昆明市主城区交通控制关键技术研究
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摘要
近年来,随着昆明市的社会经济迅猛发展,城市整体功能向国际性城市的提升,获得了越来越多的国际社会的认同,昆明市的发展目标定位为区域性国际城市。但随之而来的是私家车保有量的持续增加,主城区交通需求的急剧增加,导致了昆明市主城区交通问题急剧恶化,交通拥堵问题严重,交通压力空前。为应对城市发展的交通压力,昆明市相关部门逐年加大交通基础设施投资力度,开展了大量的基础设施建设和改建工程,虽在一定程度上缓解了城市交通拥堵问题,但由于主城区路网结构不合理以及交通需求总量大、增长迅猛,机动车总量和出行量的增长速度远远超过昆明市新建、扩建、修建道路及相应交通基础设施的增长,况且单靠简单的增加基础交通设施建设并不能从根本上解决城市交通的拥堵问题。因此,针对昆明市现有的城市路网状况,结合城市未来发展规划的需求,运用现代的城市交通组织优化、交通管制、控制等措施,从时间和空间两个层面上对交通流进行合理的组织优化,以达到减少甚至消除城市交通拥堵,减轻城市交通压力的目的。
本文正是针对昆明市主城区现有道路交通状况,在不增加基础交通设施建设的基础上,通过分析主城区交通OD需求、出行特性、现有路网构成、道路特点等,研究适合昆明市主城区的交通控制方法。本文的研究主要依托《昆明主城区道路交通组织与控制一体化理论与方法研究及示范应用》,《基于多源交通信息的昆明主城区交通诱导理论方法和实施技术研究》,论文总共包括六部分,主要内容和成果如下：
(1)绪论。首先介绍了昆明市主城区交通状况及城市道路网特点,由此引出昆明市主城区交通控制关键技术研究的主要目的和重要意义。结合昆明市主城区交通特性,利用交通控制等技术开发适合昆明市的交通控制技术,提出了本文研究的思路、研究框架和章节安排。
(2)昆明市主城区干线交通协调控制技术。针对昆明市主城区干线交通的特点,首先介绍了城市干线协调相关理论,在此基础上详细分析了干线绿波协调交叉口控制范围划分方法。然后建立了一种基于模糊递阶理论的单向绿波协调控制模型,从周期时长、相位差以及绿信比三个方面做了优化研究。接下来分析了干线双向绿波协调的控制目标,从交叉口延误出发,建立了一种双向绿波协调控制模型。最后研究了基于层次分析法的干线协调控制影响评价方法。
(3)昆明市主城区公交信号优先控制技术。本章提出优先发展公交的城市交通出行方式,以公交信息采集与处理方法为基础,分别给出了保障普通公交和大容量公交(BRT)优先通行权的各项控制措施。普通公交优先通行权的控制策略从空间和时间两个方面展开,并提出了一种用于边界交叉口中固定配时条件下疏散公交优先感应的信号控制策略,最后给出按公交到达时刻以及对路口交通流扰动程度的不同而制定的相应的感应控制策略,并给出公交感应信号的触发阈值(TV1、TV2、TK)。在BRT的优先通行权的实现控制策略中,空间上从转向交通处理、交通流限制、进口道设置、线路组织方面进行优化；时间上从被动优先控制、主动优先控制以及实时优先控制三个方面介绍各公交通行权的实现措施。
(4)昆明市主城区高架快速路交通与地面交通协同联动控制技术。以昆明市主城区高架快速路的交通管理与控制现状为背景,以昆明市主城区快速路出入口匝道及关联交叉口的现场调查、检测器数据为基础,对昆明市主城区快速路的交通流宏观特性、微观特性以及交汇地段的交通流特性进行研究,并从整体路网的角度出发,研究基于ALINEA模型和LWR模型的高架快速路匝道及关联交叉口的协同管理与控制策略及模型,研究了可变车道等技术,最后以昆明市主城区石闸立交桥周边快速路系统为背景进行外场测试及应用,实际运行结果表明：所研究的高架快速路交通与地面交通协同控制技术具有良好的实际意义与应用价值。
(5)交通信号控制与可变信息板路径诱导的协同优化技术。综合分析可变信息板的信息构成、信息来源、信息发布原则及信息更新间隔,深入的了解的可变信息板的路网交通流的影响机理及作用机制。在此基础上,考虑到控制策略对驾驶员的路径选择行为存在影响,通过增加交通控制策略变量,把交通控制策略对路径选择的影响考虑进来,提出了考虑诱导一致性的交通信号控制与VMS路径诱导的协同优化模型,并采用微观交通仿真工具Paramics进行了仿真模拟与分析。
(6)总结与展望。该部分对本文的研究工作及取得的成果进行了全面的总结,并指出了本文现有研究的不足,对下一步研究工作进行了展望。
In recent years, with the rapid development of social economy and the promotion to international level of the city whole function, Kunming has obtained more and more international social acceptance. Kunming's development goal is regional international city. However, cars quantities continue to increase, and the traffic demand sharply increase, all this leaded to Kunming city traffic problems worsen sharply, serious traffic jam and unprecedented traffic pressure. To cope with the development of city traffic pressure, Kunming related department increased transportation infrastructure investment year by year, and carried out a lot of infrastructure construction and renovation project. All these measures relieved parts of the urban traffic congestion problems. But because the structure of traffic network is not reasonable, and total demand is growing rapidly, the total quantity of motor vehicles and the demand of traffic are rising much faster than Kunming transportation infrastructure growth, still, add basic transportation construction cannot fundamentally solve urban traffic congestion problems. Therefore, in view of existing urban road network status of Kunming, combined with the future urban development planning needs, use modern city traffic organization optimization, traffic control to reduce or even eliminate urban traffic congestion and relieve city traffic pressure from the two aspects of time and space.
This paper is aimed at Kunming city existing road traffic conditions, without any increase in foundation transportation facilities, analyses the traffic OD demand, travel features and the characteristics of network structure, and study the traffic control method for Kunming. This research mainly relys on "Kunming city road traffic organization and control integration theory and method research and demonstration applications", and the main content of this paper are as follows:
(1) Introduction. Firstly, the paper introduced the traffic and urban road network characteristics of Kunming. And this drawned the main purpose and significance of traffic control technlogy in Kunming city, and puts forward the thinking, research framework and chapters arrangement.
(2) Route traffic coordination control technology of Kunming city. For the characters of the City of Kunming'trunk road, firstly this paper introduce the theory of traffic truck road coordination control, based on these theory analysis the division approach of the traffic control work zone in detail. then this paper proposed a model of one-way green wave coordination control based on fuzzy neural network, from the optimization of the cycle, phase and split of intersections. Then by analyzing the control objectives of the two-way green wave coordination control, starting from the intersection delay, proposed a model of two-way green wave coordination control. At last, this paper analysis the impact assessment methods of the traffic truck road coordination control based on Analytic hierarchy process.
(3) Bus signal priority control technology of Kunming city. This chapter proposed a urban travel mode based on public transport priority development,and give the various control measuers for ensuring the travel priority of the common bus and BRT. The control strategy of the common bus contains the space and the time two aspects,and a prior inductive evacuation bus singal control strategy was put forward which is can be used for border crossings in condition of fixed timing.At last,a adaptive inductive control strategy was proposed based on the bus arrived time and the change of the crossing traffic flow disturbances degree. Bus induction signal trigger threshold as followed (TV1、TV2、TV3). In the control strategy of the prior bus travel right, on the space,it would optimize from the steering traffic processing, traffic flow restrictions, import set, line distribution;on the time,it could realize the measures from three aspects:passive priority control, active priority control and real-time priority control.
(4) Elevated freeway traffic and ground traffic collaborative linkage control technology of Kunming city. Taking the expressway management and control status of kunming as a background, chapter four studied the kunming expressway traffic flow macro properties, microscopic characteristics and the intersection lots traffic flow characteristics based on the kunming expressway entrance ramp, exit ramp and the correlation crossing field detected data. From the overall benefit of the road network, the paper proposed the expressway entrance ramp, exit ramp and the correlation crossing coordination management and control strategies and models based the ALINEA and LWR model and finally took the field test and application under the background of stone-brake overpass peripheral expressway in Kunming. The actual operation effect showed that:the proposed expressway traffic coordination management and control technology has good practical significance and application value.
(5) The traffic signal control and variable information boards route guidance synergy optimization technique. Comprehensive analysis of variable information board information structure, the source of information, information release principles and information update interval, in-depth understanding of variable information board network traffic flow, the influence mechanism and function mechanism. On this basis, considering the control strategy of driver path choice behavior exist by increasing traffic impact, the traffic control strategy variables, control strategy for routing influence into account, putting forward the traffic signal control induced consistency with the VMS route guidance collaborated optimization model and adopting micro traffic simulation tools VISSIM simulation modeling and analysis.
(6) Conclusion and prospect. This part makes a comprehensive summary, and points out the existing limitations of the study and the paper further research work of prospected.
本文正是针对昆明市主城区现有道路交通状况,在不增加基础交通设施建设的基础上,通过分析主城区交通OD需求、出行特性、现有路网构成、道路特点等,研究适合昆明市主城区的交通控制方法。本文的研究主要依托《昆明主城区道路交通组织与控制一体化理论与方法研究及示范应用》,《基于多源交通信息的昆明主城区交通诱导理论方法和实施技术研究》,论文总共包括六部分,主要内容和成果如下：
(1)绪论。首先介绍了昆明市主城区交通状况及城市道路网特点,由此引出昆明市主城区交通控制关键技术研究的主要目的和重要意义。结合昆明市主城区交通特性,利用交通控制等技术开发适合昆明市的交通控制技术,提出了本文研究的思路、研究框架和章节安排。
(2)昆明市主城区干线交通协调控制技术。针对昆明市主城区干线交通的特点,首先介绍了城市干线协调相关理论,在此基础上详细分析了干线绿波协调交叉口控制范围划分方法。然后建立了一种基于模糊递阶理论的单向绿波协调控制模型,从周期时长、相位差以及绿信比三个方面做了优化研究。接下来分析了干线双向绿波协调的控制目标,从交叉口延误出发,建立了一种双向绿波协调控制模型。最后研究了基于层次分析法的干线协调控制影响评价方法。
(3)昆明市主城区公交信号优先控制技术。本章提出优先发展公交的城市交通出行方式,以公交信息采集与处理方法为基础,分别给出了保障普通公交和大容量公交(BRT)优先通行权的各项控制措施。普通公交优先通行权的控制策略从空间和时间两个方面展开,并提出了一种用于边界交叉口中固定配时条件下疏散公交优先感应的信号控制策略,最后给出按公交到达时刻以及对路口交通流扰动程度的不同而制定的相应的感应控制策略,并给出公交感应信号的触发阈值(TV1、TV2、TK)。在BRT的优先通行权的实现控制策略中,空间上从转向交通处理、交通流限制、进口道设置、线路组织方面进行优化；时间上从被动优先控制、主动优先控制以及实时优先控制三个方面介绍各公交通行权的实现措施。
(4)昆明市主城区高架快速路交通与地面交通协同联动控制技术。以昆明市主城区高架快速路的交通管理与控制现状为背景,以昆明市主城区快速路出入口匝道及关联交叉口的现场调查、检测器数据为基础,对昆明市主城区快速路的交通流宏观特性、微观特性以及交汇地段的交通流特性进行研究,并从整体路网的角度出发,研究基于ALINEA模型和LWR模型的高架快速路匝道及关联交叉口的协同管理与控制策略及模型,研究了可变车道等技术,最后以昆明市主城区石闸立交桥周边快速路系统为背景进行外场测试及应用,实际运行结果表明：所研究的高架快速路交通与地面交通协同控制技术具有良好的实际意义与应用价值。
(5)交通信号控制与可变信息板路径诱导的协同优化技术。综合分析可变信息板的信息构成、信息来源、信息发布原则及信息更新间隔,深入的了解的可变信息板的路网交通流的影响机理及作用机制。在此基础上,考虑到控制策略对驾驶员的路径选择行为存在影响,通过增加交通控制策略变量,把交通控制策略对路径选择的影响考虑进来,提出了考虑诱导一致性的交通信号控制与VMS路径诱导的协同优化模型,并采用微观交通仿真工具Paramics进行了仿真模拟与分析。
(6)总结与展望。该部分对本文的研究工作及取得的成果进行了全面的总结,并指出了本文现有研究的不足,对下一步研究工作进行了展望。
In recent years, with the rapid development of social economy and the promotion to international level of the city whole function, Kunming has obtained more and more international social acceptance. Kunming's development goal is regional international city. However, cars quantities continue to increase, and the traffic demand sharply increase, all this leaded to Kunming city traffic problems worsen sharply, serious traffic jam and unprecedented traffic pressure. To cope with the development of city traffic pressure, Kunming related department increased transportation infrastructure investment year by year, and carried out a lot of infrastructure construction and renovation project. All these measures relieved parts of the urban traffic congestion problems. But because the structure of traffic network is not reasonable, and total demand is growing rapidly, the total quantity of motor vehicles and the demand of traffic are rising much faster than Kunming transportation infrastructure growth, still, add basic transportation construction cannot fundamentally solve urban traffic congestion problems. Therefore, in view of existing urban road network status of Kunming, combined with the future urban development planning needs, use modern city traffic organization optimization, traffic control to reduce or even eliminate urban traffic congestion and relieve city traffic pressure from the two aspects of time and space.
This paper is aimed at Kunming city existing road traffic conditions, without any increase in foundation transportation facilities, analyses the traffic OD demand, travel features and the characteristics of network structure, and study the traffic control method for Kunming. This research mainly relys on "Kunming city road traffic organization and control integration theory and method research and demonstration applications", and the main content of this paper are as follows:
(1) Introduction. Firstly, the paper introduced the traffic and urban road network characteristics of Kunming. And this drawned the main purpose and significance of traffic control technlogy in Kunming city, and puts forward the thinking, research framework and chapters arrangement.
(2) Route traffic coordination control technology of Kunming city. For the characters of the City of Kunming'trunk road, firstly this paper introduce the theory of traffic truck road coordination control, based on these theory analysis the division approach of the traffic control work zone in detail. then this paper proposed a model of one-way green wave coordination control based on fuzzy neural network, from the optimization of the cycle, phase and split of intersections. Then by analyzing the control objectives of the two-way green wave coordination control, starting from the intersection delay, proposed a model of two-way green wave coordination control. At last, this paper analysis the impact assessment methods of the traffic truck road coordination control based on Analytic hierarchy process.
(3) Bus signal priority control technology of Kunming city. This chapter proposed a urban travel mode based on public transport priority development,and give the various control measuers for ensuring the travel priority of the common bus and BRT. The control strategy of the common bus contains the space and the time two aspects,and a prior inductive evacuation bus singal control strategy was put forward which is can be used for border crossings in condition of fixed timing.At last,a adaptive inductive control strategy was proposed based on the bus arrived time and the change of the crossing traffic flow disturbances degree. Bus induction signal trigger threshold as followed (TV1、TV2、TV3). In the control strategy of the prior bus travel right, on the space,it would optimize from the steering traffic processing, traffic flow restrictions, import set, line distribution;on the time,it could realize the measures from three aspects:passive priority control, active priority control and real-time priority control.
(4) Elevated freeway traffic and ground traffic collaborative linkage control technology of Kunming city. Taking the expressway management and control status of kunming as a background, chapter four studied the kunming expressway traffic flow macro properties, microscopic characteristics and the intersection lots traffic flow characteristics based on the kunming expressway entrance ramp, exit ramp and the correlation crossing field detected data. From the overall benefit of the road network, the paper proposed the expressway entrance ramp, exit ramp and the correlation crossing coordination management and control strategies and models based the ALINEA and LWR model and finally took the field test and application under the background of stone-brake overpass peripheral expressway in Kunming. The actual operation effect showed that:the proposed expressway traffic coordination management and control technology has good practical significance and application value.
(5) The traffic signal control and variable information boards route guidance synergy optimization technique. Comprehensive analysis of variable information board information structure, the source of information, information release principles and information update interval, in-depth understanding of variable information board network traffic flow, the influence mechanism and function mechanism. On this basis, considering the control strategy of driver path choice behavior exist by increasing traffic impact, the traffic control strategy variables, control strategy for routing influence into account, putting forward the traffic signal control induced consistency with the VMS route guidance collaborated optimization model and adopting micro traffic simulation tools VISSIM simulation modeling and analysis.
(6) Conclusion and prospect. This part makes a comprehensive summary, and points out the existing limitations of the study and the paper further research work of prospected.
引文
[1]C J Khisty, B K Lall. Transportation Engineering[M]. New Jersey:PRENTICE HALL,1998.
[2]P R Lowric. The Sydney Coordinated Adaptive Traffic System-Principles, Methodoligy, Algorithms[C].London, UK. IEEE International Conference on Road Traffic Signaling, 1982.
[3]Gartner N H, Assman S F, Lasaga F, et al. MULTIBAND:A Variable-Bandwidth Arterial Progression Scheme [J]. Transportation Research Record 1287, Transportation Research Board, National Research Council, Washington, D.C.,1990:212-222.
[4]Gartner N H. Road Traffic Control:Progression Methods[M]. Concise Eneyelopedia of Traffic and Transportation Systems (M. Papageorgiou, Editor), Pergamon Press, New York.1991.
[5]Park B, Schneeberger J. Micro scope simulation model calibration and validation:case study of VISSIM simulation model for a coordinated actuated Signal system [J]. Transportation Research Record 1856,2003:759-765.
[6]H Ceylan, MGH Bell. Traffic signal timing optimization based on genetic algorithm approach, including drivers'routing [J]. Transportation Research Part B,2004:169-185.
[7]M Shenoda, R Machemehl. Development of a Phase-by-Phase, Arrival-Based, Delay-Optimized Adaptive Traffic Signal Control Methodology with Metaheuristic Search[J].SWUTC/06/167863-1,2006:1-102.
[8]谭惠丽,黄乒花,李华兵.交通灯控制下主干道的交通流研究[J].物理学报.2003,52(5)：1127-1131.
[9]张卫华,陆化普,石琴,刘强.公交优先的信号交叉口配时优化方法[J].交通运输工程学报,2004：50-53.
[10]李凤.公交信号优先协调控制理论与方法研究[D].吉林大学,2009.
[11]杨晓光,林瑜,杭明升.信号控制交叉口公共汽车优先信号确定方法研究[J].中国公路学报,2001：102-104.
[12]关伟,申金升,葛芳.公交优先的信号控制策略研究[J].北方交通大学系统工程研究所,2001：177-179.
[13]Wonho Kim, L. R. Rilett, Improved Transit Signal Priority System for Networks with Nearside Bus Stops[J]. Transportation Research Record, n 1925, p 205-214,2005.
[14]Peter G. Furth, Theo H. J. Muller, Conditional Bus Priority at Signalized Intersections: Better Service with Less Traffic Disruption[J]. Transportation Research Record, n 1731, p 23-30,2000.
[15]Michael Eichler and Carlos F. Daganzo, Bus lanes with intermittent priority:Strategy formulae and an evaluation [J]. Transportation Research Part B:Methodological Volume 40, Issue 9, November 2006, Pages 731-744.
[16]Sam Yagar and Bin Han, A procedure for real-time signal control that considers transit interference and priority[J]. Transportation Research Part B:Methodological Volume 28, Issue 4, August 1994, Pages 315-331.
[17]Hongchao Liu,Meng Li. Alexander Skabardonis et al. Development and application of a simulation tool for transit signal priority [C]. Washington D.C.Transportation Research Board 84th Annual Meeting,2004.
[18]Pitu Mirchandani, Lary Head, Anna Knyazyan. An Approach Towards the Intergration of Bus Priority and Traffic Adaptive Signal Control[C].T Washington D.C.Transportation Research Board 80th Annual Meeting,2000.
[19]Gang-len Chang, Meenakshy Vasudevan,Chih-chiang Su. Modeling and evaluation of adaptive bus-preemption control with and without automatic vehicle location systems [J].Transportation Research A,1996,30(4):251-268.
[20]MacDorman.Case study in sensitivity of highway economic factors[J]. Highway Research Record,1965,100,2-19.
[21]Glickman, T.S.. Optimal periodic control of reversible traffic operations. Ph.D. Thesis, Department of Civil Engineering, Johns Hopkins University, Baltimore, MD.,1970.
[22]Hemphill, J., Surti, V.H.. A feasibility study of a reversible-lane facility for a Denver street corridor. Transportation Research Record,1974,514:29-32.
[23]Jiuh-Biing Sheu, Stephen G. Ritchie. Stochastic modeling and real-time prediction of vehicular lane-changing behavior[J]. Transportation Research Part B,2001,35:695-716.
[24]Sangho Kim, Shashi Shekhar, Manki Min. Contraflow Transportation Network Reconfiguration for Evacuation Route Planning [J]. Transactions on knowledge and data engineering,2008,20 (8):1115-1129.
[25]H. Tuydes and A. Ziliaskopoulos, "Network Re-Design to Optimize Evacuation Contraflow," Technical Report 04-4715, Proc.83rd Ann. Meeting of the Transportation Research Board,2004.
[26]Chi Xie, Dung-Ying Lin, S.Travis Waller. A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies [J]. Transportation Research Part E,2010,46,295-316.
[27]崔妍,刘东.北京市朝阳路可变车道交通组织研究[J].道路交通与安全,2006,6(9)：21-24.
[28]张好智,高自友.可变车道的道路交通网络设计优化方法[J].中国管理科学,2007,15(2)：86-97.
[29]岳雷,汤震,杜豫川,孙立军.上海世博会可变车道技术研究[J].交通与运输,2009(7)：56-59.
[30]倪富健,刘志超.可变交通信息牌的最优分布模型[J].信息与控制,2003,32(5)：3952398.
[31]刘智勇.智能交通控制理论及其应用[M].北京：科学出版社,2003.
[32]吴兵,李晔.交通管理与控制[M].北京：人民交通出版社,2005.
[33]王东.基于遗传算法的城市干线交通信号协调控制研究[D].西安：长安大学,2010.
[34]杨庆芳,陈林.交通控制子区动态划分方法[J].吉林大学学报(工学版).2006,36：139-142.
[35]常丽君.城市区域交通状态判别方法研究[D].长春：吉林大学,2008.
[36]段里仁.道路交通自动控制[M].北京：中国人民大学出版社,1991.
[37]赵国永,陈阳舟.中关村西区的单向交通干线协调控制[J].交通与计算机.2006,24(128)：28-31.
[38]刘智勇,吴今培.城市交通大系统递阶模糊神经网络控制[J].信息与控制,1997,26(6)：441-447.
[39]仇东华.干线协调控制的研究与设计[D].合肥：中国科学技术大学,2009.
[40]邵春福.交通规划原理[M].北京：中国铁道出版社,2004.
[41]李克平译.交通信号控制指南——德国现行规范(RiLSA) [M].德国：道路与交通工程研究学会编；北京：中国建筑工业出版社,2006.
[42]Wanner Colombini Martins, BRT SYSTEMS[R].BEIJING,2004.
[43]Herbert S. Levinson, Samuel Zmmerman, Scott Rutherford. TCRP report 90:Bus Rapid Transit Volume 2:Implementation Guidelines[R].2003.
[44]陈建宗.快速公交信号交叉口优先通行技术研究[D].西安：长安大学,2008.
[45]陈军.公交信号优先控制及其在BRT中的应用[D].长沙：中南大学,2009.
[46]陈光勤.快速公交车辆平面交叉口信号优先实现方法[J].同济大学学报(自然科学版).2006,34(1)：41-46.
[47]马万经,杨晓光.公交信号优先控制策略研究综述[J].城市交通.2010,8(6)：70-78.
[48]Papageorgiou M.An integrated control approach for traffic corridors[J].Transportation Research Part C,1995,3(1):19-30.
[49]刘红红,王鑫玥,杨兆升.城市公共交通优先的信号控制策略[J].公路交通科技.2004,21(5)：122-124.
[50]Wu Jifeng, Chang Gang-len.An integrated optimal control and algorithm for commuting corridors[J].International Transactions on Operational Research,1999,6:39-55.
[51]Zhang H, Ritchie S G, ReckerW W. Some general results on the optimal ramp control problem[J]. Transportation Research Part C:Emerging Technologies,1996,4 (2):51-69.
[52]Tian Zong Z, Kevin B, Roelof E, et al.Integrated control strategies for surface street and freeway systems[C]//The 81th Annual Meeting of Transportation Research Board Meeting,Washington D.C,2002.
[53]Eil K, Ravi-Praveen A, John B. Adaptive coordination of ramp meter and intersection signal for optimal management of freeway corridor[C]//The 82th Annual Meeting of Transportation Research Board Meeting,Washington D.C.2003.
[54]任黎立.高速道路入口匝道控制方法综述[J].交通标准化,2006(5)：146-149性拥挤.
[55]van den Berg M, De Schutter B, Hegyi A, et al.Model predictive control for mixed urban and freeway networks[C]//The 83th Annual Meeting of Transportation Research Board Meeting,Washington D.C.2004.
[56]Zhang H M, Recker W W.On optimal freeway ramp control policies for congested traffic corridors[J].Transportation Research Part B,1999,33:417-436.
[57]Yang Xiao-fang, Yang Xiao-guang, Fu Qiang, et al.Study of integrated control strategy for on ramp of urban expressway and interrelated urban road[C]//6th international conference on ITS telecommunications, Chengdu,2006:110-113.
[58]郑建湖,董德存,陈洪.城市快速路入口匝道控制策略比较分析[J].计算机测量与控制,2006,14(2)：196-199.
[59]周小鹏,冯奇,孙立军.城市快速路入口匝道控制策略与流程设计[J].山东交通学院学报,2006,14(2)：7-9.
[60]Daganzo C F.The cell transmission model:A dynamic representation of highway traffic consistent with the hydrodynamic theory[J]. Transportation Research,1993,28:269-287. [13] Feldman O, Maher M.A cell transmission model applied to the optimisation of traffic signals [C]//Universities'Transport Study Group,34th Annual Conference,2002,2.
[61]杨晓芳,付强,杨晓光.城市快速路与地面道路交通整合控制分析[J].交通与计算机,2005,23(5)：4-7.
[62]PapageorgiouM,Blosseville J M,Habib H S. Modeling and real-time control of traffic flow on the southern part of boulevard peripherique in Paris:Part Ⅱ:Coordinated On-Ramp Metering [J]. Trunspn Res.2A 24,1990:361-370.
[63]Papageorgiou M, Habib H S, Blosseville J M. ALINEA:a local feedback control law for on-ramp metering[J]. Transportation Research Record,1991,1320:58-64.
[64]Papageorgiou M, H. Hadi Salem, M iddleham F. ALINEA local ramp metering: summary of field results[J]. Transportation Research Record,1997,1603:90-98.
[65]Chu L, Yang X. Optimization of the ALINE A ramp metering control using genetic algorithm with micro-simulation[C]//Transportation Research Board 82nd Annual Meeting, Washington, DC.,2003.
[66]聂磊,杨晓光,庄斌,等.快速路入口匝道控制适应性研究[J].交通与计算机,2006,24(3)：18-21.
[67]Yang Xiaofang, Han Yin, Fu Qiang.A control method for signal intersection which join with off-ramp[C]//2008 International Conference of Chinese Logistics and Transportation Professionals, ChengDu,2008.
[68]Mu"oz L, Sun Xiaotian, Horowitz R, et al.Traffic density estimation with the cell transmission model [C]//Proceedings of the American Control Conference Denver, Colorado June 4-6,2003:3750-3755.
[69]Mu"oz L, Sun Xiaotian, Sun Dengfeng, et al.Methodological calibration of the cell transmission model [C]//Proceedings of the American Control Conference Boston, Massachusetts June 30-July 2,2004:798-803.
[70]Jane Lappin, Jon Bottom. Understanding and Predicting Traveler Response to Information:A Literature Review[R]. U.S. Department of Transportation Federal Highway Administration, December 2001
[71]杨兆升.交通运输系统规划—有关理论与方法[M].北京：人民交通出版社,1998年9月,pp.111-112
[72]Carlos F.Daganzo. The cell transmission model:A dynamic representation of highway traffic consistent with the hydrodynamic theory[J]. Transportation Research B,1994,28(4), pp.269-287
[73]Carlos F.Daganzo. The Cell Transmission Model, PartⅡ:Network Traffic[J]. Transportation Research B,1995,29(2), pp.79-93
[74]卢守峰.基于元胞自动机的交通信号控制与路径诱导的协同研究[D].长春：吉林大学,2009.
[2]P R Lowric. The Sydney Coordinated Adaptive Traffic System-Principles, Methodoligy, Algorithms[C].London, UK. IEEE International Conference on Road Traffic Signaling, 1982.
[3]Gartner N H, Assman S F, Lasaga F, et al. MULTIBAND:A Variable-Bandwidth Arterial Progression Scheme [J]. Transportation Research Record 1287, Transportation Research Board, National Research Council, Washington, D.C.,1990:212-222.
[4]Gartner N H. Road Traffic Control:Progression Methods[M]. Concise Eneyelopedia of Traffic and Transportation Systems (M. Papageorgiou, Editor), Pergamon Press, New York.1991.
[5]Park B, Schneeberger J. Micro scope simulation model calibration and validation:case study of VISSIM simulation model for a coordinated actuated Signal system [J]. Transportation Research Record 1856,2003:759-765.
[6]H Ceylan, MGH Bell. Traffic signal timing optimization based on genetic algorithm approach, including drivers'routing [J]. Transportation Research Part B,2004:169-185.
[7]M Shenoda, R Machemehl. Development of a Phase-by-Phase, Arrival-Based, Delay-Optimized Adaptive Traffic Signal Control Methodology with Metaheuristic Search[J].SWUTC/06/167863-1,2006:1-102.
[8]谭惠丽,黄乒花,李华兵.交通灯控制下主干道的交通流研究[J].物理学报.2003,52(5)：1127-1131.
[9]张卫华,陆化普,石琴,刘强.公交优先的信号交叉口配时优化方法[J].交通运输工程学报,2004：50-53.
[10]李凤.公交信号优先协调控制理论与方法研究[D].吉林大学,2009.
[11]杨晓光,林瑜,杭明升.信号控制交叉口公共汽车优先信号确定方法研究[J].中国公路学报,2001：102-104.
[12]关伟,申金升,葛芳.公交优先的信号控制策略研究[J].北方交通大学系统工程研究所,2001：177-179.
[13]Wonho Kim, L. R. Rilett, Improved Transit Signal Priority System for Networks with Nearside Bus Stops[J]. Transportation Research Record, n 1925, p 205-214,2005.
[14]Peter G. Furth, Theo H. J. Muller, Conditional Bus Priority at Signalized Intersections: Better Service with Less Traffic Disruption[J]. Transportation Research Record, n 1731, p 23-30,2000.
[15]Michael Eichler and Carlos F. Daganzo, Bus lanes with intermittent priority:Strategy formulae and an evaluation [J]. Transportation Research Part B:Methodological Volume 40, Issue 9, November 2006, Pages 731-744.
[16]Sam Yagar and Bin Han, A procedure for real-time signal control that considers transit interference and priority[J]. Transportation Research Part B:Methodological Volume 28, Issue 4, August 1994, Pages 315-331.
[17]Hongchao Liu,Meng Li. Alexander Skabardonis et al. Development and application of a simulation tool for transit signal priority [C]. Washington D.C.Transportation Research Board 84th Annual Meeting,2004.
[18]Pitu Mirchandani, Lary Head, Anna Knyazyan. An Approach Towards the Intergration of Bus Priority and Traffic Adaptive Signal Control[C].T Washington D.C.Transportation Research Board 80th Annual Meeting,2000.
[19]Gang-len Chang, Meenakshy Vasudevan,Chih-chiang Su. Modeling and evaluation of adaptive bus-preemption control with and without automatic vehicle location systems [J].Transportation Research A,1996,30(4):251-268.
[20]MacDorman.Case study in sensitivity of highway economic factors[J]. Highway Research Record,1965,100,2-19.
[21]Glickman, T.S.. Optimal periodic control of reversible traffic operations. Ph.D. Thesis, Department of Civil Engineering, Johns Hopkins University, Baltimore, MD.,1970.
[22]Hemphill, J., Surti, V.H.. A feasibility study of a reversible-lane facility for a Denver street corridor. Transportation Research Record,1974,514:29-32.
[23]Jiuh-Biing Sheu, Stephen G. Ritchie. Stochastic modeling and real-time prediction of vehicular lane-changing behavior[J]. Transportation Research Part B,2001,35:695-716.
[24]Sangho Kim, Shashi Shekhar, Manki Min. Contraflow Transportation Network Reconfiguration for Evacuation Route Planning [J]. Transactions on knowledge and data engineering,2008,20 (8):1115-1129.
[25]H. Tuydes and A. Ziliaskopoulos, "Network Re-Design to Optimize Evacuation Contraflow," Technical Report 04-4715, Proc.83rd Ann. Meeting of the Transportation Research Board,2004.
[26]Chi Xie, Dung-Ying Lin, S.Travis Waller. A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies [J]. Transportation Research Part E,2010,46,295-316.
[27]崔妍,刘东.北京市朝阳路可变车道交通组织研究[J].道路交通与安全,2006,6(9)：21-24.
[28]张好智,高自友.可变车道的道路交通网络设计优化方法[J].中国管理科学,2007,15(2)：86-97.
[29]岳雷,汤震,杜豫川,孙立军.上海世博会可变车道技术研究[J].交通与运输,2009(7)：56-59.
[30]倪富健,刘志超.可变交通信息牌的最优分布模型[J].信息与控制,2003,32(5)：3952398.
[31]刘智勇.智能交通控制理论及其应用[M].北京：科学出版社,2003.
[32]吴兵,李晔.交通管理与控制[M].北京：人民交通出版社,2005.
[33]王东.基于遗传算法的城市干线交通信号协调控制研究[D].西安：长安大学,2010.
[34]杨庆芳,陈林.交通控制子区动态划分方法[J].吉林大学学报(工学版).2006,36：139-142.
[35]常丽君.城市区域交通状态判别方法研究[D].长春：吉林大学,2008.
[36]段里仁.道路交通自动控制[M].北京：中国人民大学出版社,1991.
[37]赵国永,陈阳舟.中关村西区的单向交通干线协调控制[J].交通与计算机.2006,24(128)：28-31.
[38]刘智勇,吴今培.城市交通大系统递阶模糊神经网络控制[J].信息与控制,1997,26(6)：441-447.
[39]仇东华.干线协调控制的研究与设计[D].合肥：中国科学技术大学,2009.
[40]邵春福.交通规划原理[M].北京：中国铁道出版社,2004.
[41]李克平译.交通信号控制指南——德国现行规范(RiLSA) [M].德国：道路与交通工程研究学会编；北京：中国建筑工业出版社,2006.
[42]Wanner Colombini Martins, BRT SYSTEMS[R].BEIJING,2004.
[43]Herbert S. Levinson, Samuel Zmmerman, Scott Rutherford. TCRP report 90:Bus Rapid Transit Volume 2:Implementation Guidelines[R].2003.
[44]陈建宗.快速公交信号交叉口优先通行技术研究[D].西安：长安大学,2008.
[45]陈军.公交信号优先控制及其在BRT中的应用[D].长沙：中南大学,2009.
[46]陈光勤.快速公交车辆平面交叉口信号优先实现方法[J].同济大学学报(自然科学版).2006,34(1)：41-46.
[47]马万经,杨晓光.公交信号优先控制策略研究综述[J].城市交通.2010,8(6)：70-78.
[48]Papageorgiou M.An integrated control approach for traffic corridors[J].Transportation Research Part C,1995,3(1):19-30.
[49]刘红红,王鑫玥,杨兆升.城市公共交通优先的信号控制策略[J].公路交通科技.2004,21(5)：122-124.
[50]Wu Jifeng, Chang Gang-len.An integrated optimal control and algorithm for commuting corridors[J].International Transactions on Operational Research,1999,6:39-55.
[51]Zhang H, Ritchie S G, ReckerW W. Some general results on the optimal ramp control problem[J]. Transportation Research Part C:Emerging Technologies,1996,4 (2):51-69.
[52]Tian Zong Z, Kevin B, Roelof E, et al.Integrated control strategies for surface street and freeway systems[C]//The 81th Annual Meeting of Transportation Research Board Meeting,Washington D.C,2002.
[53]Eil K, Ravi-Praveen A, John B. Adaptive coordination of ramp meter and intersection signal for optimal management of freeway corridor[C]//The 82th Annual Meeting of Transportation Research Board Meeting,Washington D.C.2003.
[54]任黎立.高速道路入口匝道控制方法综述[J].交通标准化,2006(5)：146-149性拥挤.
[55]van den Berg M, De Schutter B, Hegyi A, et al.Model predictive control for mixed urban and freeway networks[C]//The 83th Annual Meeting of Transportation Research Board Meeting,Washington D.C.2004.
[56]Zhang H M, Recker W W.On optimal freeway ramp control policies for congested traffic corridors[J].Transportation Research Part B,1999,33:417-436.
[57]Yang Xiao-fang, Yang Xiao-guang, Fu Qiang, et al.Study of integrated control strategy for on ramp of urban expressway and interrelated urban road[C]//6th international conference on ITS telecommunications, Chengdu,2006:110-113.
[58]郑建湖,董德存,陈洪.城市快速路入口匝道控制策略比较分析[J].计算机测量与控制,2006,14(2)：196-199.
[59]周小鹏,冯奇,孙立军.城市快速路入口匝道控制策略与流程设计[J].山东交通学院学报,2006,14(2)：7-9.
[60]Daganzo C F.The cell transmission model:A dynamic representation of highway traffic consistent with the hydrodynamic theory[J]. Transportation Research,1993,28:269-287. [13] Feldman O, Maher M.A cell transmission model applied to the optimisation of traffic signals [C]//Universities'Transport Study Group,34th Annual Conference,2002,2.
[61]杨晓芳,付强,杨晓光.城市快速路与地面道路交通整合控制分析[J].交通与计算机,2005,23(5)：4-7.
[62]PapageorgiouM,Blosseville J M,Habib H S. Modeling and real-time control of traffic flow on the southern part of boulevard peripherique in Paris:Part Ⅱ:Coordinated On-Ramp Metering [J]. Trunspn Res.2A 24,1990:361-370.
[63]Papageorgiou M, Habib H S, Blosseville J M. ALINEA:a local feedback control law for on-ramp metering[J]. Transportation Research Record,1991,1320:58-64.
[64]Papageorgiou M, H. Hadi Salem, M iddleham F. ALINEA local ramp metering: summary of field results[J]. Transportation Research Record,1997,1603:90-98.
[65]Chu L, Yang X. Optimization of the ALINE A ramp metering control using genetic algorithm with micro-simulation[C]//Transportation Research Board 82nd Annual Meeting, Washington, DC.,2003.
[66]聂磊,杨晓光,庄斌,等.快速路入口匝道控制适应性研究[J].交通与计算机,2006,24(3)：18-21.
[67]Yang Xiaofang, Han Yin, Fu Qiang.A control method for signal intersection which join with off-ramp[C]//2008 International Conference of Chinese Logistics and Transportation Professionals, ChengDu,2008.
[68]Mu"oz L, Sun Xiaotian, Horowitz R, et al.Traffic density estimation with the cell transmission model [C]//Proceedings of the American Control Conference Denver, Colorado June 4-6,2003:3750-3755.
[69]Mu"oz L, Sun Xiaotian, Sun Dengfeng, et al.Methodological calibration of the cell transmission model [C]//Proceedings of the American Control Conference Boston, Massachusetts June 30-July 2,2004:798-803.
[70]Jane Lappin, Jon Bottom. Understanding and Predicting Traveler Response to Information:A Literature Review[R]. U.S. Department of Transportation Federal Highway Administration, December 2001
[71]杨兆升.交通运输系统规划—有关理论与方法[M].北京：人民交通出版社,1998年9月,pp.111-112
[72]Carlos F.Daganzo. The cell transmission model:A dynamic representation of highway traffic consistent with the hydrodynamic theory[J]. Transportation Research B,1994,28(4), pp.269-287
[73]Carlos F.Daganzo. The Cell Transmission Model, PartⅡ:Network Traffic[J]. Transportation Research B,1995,29(2), pp.79-93
[74]卢守峰.基于元胞自动机的交通信号控制与路径诱导的协同研究[D].长春：吉林大学,2009.
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