城市道路交叉口机动车运行特性研究
|
摘要
交叉口是城市路网中连续交通流与间断交通流相互转化的“咽喉”，常常发生交通拥堵，导致路网运行效率降低。机动车作为交叉口交通流的重要组成部分，其运行特性直接影响着交叉口的运行效率；对交叉口处机动车的运行特性进行深入分析和精确建模，可以更好的为交通管控、交通组织提供理论依据，有效地缓解交通拥堵。
机动车运行特性研究主要分为微观运行特性和宏观运行特性研究，交叉口处机动车微观运行特性包括机动车的跟驰、换道、停车避让等驾驶行为，这些驾驶行为通常是驾驶员在驾驶任务和周边交通环境共同影响下，对机动车进行操纵体现出来的，机动车驾驶员不同的驾驶心理，会造成机动车不同的运行特性。由此可见，驾驶员是交叉口运行情况优劣的核心，驾驶员驾驶心理是研究机动车运行特性的关键。故在交叉口机动车微观运行特性方面，论文从交叉口处机动车驾驶员的驾驶心理角度入手，分析交叉口处客体对目标车辆驾驶员驾驶心理的影响，研究机动车驾驶员驾驶行为，进而实现了对交叉口机动车微观运行特性的深入分析和精确建模。交叉口处机动车宏观运行特性包括机动车的到达分布、传播延误、通行效率等，这些宏观运行特性的研究对交叉口处交通管控、交通组织以及缓解交通拥堵有着重要的作用。为了对其进行详细分析，论文结合数理统计中的概率论模型、交通流理论中的流-密-速关系模型、交通波模型等，对交叉口机动车到达分布特性、延误特性、传播特性等等宏观运行特性进行了定性描述，并结合视频采集手段，对建立的模型进行了验证。
论文的研究可以丰富和发展城市道路交通流理论，为交叉口的交通控制方案制定、交通组织管理等提供理论基础，进而达到提升交叉口交通安全和交叉口通行效率的目的，论文的具体研究内容包括以下几部分：
（1）研究了交叉口处机动车驾驶员驾驶心理受到的刺激影响情况。通过分析交叉口处客体对机动车驾驶员驾驶心理的影响情况，研究机动车不同运行状态下的驾驶员驾驶心理，给出了机动车在运行时所需的安全距离和静止时所需的安全距离及驾驶员的感知-响应情况，进而确定周边客体对机动车驾驶员所产生的影响范围和影响强度，并基于以上分析，构建了交叉口处机动车驾驶员受到刺激影响的一般模型。
（2）分析了机动车驾驶员在不同刺激影响情况下的驾驶决策和驾驶行为。通过对不同刺激影响下的驾驶员心理决策过程进行分析，并结合贝叶斯概率理论和模糊聚类理论，建立了基于贝叶斯概率理论和模糊聚类理论的驾驶员驾驶行为决策模型；随后利用第二章建立的驾驶员心理压力模型及驾驶员的感知响应关系，确定了不同情况下的驾驶员心理压力，给出了不同相应临界值下的驾驶员驾驶行为，建立了驾驶员心理压力与机动车运行特性的关系模型，并对模型的可行性进行了分析。
（3）建立了交叉口处阻滞和摩擦干扰下驾驶员驾驶行为模型。结合机动车运行特性与驾驶员驾驶心理的关系模型、驾驶员驾驶行为决策模型，研究交叉口处驾驶员在阻滞干扰下和摩擦干扰下的驾驶行为决策，分析机动车释放过程中的阻滞干扰和摩擦干扰对驾驶员驾驶心理的影响情况，将驾驶员的应对行为和车辆运行行为进行数学抽象，建立摩擦干扰和阻滞干扰情况下的驾驶员驾驶行为模型，确定了阻滞干扰和摩擦干扰下的机动车微观运行特性。
（4）研究了交叉口机动车流的到达分布、延误、传播等宏观运行特性。对交叉口处机动车的宏观运行特性进行研究，本部分从上下游交叉口间的流量关系入手，通过分析交叉口处机动车的到达规律，绿灯末期的机动车运行特性，给出了交叉口机动车的到达分布模型、到达延误模型，绿灯末期驾驶员驾驶行为模型。随后结合数理统计中的概率论模型、交通流理论中的流-密-速关系模型、交通波模型等，对交叉口机动车到达分布特性、延误特性、传播特性等等宏观运行特性进行了定性描述，并结合视频采集手段，对建立的模型进行了验证。
最后，对论文的研究进展及主要成果进行总结，并提出研究过程中存在的主要问题以及下一步需要探索内容。
Signalized intersections, as crucial points for uninterrupted and continuum trafficflow transforming into each other, are congested frequently, which leads to the decreaseof vehicles operating efficiency in urban network. As a major component of traffic flowat the intersection, vehicles affect the efficiency at the intersections directly. Thus, tosupply the strategy making of traffic management and traffic control with better theorysupports, and alleviate traffic jam efficiently, analyzing the operating characteristics ofvehicles at the intersections deeply and establishing the exact models are necessary.
Operating characteristics of vehicles can be divided into microscopic andmacroscopic ones. The main studies of microscopic characteristics of the vehiclesconsist of the behaviors of lane change, acceleration and deceleration, stop and yield.These behaviors are determined by driving task and the surrounding traffic environment,and different psychology results in different behaviors. Thus, in terms of microscopiccharacteristic, the research in this paper analyzed the surrounding objects influence onthe vehicle, and made deeply analysis and model establishment about the microscopiccharacters come true. Macroscopic characteristics consist of vehicle arrival distribution,propagation delay and traffic efficiency, and so forth, and these characteristics aresignificantly beneficial to traffic control, traffic organization strategies making andeasement of traffic congestion. To deeply analyze the characteristics, in this paper, theyare described qualitatively combined with probabilistic models, traffic flow theory andshock wave models. The models established in this paper are tested with video data.
The research in this paper can enrich and develop the traffic flow theory in urbanroad, and supply the making of traffic control strategies and traffic managements withtheory support, which aims to strengthen security and enhance the inefficiency atintersection. There are four major sections in this paper, which shows as following:
(1)The situations that the drivers are affected by psychological stimulation atintersections are studied. Through analyzing the conditions which the objects haveinfluence on the drivers’ psychology, and studying when the vehicle are in different states,two kinds of safety distances between two vehicles are proposed with static and movingtraffic flow separately, and the percept-respond process are depicted. Eventually, based on the definition of the scope and intensity of influence on the driver, the general modelwhich describes the affect on drivers at intersections is established.
(2) The driving behaviors and decisions are analyzed when the driver is affected bydifferent psychological stimulations. With analyzing the driver's decision-makingprocesses in kinds of stimulus situations, combining with Bayesian probability theoryand fuzzy clustering theory, a driving behavior decision model is created. To establish arelationship model between psychological pressure and operating characteristics ofvehicles, the driver's psychological stress model and the perception-respond diagram areused to calculate driver's psychological pressure under different circumstances. Thisrelationship model is analyzed for its feasibility.
(3) Driving behavior model with blocking and friction interfering at intersection isestablished. This section Combines the relationship model between operatingcharacteristics and drivers’ psychological with driving behavior decision model to studythe process of decision-making in the situations of friction and block interferer during thedischarge process, and analyzes the psychological effects on the drivers. To create thedriving behavior models with interfering of blocking and friction interfering, thebehaviors of driver and vehicle are transformed into mathematical abstractions.
(4) The macro-operating characteristics involving arrival distribution, delay andpropagation were studied. In terms of macroscopic characteristics, from the flowrelationship between upstream intersection and downstream intersection, analyzing thearrival distribution and vehicles operating characteristics at end of green interval, thearrival distribution model, delay model and driving behavior at the tail of green periodwere established. Combined with probability theory model of mathematical statistics,flow-density-velocity relationship model of traffic flow theory, shock wave models,macroscopic characteristics were described qualitatively, and models established in thissection are tested with video data.
Finally, the research progress and the main results of the paper are summarized, andthe main problems existing in the research and the future work are proposed.
机动车运行特性研究主要分为微观运行特性和宏观运行特性研究，交叉口处机动车微观运行特性包括机动车的跟驰、换道、停车避让等驾驶行为，这些驾驶行为通常是驾驶员在驾驶任务和周边交通环境共同影响下，对机动车进行操纵体现出来的，机动车驾驶员不同的驾驶心理，会造成机动车不同的运行特性。由此可见，驾驶员是交叉口运行情况优劣的核心，驾驶员驾驶心理是研究机动车运行特性的关键。故在交叉口机动车微观运行特性方面，论文从交叉口处机动车驾驶员的驾驶心理角度入手，分析交叉口处客体对目标车辆驾驶员驾驶心理的影响，研究机动车驾驶员驾驶行为，进而实现了对交叉口机动车微观运行特性的深入分析和精确建模。交叉口处机动车宏观运行特性包括机动车的到达分布、传播延误、通行效率等，这些宏观运行特性的研究对交叉口处交通管控、交通组织以及缓解交通拥堵有着重要的作用。为了对其进行详细分析，论文结合数理统计中的概率论模型、交通流理论中的流-密-速关系模型、交通波模型等，对交叉口机动车到达分布特性、延误特性、传播特性等等宏观运行特性进行了定性描述，并结合视频采集手段，对建立的模型进行了验证。
论文的研究可以丰富和发展城市道路交通流理论，为交叉口的交通控制方案制定、交通组织管理等提供理论基础，进而达到提升交叉口交通安全和交叉口通行效率的目的，论文的具体研究内容包括以下几部分：
（1）研究了交叉口处机动车驾驶员驾驶心理受到的刺激影响情况。通过分析交叉口处客体对机动车驾驶员驾驶心理的影响情况，研究机动车不同运行状态下的驾驶员驾驶心理，给出了机动车在运行时所需的安全距离和静止时所需的安全距离及驾驶员的感知-响应情况，进而确定周边客体对机动车驾驶员所产生的影响范围和影响强度，并基于以上分析，构建了交叉口处机动车驾驶员受到刺激影响的一般模型。
（2）分析了机动车驾驶员在不同刺激影响情况下的驾驶决策和驾驶行为。通过对不同刺激影响下的驾驶员心理决策过程进行分析，并结合贝叶斯概率理论和模糊聚类理论，建立了基于贝叶斯概率理论和模糊聚类理论的驾驶员驾驶行为决策模型；随后利用第二章建立的驾驶员心理压力模型及驾驶员的感知响应关系，确定了不同情况下的驾驶员心理压力，给出了不同相应临界值下的驾驶员驾驶行为，建立了驾驶员心理压力与机动车运行特性的关系模型，并对模型的可行性进行了分析。
（3）建立了交叉口处阻滞和摩擦干扰下驾驶员驾驶行为模型。结合机动车运行特性与驾驶员驾驶心理的关系模型、驾驶员驾驶行为决策模型，研究交叉口处驾驶员在阻滞干扰下和摩擦干扰下的驾驶行为决策，分析机动车释放过程中的阻滞干扰和摩擦干扰对驾驶员驾驶心理的影响情况，将驾驶员的应对行为和车辆运行行为进行数学抽象，建立摩擦干扰和阻滞干扰情况下的驾驶员驾驶行为模型，确定了阻滞干扰和摩擦干扰下的机动车微观运行特性。
（4）研究了交叉口机动车流的到达分布、延误、传播等宏观运行特性。对交叉口处机动车的宏观运行特性进行研究，本部分从上下游交叉口间的流量关系入手，通过分析交叉口处机动车的到达规律，绿灯末期的机动车运行特性，给出了交叉口机动车的到达分布模型、到达延误模型，绿灯末期驾驶员驾驶行为模型。随后结合数理统计中的概率论模型、交通流理论中的流-密-速关系模型、交通波模型等，对交叉口机动车到达分布特性、延误特性、传播特性等等宏观运行特性进行了定性描述，并结合视频采集手段，对建立的模型进行了验证。
最后，对论文的研究进展及主要成果进行总结，并提出研究过程中存在的主要问题以及下一步需要探索内容。
Signalized intersections, as crucial points for uninterrupted and continuum trafficflow transforming into each other, are congested frequently, which leads to the decreaseof vehicles operating efficiency in urban network. As a major component of traffic flowat the intersection, vehicles affect the efficiency at the intersections directly. Thus, tosupply the strategy making of traffic management and traffic control with better theorysupports, and alleviate traffic jam efficiently, analyzing the operating characteristics ofvehicles at the intersections deeply and establishing the exact models are necessary.
Operating characteristics of vehicles can be divided into microscopic andmacroscopic ones. The main studies of microscopic characteristics of the vehiclesconsist of the behaviors of lane change, acceleration and deceleration, stop and yield.These behaviors are determined by driving task and the surrounding traffic environment,and different psychology results in different behaviors. Thus, in terms of microscopiccharacteristic, the research in this paper analyzed the surrounding objects influence onthe vehicle, and made deeply analysis and model establishment about the microscopiccharacters come true. Macroscopic characteristics consist of vehicle arrival distribution,propagation delay and traffic efficiency, and so forth, and these characteristics aresignificantly beneficial to traffic control, traffic organization strategies making andeasement of traffic congestion. To deeply analyze the characteristics, in this paper, theyare described qualitatively combined with probabilistic models, traffic flow theory andshock wave models. The models established in this paper are tested with video data.
The research in this paper can enrich and develop the traffic flow theory in urbanroad, and supply the making of traffic control strategies and traffic managements withtheory support, which aims to strengthen security and enhance the inefficiency atintersection. There are four major sections in this paper, which shows as following:
(1)The situations that the drivers are affected by psychological stimulation atintersections are studied. Through analyzing the conditions which the objects haveinfluence on the drivers’ psychology, and studying when the vehicle are in different states,two kinds of safety distances between two vehicles are proposed with static and movingtraffic flow separately, and the percept-respond process are depicted. Eventually, based on the definition of the scope and intensity of influence on the driver, the general modelwhich describes the affect on drivers at intersections is established.
(2) The driving behaviors and decisions are analyzed when the driver is affected bydifferent psychological stimulations. With analyzing the driver's decision-makingprocesses in kinds of stimulus situations, combining with Bayesian probability theoryand fuzzy clustering theory, a driving behavior decision model is created. To establish arelationship model between psychological pressure and operating characteristics ofvehicles, the driver's psychological stress model and the perception-respond diagram areused to calculate driver's psychological pressure under different circumstances. Thisrelationship model is analyzed for its feasibility.
(3) Driving behavior model with blocking and friction interfering at intersection isestablished. This section Combines the relationship model between operatingcharacteristics and drivers’ psychological with driving behavior decision model to studythe process of decision-making in the situations of friction and block interferer during thedischarge process, and analyzes the psychological effects on the drivers. To create thedriving behavior models with interfering of blocking and friction interfering, thebehaviors of driver and vehicle are transformed into mathematical abstractions.
(4) The macro-operating characteristics involving arrival distribution, delay andpropagation were studied. In terms of macroscopic characteristics, from the flowrelationship between upstream intersection and downstream intersection, analyzing thearrival distribution and vehicles operating characteristics at end of green interval, thearrival distribution model, delay model and driving behavior at the tail of green periodwere established. Combined with probability theory model of mathematical statistics,flow-density-velocity relationship model of traffic flow theory, shock wave models,macroscopic characteristics were described qualitatively, and models established in thissection are tested with video data.
Finally, the research progress and the main results of the paper are summarized, andthe main problems existing in the research and the future work are proposed.
引文
[1]交通工程委员会.交通工程手册[M].北京:人民交通出版社.1998.
[2] Edie L C. Car-following and steady-state theory for noncongested traffic[J].Oper. Res.1961,9(1):66-76.
[3] Bando M., Hasebe K, etc. Model of traffic congestion and numericalsimulation [J]. Physical Review E,1995,51:1035-1042.
[4]汪秉宏,邝乐琪,许伯铭.高速公路交通流元胞自动机模型的一种统计平均解耦处理[J].物理学报,1998，47(6):906-915.
[5] May A D. Traffic Flow Fundamentals [M]. New Jersey: Prentiee-Hall,Inc,1990.
[6] Vlahogianni E I. Jr.Webber C.L. etc. Statistical characteristics of transitionalqueue conditions in signalized arterials [J]. Transportation Research Part C,2007,15(6):392-03.
[7]曲昭伟,刘诗序,王殿海等.模拟电路的信号交叉口交通流模型[J].吉林大学学报(工学版),2008(S1):49-52.
[8]王殿海,赵志宏.模拟电路系统研究网络交通流特性的思想与方法[J].系统工程理论与实践,2002(9):107-111.
[9] Pacey G M. The progress of a bunch of vehicles released from a trafficsignal.RRL Note, Transport and Road Research Laboratory [J]. Growthorne, UK,1956. No. RN/2665/GMP.
[10] Roberston D I. Transyt: A traffic network study tool [J]. RRL Report,No.LR253, Transport and Road Research Laboratory, Growthome, UK,1969.
[11] Al-ghamdi A S. Entering headway for through movements at urbansignalized intersections [J]. Ttrasportation Research record,1999, No.1967,42-47.
[12] Thirayoot Limanond, Suebpong Chookerd, Natcha Roubtonglang. Effects ofcountdown timers on queue discharge characteristics of through movement at asignalized intersection[J]. Transportation Research Part C.2009,17(6):662-671.
[13]邵长桥,杜晓辉,李光芹.信号交叉口排队离散车头时距统计分析[J].公路交通科技,2003,20（4）:76-79.
[14]钱大琳,蒋海峰等.信号交叉口混合交通流干扰影响及其计算方法研究[J].交通运输系统工程与信息.2006,6(3):75-78.
[15] Stokes, R. W. Capacities of triple left-turn lanes [C]. Rep. to Institute ofTransportation Engineers Technical Council Committee5P-5A., Washington, D.C.1995.
[16] Tarko, A P., and Perez-Cartagena, R. I. Calibration of capacity parametersfor signalized intersections in Indiana [J]. J. Transp. Eng.,2005,131(12),904-911.
[17]王炜,过秀成,等编著.交通工程学[M].南京:东南大学出版社.2000.
[18]郭冠英.用集散波法计算道路交通拥塞长度[J].上海公路,1997(2):39-41.
[19] Greenshields B D. A Study in Highway Capacity [C]. Highway Research Board, Proceedings,1935(14):448-477.
[20]Greenberg H. An analysis of traffic flow [J]. Operations Research.1959(7):78-85.
[21]Webster F.V. Traffic signal settings [J]. Road Research Laboratory Technical Paper, HMSO, London,1958. No.39.
[22]Stephanopoulos G, Michalopoulos P., Modeling and analysis of traffic queue dynamics at signalized intersections [J]. Transportation Research A,1979,13(5):295-307.
[23]Brilon W, Wu N. Delays at fixed-time traffic signals under time dependent traffic conditions [J]. Traffic Engineering and Control,1990,31(12):23-63.
[24]May A.D. Traffic Flow Fundamentals [M]. New Jersey:Prentiee-Hall, Inc,1990.
[25]Vlahogianni E.I., Jr. Webber C.L., etc. Statistical characteristics of transitional queue conditions in signalized arterials [J] Transportation Research Part C,2007,15(6):392-03.
[26]Heidemann D. Queue length and delay distributions at traffic signals [J]. Transportation Research Part B,1994,28(5):377-389.
[27]Heidemann D. Queue length and waiting-time distributions at priority intersections [J]. Transportation Research Part B,1991,25(4):163-174.
[28]Songchitruksa P. Hard E.N. Queuing simulation of roadside survey station: blocked traffic lane [J]. Trasportation Research Part A,2008,42(6):857-873.
[29]Comert G, Cetin mecit. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research,2008.7.384-396.
[30]张亚平,李硕.信号交叉口车辆集结与消散分析[J].长沙交通学院学报,1999,15(3)：57-61.
[31]王殿海,景春光,曲昭伟.交通波理论在交叉口交通流分析中的应用[J].中国公路学报,2002,15(1)：93-96.
[32]韩凤春,刘东,曹金璇,马社强.城市交叉口混合交通流特征及提高通行能力对策研究[J].中国人民公安大学学报(自然科学版),2004.2,Total No.40,93-96.
[33]徐良杰,王炜.信号交叉口行人过街时间模型[J].交通运输工程学报,2005,5(1)：111-115.
[34]姚荣涵.车辆排队模型研究.吉林：吉林大学博士学位论文[D],2007.
[35]Webster F.V. Traffic signal settings [J]. Road Research Laboratory Technical Paper, HMSO, London,1958. No.39.
[36]Akcelik R. Time-dependent expressions for delay, stop rate and queue length at traffic signals [R]. International Report AIR, Australian Road Research Board, Vermont South,367-11980.
[37]Akcelik R. The highway capacity manual:delay formula for signalized intersection ITE Journal [M].1988,58(3):23-27.
[38]Olszewski P. Overall Delay, Stopped Delay, and Stops at Signalized Intersections [J]. Journal of Transportation Engineering,1993,119(6):835-852.
[39]Pollatschek M A. Polus A., Livneh M. A decision model for gap acceptance and capacity at intersections [J], Transportation Research Part B,2002,36(7):649-663.
[40]Cassidy, M J. Anani etc. Study of freeway traffic near an off-ramp [J]. Transportation Research Part A.2002,36(6):563-572.
[41]Comert G. Cetin mecit. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research, In Press, Corrected Proof, Available online1July2008.
[42]邵长桥,荣建等.停车延误、引道延误和控制延误关系研究中国公路学报[J].2002.
[43]陈绍宽,郭谨一,王漩,毛保华.信号交叉口延误计算方法的比较[J].北京交通大学报,2005,29(3)：77-80.
[44]庄焰,曾文佳.信号交叉口延误计算模型研究[J].深圳大学学报,2006,23(4)：309-313.
[45]杨佩昆,黄文忠,车丕明.城市道路车队离散过程中的交通流模型[J].同济大学学报(自然科学版).1994(3)：294-299.
[46]Chen X M. Shao C F. Yue H. Influence of Bicycle Traffic on Capacity of Typical Signalized Intersection [J]. Tsinghua Science&Technology,2007,12(2):198-203.
[47]Chen Z.Q. Mao B.H. Liu M.J. Liu Z.L. Liang X. Modeling vehicles movement at signalized intersection [C]. Proceedings of the sixth International Conference on Traffic and Transportation Studies. USA,2008.653-668.
[48]S. H. Yang, D.H.Wang, B. Dong, and Y P.Wang. Modification of start-wave model at signalized intersection. Journal of Highway and Transportation Research and Development,2006, vol.23, no.1,130-134.
[49]D C Gazis, R Herman, and R B Potts. Car-following theory of steady-state traffic flow. Operations Research,1959, vol.7, no.4,499-505.
[50]D C Gazis, R. Herman, and R W Rothery, Follow-the-leader models of traffic flow, Operations Research,1961, vol.9, no.4,545-567.
[51]Peter Hides. A car-following model for urban traffic simulation [J]. Traffic Engineering and Control,1998,39(5):300-305.
[52]Cheu R L, Martinez J, and Duran C. A Cell Transmission Model with Lane Changing and Vehicle Tracking for Port of Entry Simulations [C]. Washington D.C. in The88th Annual Meeting of the Transportation Research Board.2008.
[53]Richards P I. Shock waves on the highway [J]. Operations Research,1956,4:42-51.
[54]Payne H J. Models of freeway traffic and control [C]. Bekey GA. Mathematical Methods of Public Systems,1971,1(1):51-61.
[55]Payne H J. FREFLO:A macroscopic simulation model of freeway traffic [J]. Transportation Research Record,1979,(772):68-77.
[56]Kuhne, R.D. Traffic Patterns in unstable Traffic Flow on Freeways [C]. Highway Capacity and Level of Service, Brannolte (ed.), Rotterdam,1991.
[57]Kerner B.S. Konhauser P. Cluster effect in initially homogeneous traffic flow [J]. Physics Review,1993,48(4):R2335-R2338.
[58]Kimber R M. The traffic capacity of roundabout [R]. TRRL report, LR942, Department of Environment, Department of Transport, UK,1980.
[59]Wolfram S. Theory and Applications of Cellular Automata [M]. Singapore: World Scientific Research,1986.
[60]Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic [J]. Journal de Physique I France,1992,2(12):2221-2229.
[61]Biham O, Middleton AA, Levine D. Self-organization and a dynamical transition in traffic-flow models [J]. Physical Review A,1992,46(10):86124-86127.
[62]Fukui M, Ishibashi Y. Traffic flow in ID cellular automaton model including cars moving with high speed [J]. Journal of the Physical Society of Japan,1996,65(6):1868-1870.
[63]王永明,周磊山,吕永波.基于弹性安全换道间距的元胞自动机交通流模型系统仿真学报[J],2008,20(5)：1159-1162.
[64]Gao L P, Liu M J, Sun Z Z, Mao B H. Simulation on impact of information guidance on regional traffic flow. Journal of Transportation Systems Engineering and Information Technology,2008,8(4),63-69.
[65]Jiang Rui, Wu Qing-song. The moving behavior of a large object in the crowds in a narrow channel [J]. Physical A,2006,364:457-463.
[66]杨蓓蓓,张小宁,孙立军.基于元胞传输模型的交通事件消散建模[J].重庆交通大学学报,2007,27(3)：4245.
[67]Bando M, Hasebe K, etc. Model of traffic congestion and numerical simulation [J]. Physical Review E,1995,51:1035-1042.
[68]Daganzo C F. The cell transmission model, part Ⅱ:network traffic [J]. Transpn. Res.1995,29B(2).
[69]Rascle M. An improved macroscopic model of traffic flow:Derivation and links with the Lighthill-Whitham model. Math. Comput. Model.2002(35):581-590.
[70]吴正.低速混合型城市交通的流体力学模型[J].力学学报,1994,26(2)：149-157.
[71]龙小强,晏启鹏.非机动车道对机动车道干扰的流体内摩擦模型[J].中国公路学报,2002,15(1)：100-102.
[72]隽志才,魏丽英,李江.信号交叉口排队长度宏观模拟的自适应分析法[J].中国公路学报,2000,13(1)：77-80.
[73]杨晓光,陈白磊,彭国雄.行人交通控制信号设置方法研究[J].中国公 路学报,2001(1)：73-7680.
[74]S Jin, Modeling of Car Following Behavior Considering Visual Attention Performance[D], Jilin university, JiLin, China,2010.
[75]P F Tao, Modeling of Driving Behavior Based on the Psychology Field Theory [D], Jilin university, JiLin, China,2012.
[76]Michael P G, Leeming F C, Dwyer, W O. Headway on urban streets: observational data and an intervention to decrease tailgating [J]. Transportation Research Part F,2000,3(2):55-64.
[77]Van der Horst D J. Lipid transport function of lipoproteins in flying insects [J]. Biochimica et Biophysica Acta (BBA)-Lipids and Lipid Metabolism,1990,1047(3):195-211.
[78]Wiedemann R, Reiter U. Microscopic traffic simulation:the simulation system:Mission, background and actual state[R]. Project ICARUS (V1052) Final Report,1992.
[79]Wim van Winsum. The human element in car following models [J]. Transportation Research Part F.1999:207-211.
[80]付坤.基于驾驶员与道路环境因素的驾驶行为差错数学分析[D]：吉林大学,2013.
[81]Vroom V H. Some personality determinants of the effects of participation [J]. The Journal of Abnormal and Social Psychology,1959,59(3):322.
[82]Manning W G. The logged dependent variable, heteroscedasticity, and the retransformation problem[J]. Journal of health economics,1998,17(3):283-295.
[83]赵炳强.驾驶员动态视觉特征及其影响[J].公路交通科技.1998.05.Vo1.15.Supl(1)：10-13.
[84]Wiedemann R, Reiter U. Microscopic traffic simulation:the simulation system:Mission, background and actual state [R]. Project ICARUS (V1052) FinalReport，1992.
[85]P G Gipps. A Model for the structure of lane-changing decisions [J]. Transportation Research Part B.1986:403-414.
[86]邹智军,杨东援.微观交通仿真中的车道变换模型[J],中国公路学报.2002，15(2)：105-108.
[87]Bando M, Hasebe K, etc. Model of traffic congestion and numerical simulation [J]. Physical Review E,1995,51:1035-1042.
[88]Helbing D. Traffic and related self-driven many-particle systems [J]. Reciew of Modern Physics.2001,73(4):1067-1141.
[89]Helbing D, Tilch B. Generalized force model of traffic dynamics [J]. Physical Review E,1998,58(1):133-138.
[90]Jiang R, Wu Q S, Zhu Z J. Full velocity difference model for a car-following theory [J]. Physical Review E,2001,64(1):017101.
[91]李珊珊,平交路口机动车自行车行人及其相互干扰微观行为模型研究 [D].北京交通大学.2013.
[92]景春光,曲大义,梁春岩.两相位交叉口机非冲突对机动车饱和流率的影响[J].公路交通科技.2007(08)：124-127.
[93]刘明君.基于混合交通流的信号交叉口机动车车头时距研究[D].北京交通大学,2010.
[94]Bang K. Carlsson A. and Palgunadi. Development of Speed-Flow Relationships for Indonesian Rural Roads Using Empirical Data and Simulation. Transportation Research Board,74th Annual Meeting, Washington DC.
[95]臧晓冬,汤远红等.混合交通侧向干扰模型分析[J].交通科技与经济.2002，2(3)：54-55.
[96]李珊珊,平交路口机动车自行车行人及其相互干扰微观行为模型研究[D].北京交通大学.2013.
[97]龙小强,晏启鹏.非机动车道对机动车道干扰的流体内摩擦模型[J].中国公路学报.2002,15(1)：100-102.
[98]安维胜.混合交通流动力学建模研究[D].四川：西南交通大学.2010.
[99]罗霞,杜进有,陈应文.混合交通流特性分析[J].西南交通大学学报.2000,297-300.
[100]Nelson P. Sopasakis A. The Prigogine-Herman kinetic model predicts widely scattered traffic flow data at high concentrations. Transpn. Res.1998(32):589-604.
[101]M R Ibrahim, M R Karim and F A Kidwai. The Effect of Digital Count-Down Display on Signalized Junction Performance [J]. American Journal of Applied Sciences2008,5(5):479-482.
[102]王岩,杨晓光.基于交通安全的交叉口倒计时信号灯设置研究[J].中国安全科学学报.2006(03)：55-59.
[103]Mahalel D, Zaidel D. Klein T. Driver's decision process on termination of the green light. Accident Analysis&Prevention.1985.17(5),373-380.
[104]Mussa R N, Newton C J, Matthias J S, Sadalla E K, Burns E K. Simulator evaluation of green and flashing amber signal. Transportation Research Record1550.1996.23-29.
[105]Newton C, Mussa R N, Sadalla E K, Burns E K, Matthias J S. Evaluation of an alternative traffic light change anticipation system. Accident Analysis.1997.
[106]吴文静,隽志才,贾洪飞.倒计时信号交叉口处的驾驶员行为决策[J].系统工程理论与实践,2009(007)：160-165.
[107]龙科军,何林儒,韩立.黄灯期间信号交叉口的驾驶员行为[J].系统工程.2010.12.28(12)：117-120.
[108]王秀良,乔木.十字路口黄灯时间及困境区域的数学模型研究[J].武汉理工大学学报(交通科学与工程版),2011(5)：117-120.
[109]May A D. Traffic Flow Fundamentals [M]. New Jersey:Prentiee-Hall, Inc,1990.
[110]Vlahogianni E I., Jr.Webber C L., etc. Statistical characteristics of transitional queue conditions in signalized arterials [J]. Transportation Research Part C,2007,15(6):392-03.
[111]曲昭伟,王殿海,姚荣涵.信号交叉口起动波的运动学模型[J].吉林大学学报(工学版).2008(2)：268-272.
[2] Edie L C. Car-following and steady-state theory for noncongested traffic[J].Oper. Res.1961,9(1):66-76.
[3] Bando M., Hasebe K, etc. Model of traffic congestion and numericalsimulation [J]. Physical Review E,1995,51:1035-1042.
[4]汪秉宏,邝乐琪,许伯铭.高速公路交通流元胞自动机模型的一种统计平均解耦处理[J].物理学报,1998，47(6):906-915.
[5] May A D. Traffic Flow Fundamentals [M]. New Jersey: Prentiee-Hall,Inc,1990.
[6] Vlahogianni E I. Jr.Webber C.L. etc. Statistical characteristics of transitionalqueue conditions in signalized arterials [J]. Transportation Research Part C,2007,15(6):392-03.
[7]曲昭伟,刘诗序,王殿海等.模拟电路的信号交叉口交通流模型[J].吉林大学学报(工学版),2008(S1):49-52.
[8]王殿海,赵志宏.模拟电路系统研究网络交通流特性的思想与方法[J].系统工程理论与实践,2002(9):107-111.
[9] Pacey G M. The progress of a bunch of vehicles released from a trafficsignal.RRL Note, Transport and Road Research Laboratory [J]. Growthorne, UK,1956. No. RN/2665/GMP.
[10] Roberston D I. Transyt: A traffic network study tool [J]. RRL Report,No.LR253, Transport and Road Research Laboratory, Growthome, UK,1969.
[11] Al-ghamdi A S. Entering headway for through movements at urbansignalized intersections [J]. Ttrasportation Research record,1999, No.1967,42-47.
[12] Thirayoot Limanond, Suebpong Chookerd, Natcha Roubtonglang. Effects ofcountdown timers on queue discharge characteristics of through movement at asignalized intersection[J]. Transportation Research Part C.2009,17(6):662-671.
[13]邵长桥,杜晓辉,李光芹.信号交叉口排队离散车头时距统计分析[J].公路交通科技,2003,20（4）:76-79.
[14]钱大琳,蒋海峰等.信号交叉口混合交通流干扰影响及其计算方法研究[J].交通运输系统工程与信息.2006,6(3):75-78.
[15] Stokes, R. W. Capacities of triple left-turn lanes [C]. Rep. to Institute ofTransportation Engineers Technical Council Committee5P-5A., Washington, D.C.1995.
[16] Tarko, A P., and Perez-Cartagena, R. I. Calibration of capacity parametersfor signalized intersections in Indiana [J]. J. Transp. Eng.,2005,131(12),904-911.
[17]王炜,过秀成,等编著.交通工程学[M].南京:东南大学出版社.2000.
[18]郭冠英.用集散波法计算道路交通拥塞长度[J].上海公路,1997(2):39-41.
[19] Greenshields B D. A Study in Highway Capacity [C]. Highway Research Board, Proceedings,1935(14):448-477.
[20]Greenberg H. An analysis of traffic flow [J]. Operations Research.1959(7):78-85.
[21]Webster F.V. Traffic signal settings [J]. Road Research Laboratory Technical Paper, HMSO, London,1958. No.39.
[22]Stephanopoulos G, Michalopoulos P., Modeling and analysis of traffic queue dynamics at signalized intersections [J]. Transportation Research A,1979,13(5):295-307.
[23]Brilon W, Wu N. Delays at fixed-time traffic signals under time dependent traffic conditions [J]. Traffic Engineering and Control,1990,31(12):23-63.
[24]May A.D. Traffic Flow Fundamentals [M]. New Jersey:Prentiee-Hall, Inc,1990.
[25]Vlahogianni E.I., Jr. Webber C.L., etc. Statistical characteristics of transitional queue conditions in signalized arterials [J] Transportation Research Part C,2007,15(6):392-03.
[26]Heidemann D. Queue length and delay distributions at traffic signals [J]. Transportation Research Part B,1994,28(5):377-389.
[27]Heidemann D. Queue length and waiting-time distributions at priority intersections [J]. Transportation Research Part B,1991,25(4):163-174.
[28]Songchitruksa P. Hard E.N. Queuing simulation of roadside survey station: blocked traffic lane [J]. Trasportation Research Part A,2008,42(6):857-873.
[29]Comert G, Cetin mecit. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research,2008.7.384-396.
[30]张亚平,李硕.信号交叉口车辆集结与消散分析[J].长沙交通学院学报,1999,15(3)：57-61.
[31]王殿海,景春光,曲昭伟.交通波理论在交叉口交通流分析中的应用[J].中国公路学报,2002,15(1)：93-96.
[32]韩凤春,刘东,曹金璇,马社强.城市交叉口混合交通流特征及提高通行能力对策研究[J].中国人民公安大学学报(自然科学版),2004.2,Total No.40,93-96.
[33]徐良杰,王炜.信号交叉口行人过街时间模型[J].交通运输工程学报,2005,5(1)：111-115.
[34]姚荣涵.车辆排队模型研究.吉林：吉林大学博士学位论文[D],2007.
[35]Webster F.V. Traffic signal settings [J]. Road Research Laboratory Technical Paper, HMSO, London,1958. No.39.
[36]Akcelik R. Time-dependent expressions for delay, stop rate and queue length at traffic signals [R]. International Report AIR, Australian Road Research Board, Vermont South,367-11980.
[37]Akcelik R. The highway capacity manual:delay formula for signalized intersection ITE Journal [M].1988,58(3):23-27.
[38]Olszewski P. Overall Delay, Stopped Delay, and Stops at Signalized Intersections [J]. Journal of Transportation Engineering,1993,119(6):835-852.
[39]Pollatschek M A. Polus A., Livneh M. A decision model for gap acceptance and capacity at intersections [J], Transportation Research Part B,2002,36(7):649-663.
[40]Cassidy, M J. Anani etc. Study of freeway traffic near an off-ramp [J]. Transportation Research Part A.2002,36(6):563-572.
[41]Comert G. Cetin mecit. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research, In Press, Corrected Proof, Available online1July2008.
[42]邵长桥,荣建等.停车延误、引道延误和控制延误关系研究中国公路学报[J].2002.
[43]陈绍宽,郭谨一,王漩,毛保华.信号交叉口延误计算方法的比较[J].北京交通大学报,2005,29(3)：77-80.
[44]庄焰,曾文佳.信号交叉口延误计算模型研究[J].深圳大学学报,2006,23(4)：309-313.
[45]杨佩昆,黄文忠,车丕明.城市道路车队离散过程中的交通流模型[J].同济大学学报(自然科学版).1994(3)：294-299.
[46]Chen X M. Shao C F. Yue H. Influence of Bicycle Traffic on Capacity of Typical Signalized Intersection [J]. Tsinghua Science&Technology,2007,12(2):198-203.
[47]Chen Z.Q. Mao B.H. Liu M.J. Liu Z.L. Liang X. Modeling vehicles movement at signalized intersection [C]. Proceedings of the sixth International Conference on Traffic and Transportation Studies. USA,2008.653-668.
[48]S. H. Yang, D.H.Wang, B. Dong, and Y P.Wang. Modification of start-wave model at signalized intersection. Journal of Highway and Transportation Research and Development,2006, vol.23, no.1,130-134.
[49]D C Gazis, R Herman, and R B Potts. Car-following theory of steady-state traffic flow. Operations Research,1959, vol.7, no.4,499-505.
[50]D C Gazis, R. Herman, and R W Rothery, Follow-the-leader models of traffic flow, Operations Research,1961, vol.9, no.4,545-567.
[51]Peter Hides. A car-following model for urban traffic simulation [J]. Traffic Engineering and Control,1998,39(5):300-305.
[52]Cheu R L, Martinez J, and Duran C. A Cell Transmission Model with Lane Changing and Vehicle Tracking for Port of Entry Simulations [C]. Washington D.C. in The88th Annual Meeting of the Transportation Research Board.2008.
[53]Richards P I. Shock waves on the highway [J]. Operations Research,1956,4:42-51.
[54]Payne H J. Models of freeway traffic and control [C]. Bekey GA. Mathematical Methods of Public Systems,1971,1(1):51-61.
[55]Payne H J. FREFLO:A macroscopic simulation model of freeway traffic [J]. Transportation Research Record,1979,(772):68-77.
[56]Kuhne, R.D. Traffic Patterns in unstable Traffic Flow on Freeways [C]. Highway Capacity and Level of Service, Brannolte (ed.), Rotterdam,1991.
[57]Kerner B.S. Konhauser P. Cluster effect in initially homogeneous traffic flow [J]. Physics Review,1993,48(4):R2335-R2338.
[58]Kimber R M. The traffic capacity of roundabout [R]. TRRL report, LR942, Department of Environment, Department of Transport, UK,1980.
[59]Wolfram S. Theory and Applications of Cellular Automata [M]. Singapore: World Scientific Research,1986.
[60]Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic [J]. Journal de Physique I France,1992,2(12):2221-2229.
[61]Biham O, Middleton AA, Levine D. Self-organization and a dynamical transition in traffic-flow models [J]. Physical Review A,1992,46(10):86124-86127.
[62]Fukui M, Ishibashi Y. Traffic flow in ID cellular automaton model including cars moving with high speed [J]. Journal of the Physical Society of Japan,1996,65(6):1868-1870.
[63]王永明,周磊山,吕永波.基于弹性安全换道间距的元胞自动机交通流模型系统仿真学报[J],2008,20(5)：1159-1162.
[64]Gao L P, Liu M J, Sun Z Z, Mao B H. Simulation on impact of information guidance on regional traffic flow. Journal of Transportation Systems Engineering and Information Technology,2008,8(4),63-69.
[65]Jiang Rui, Wu Qing-song. The moving behavior of a large object in the crowds in a narrow channel [J]. Physical A,2006,364:457-463.
[66]杨蓓蓓,张小宁,孙立军.基于元胞传输模型的交通事件消散建模[J].重庆交通大学学报,2007,27(3)：4245.
[67]Bando M, Hasebe K, etc. Model of traffic congestion and numerical simulation [J]. Physical Review E,1995,51:1035-1042.
[68]Daganzo C F. The cell transmission model, part Ⅱ:network traffic [J]. Transpn. Res.1995,29B(2).
[69]Rascle M. An improved macroscopic model of traffic flow:Derivation and links with the Lighthill-Whitham model. Math. Comput. Model.2002(35):581-590.
[70]吴正.低速混合型城市交通的流体力学模型[J].力学学报,1994,26(2)：149-157.
[71]龙小强,晏启鹏.非机动车道对机动车道干扰的流体内摩擦模型[J].中国公路学报,2002,15(1)：100-102.
[72]隽志才,魏丽英,李江.信号交叉口排队长度宏观模拟的自适应分析法[J].中国公路学报,2000,13(1)：77-80.
[73]杨晓光,陈白磊,彭国雄.行人交通控制信号设置方法研究[J].中国公 路学报,2001(1)：73-7680.
[74]S Jin, Modeling of Car Following Behavior Considering Visual Attention Performance[D], Jilin university, JiLin, China,2010.
[75]P F Tao, Modeling of Driving Behavior Based on the Psychology Field Theory [D], Jilin university, JiLin, China,2012.
[76]Michael P G, Leeming F C, Dwyer, W O. Headway on urban streets: observational data and an intervention to decrease tailgating [J]. Transportation Research Part F,2000,3(2):55-64.
[77]Van der Horst D J. Lipid transport function of lipoproteins in flying insects [J]. Biochimica et Biophysica Acta (BBA)-Lipids and Lipid Metabolism,1990,1047(3):195-211.
[78]Wiedemann R, Reiter U. Microscopic traffic simulation:the simulation system:Mission, background and actual state[R]. Project ICARUS (V1052) Final Report,1992.
[79]Wim van Winsum. The human element in car following models [J]. Transportation Research Part F.1999:207-211.
[80]付坤.基于驾驶员与道路环境因素的驾驶行为差错数学分析[D]：吉林大学,2013.
[81]Vroom V H. Some personality determinants of the effects of participation [J]. The Journal of Abnormal and Social Psychology,1959,59(3):322.
[82]Manning W G. The logged dependent variable, heteroscedasticity, and the retransformation problem[J]. Journal of health economics,1998,17(3):283-295.
[83]赵炳强.驾驶员动态视觉特征及其影响[J].公路交通科技.1998.05.Vo1.15.Supl(1)：10-13.
[84]Wiedemann R, Reiter U. Microscopic traffic simulation:the simulation system:Mission, background and actual state [R]. Project ICARUS (V1052) FinalReport，1992.
[85]P G Gipps. A Model for the structure of lane-changing decisions [J]. Transportation Research Part B.1986:403-414.
[86]邹智军,杨东援.微观交通仿真中的车道变换模型[J],中国公路学报.2002，15(2)：105-108.
[87]Bando M, Hasebe K, etc. Model of traffic congestion and numerical simulation [J]. Physical Review E,1995,51:1035-1042.
[88]Helbing D. Traffic and related self-driven many-particle systems [J]. Reciew of Modern Physics.2001,73(4):1067-1141.
[89]Helbing D, Tilch B. Generalized force model of traffic dynamics [J]. Physical Review E,1998,58(1):133-138.
[90]Jiang R, Wu Q S, Zhu Z J. Full velocity difference model for a car-following theory [J]. Physical Review E,2001,64(1):017101.
[91]李珊珊,平交路口机动车自行车行人及其相互干扰微观行为模型研究 [D].北京交通大学.2013.
[92]景春光,曲大义,梁春岩.两相位交叉口机非冲突对机动车饱和流率的影响[J].公路交通科技.2007(08)：124-127.
[93]刘明君.基于混合交通流的信号交叉口机动车车头时距研究[D].北京交通大学,2010.
[94]Bang K. Carlsson A. and Palgunadi. Development of Speed-Flow Relationships for Indonesian Rural Roads Using Empirical Data and Simulation. Transportation Research Board,74th Annual Meeting, Washington DC.
[95]臧晓冬,汤远红等.混合交通侧向干扰模型分析[J].交通科技与经济.2002，2(3)：54-55.
[96]李珊珊,平交路口机动车自行车行人及其相互干扰微观行为模型研究[D].北京交通大学.2013.
[97]龙小强,晏启鹏.非机动车道对机动车道干扰的流体内摩擦模型[J].中国公路学报.2002,15(1)：100-102.
[98]安维胜.混合交通流动力学建模研究[D].四川：西南交通大学.2010.
[99]罗霞,杜进有,陈应文.混合交通流特性分析[J].西南交通大学学报.2000,297-300.
[100]Nelson P. Sopasakis A. The Prigogine-Herman kinetic model predicts widely scattered traffic flow data at high concentrations. Transpn. Res.1998(32):589-604.
[101]M R Ibrahim, M R Karim and F A Kidwai. The Effect of Digital Count-Down Display on Signalized Junction Performance [J]. American Journal of Applied Sciences2008,5(5):479-482.
[102]王岩,杨晓光.基于交通安全的交叉口倒计时信号灯设置研究[J].中国安全科学学报.2006(03)：55-59.
[103]Mahalel D, Zaidel D. Klein T. Driver's decision process on termination of the green light. Accident Analysis&Prevention.1985.17(5),373-380.
[104]Mussa R N, Newton C J, Matthias J S, Sadalla E K, Burns E K. Simulator evaluation of green and flashing amber signal. Transportation Research Record1550.1996.23-29.
[105]Newton C, Mussa R N, Sadalla E K, Burns E K, Matthias J S. Evaluation of an alternative traffic light change anticipation system. Accident Analysis.1997.
[106]吴文静,隽志才,贾洪飞.倒计时信号交叉口处的驾驶员行为决策[J].系统工程理论与实践,2009(007)：160-165.
[107]龙科军,何林儒,韩立.黄灯期间信号交叉口的驾驶员行为[J].系统工程.2010.12.28(12)：117-120.
[108]王秀良,乔木.十字路口黄灯时间及困境区域的数学模型研究[J].武汉理工大学学报(交通科学与工程版),2011(5)：117-120.
[109]May A D. Traffic Flow Fundamentals [M]. New Jersey:Prentiee-Hall, Inc,1990.
[110]Vlahogianni E I., Jr.Webber C L., etc. Statistical characteristics of transitional queue conditions in signalized arterials [J]. Transportation Research Part C,2007,15(6):392-03.
[111]曲昭伟,王殿海,姚荣涵.信号交叉口起动波的运动学模型[J].吉林大学学报(工学版).2008(2)：268-272.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |