬玲.城市交通的计算机控制和管理[M].上海:测绘出版社,1988.
[36] Ma Yingying,Yang Xiaoguang, Zhong Zhangjian. Offline Offset Models for Coordinated Signal Control[R].Beijing: Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems, 2008:111-114.
[37]马永光.城市交通干线信号优化控制方法的研究[D].天津:天津大学硕士论文,2007.
[38]陈宁宁,何兆成,余志.考虑动态红灯排队消散时间的改进MAXBAND模型[J].武汉理工大学学报(交通科学与工程版),2009,33(5):843-847.
[39] Lu Shoufeng, Liu Ximin, Dai Shiqiang. Revised MAXBAND Model for BandwidthOptimization of Traffic Flow Dispersion[J].2008 ISECS International Colloquium on Computing, Communication, Control, and Management, 2008:85-89.
[40] Li Xiaohong, Tan Guozhen, Chen Chao. Urban Arterial Road Green-wave Control Based on Genetic Algorithm[R].Chongqing:Proceedings of the 7th World Congress on Intelligent Control and Automation,2008:3087-3092.
[41]卢凯,徐建闽.干道协调控制相位差模型及其优化方法[J].中国公路学报,2008,21(1):83-88.
[42]王殿海,李凤,宋现敏.干线协调控制中公共周期优化方法研究[J].交通信息与安全,2009, 27(5): 10-13.
[43]王小平,曹立明.遗传算法—理论、应用与软件实现[M].西安:西安交通大学出版社,2002.
[44]王晶,杨建军.具有局部搜索能力的自适应变异遗传算法[J].北京化工大学学报,2003, 30(6):80-83.
[45] Sun Yan, Sun Zheng. Using Orthogonal Genetic Algorithm to Optimize Location of Traffic Counting Points[J].Proceedings of the 26th Chinese Control Conference,2007:75-78.
[46] Srinivas, Patnaik. Adaptive Probabilities of Crossover Genetic in Mutation and Algorithms[J]. IEEE Transactions on Systems, Main and Cybernetic, 1994, 24(4):656-667.
[47] LI Taoshen, GE Zhihui. Adaptive Genetic Algorithm for Multiple QoS Anycast Routing[J]. Intelligent Computing and Intelligent Systems, 2009:772-776.
[48] Siyan Wang, Guoli Zhang. A Self-adaptive Genetic Algorithm Based on Region Balance Variation[J]. Second International Workshop on Knowledge Discovery and Data Mining, 2009: 104-107.
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