多线路公交车站能力计算方法研究
|
摘要
城市公共交通系统是重要的城市基础设施,是关系国计民生的社会公共事业。优先发展城市公共交通,不仅是缓解城市交通拥堵的有效措施,也是改善城市居住环境,促进城市可持续发展的必然要求。公交汽车作为常规公共交通方式,具有投资少、运行灵活、覆盖面广等特点,在未来相当长一段时间内仍是城市公共交通的主体。公交车站是城市公交网络中最重要的交通基础设施之一,也是最基本的交通瓶颈所在,是各种交通问题集中的地方。对公交车站的车辆行为进行深入分析,并在此基础上建立符合我国国情的车站能力计算方法体系,不仅具有非常重要的理论意义,也是十分迫切的现实需求。
大城市中心区的公交车站具有停靠线路多、车辆运行准时性差、停靠时间波动大等特点。美国道路通行能力手册推荐的车站能力计算方法,没有充分考虑到公交车辆到达的随机性,对停靠的波动性处理又过于理想化；有些学者采用的随机服务系统方法与公交车辆排队进出车站的实际情况有差异；多停靠位的车站能力计算方法一般采用简单的累计有效停靠位来体现停靠位的不完全利用问题,难以体现不同车站不同运行状态的差异及车站内公交车辆的相互影响。有鉴于此,本文根据我国城市地区公交车站的实际运行情况,考虑了公交车辆到达以及停靠时间的随机分布问题,构建了基于服务水平的车站能力计算模型,并扩展到多停靠位车站。主要工作和结论包括：
(1)在分析国内外公交车站能力研究现状的基础上,探讨了理论计算方法、随机服务系统方法、饱和车头时距方法、统计回归方法及仿真等方法的计算原理,总结了各种方法的优缺点和适用情形,指出现有研究存在的问题,并分析了公交车站能力“量”与“质”的双重属性。
(2)从城市客流分布以及土地资源利用的角度,分析了大城市中心区车站设置的特征和发展趋势,多线路共用站已成为普遍采用的车站形式。以北京地区的公交车站为实例,研究了多线路共用站在实际应用中存在的问题,指出能力估计过高导致的车站排队是最普遍,也是最根本的问题。从车站形式及内部设计、公交车辆外形与性能、乘客乘降及候车、车站周边交通环境四方面,分析了车站能力的影响因素。
(3)构建了基于服务水平、考虑公交车辆到达分布和停靠时间分布的单停靠位公交车站能力计算模型。调查数据表明,单位时间到达车站的公交车辆数量服从泊松分布,公交车辆的停靠时间服从负指数分布或k阶爱尔朗分布(k为自然数),根据k值的不同,停靠时间呈现不同的分布状态,k值越大,分布的随机性越小。选取排队概率作为服务水平的衡量指标,在到达服从泊松分布的基础上,分别建立了停靠时间服从负指数分布和k阶爱尔朗分布的单停靠位车站能力计算模型。通过算例分析,得到车站能力随设计服务水平的升高而降低,随停靠时间的随机性降低而升高的主要结论,并且k≤15,特别是k≤5的范围内,k值对车站能力的影响最为显著。
(4)以单停靠位车站能力计算模型为基础,通过研究公交车辆在车站范围内的微观行为,分别建立了出站排队时间模型、空置时间模型、运营裕量模型,共同构成两停靠位车站能力的计算模型。通过算例分析了车站能力各个计算因素在不同的停靠时间分布随机程度下的变化情况,运营裕量和车站能力与排队概率的整体关系,不同的服务水平对应的运营裕量ts与车站能力Cs的具体变化情况。
(5)对三停靠位公交车站的能力计算模型进行了探索性研究,根据事件发生的情形和概率,构建不同情形下的出站排队时间计算模型,进而得到平均出站排队时间的计算模型。通过算例得到3号停靠位公交车辆的出站排队时间tcp3随交通强度的增加而增加,且随平均停靠时间的升高而整体水平上升的结论。
Public transport system is the basic infrastructure in city, and also the social commonweal concerning the national economy and the people's livelihood. Transit priority policies are not only the effective measures that release traffic jam, but also the demand of city's sustainable development. The traditional transit mode (in fact, bus) is occupying the main part of transport in a long time for the advantage of low energy and land cost, flexible operation and large coverage of network. As the nodes of transit network, bus stops are the basic facilities of bus service, also the bottleneck of traffic where a lot of traffic problems happen. Therefore, it has great theoretical significance and real world demand to built capacity calculation method basing on the real situation in China after an in-depth analysis on the vehicle behavior around and inside bus stops.
Bus stops in urban area of big cities have several vivid characteristics, which include large number of bus lines, poor punctuality, and strong fluctuation of dwell time. The classic bus stop capacity calculation formula presented by HCM (Highway Capacity Manual, HCM) didn't fully considering the bus arriving and dwelling random, for this, some researcher used the stochastic service method to calculate bus stop capacity. However, the actual bus in-and-out rule can not be followed in stochastic service method. Moreover, for multi-berth bus stop, the existing models only introduce an effective berth number to show the effect of incomplete use of the berths in the capacity calculation formula, but the real situation is complicated and varied among different bus stops and different periods in the same stop, so the effective berth number is too simple and inflexible to describe the variation of capacity. Considering the disadvantage of existing methods, this dissertation develops a novel method for bus stop capacity calculation that based on the recognition and discrimination of random bus arriving time, random dwelling time and in-and-out-of-berth rule which are the facts in the operation of bus stop in urban area of big cities. Main works of this dissertation are summarized as below:
(1) Introduction on the previous studies of the bus stop capacity calculation methods and discussion on the advantage and disadvantage of these methods, which include theoretical calculation method, stochastic service method, saturated headway method, statistical regression method, and simulation method. As a production, the unsuitability of these methods on the capacity calculation of bus stops in urban area is summarized and the quantity and quality of bus stop capacity are analyzed.
(2) Analysis on the characteristics and trends of bus stops setting in urban area of big cities, from aspects of passenger flow distribution and land source using. As a conclusion of the analysis, the multi-lines design (there are more than one line that dwelling on the bus stop) is widely used and will be the trend in future. The practical problems happening in multi-lines stop are figured out from the real cases in the city of Beijing, and the overestimation on capacity is found to be the most fundamental and common problem. Moreover, this dissertation is analyzing the influencing factors of capacity from four aspects, including bus stop setting and interior design, bus properties and operation, passenger loading-and-unloading and arriving characteristics, and traffic surrounding.
(3) Development of a novel method for capacity analysis and estimation, based on the bus arrival and dwell time distribution, as well as the designed service level. As known from the observed data, bus arrival in unit time follows Poisson distribution, and dwell time follows either negative exponential distribution or k-order Erlang distribution. The order k presents the random level of dwell time, and the bigger is k, the lower is the random level. While queue rate is selected as the measure index, and arrival distribution is set to be Poisson, the calculation models of bus stop capacity is developed separately for dwell time following negative exponential distribution and k-order Erlang distribution. As the conclusion of case study, the capacity is decreasing with the elevation of designed service level and dwell time random, furthermore when in the range of k≦ 15 especially k≦ 5, k has great effect on the capacity.
(4) Development of a novel method on the two-berth bus stop capacity calculation. Deriving from the method proposed in anterior chapter, three sub-models, including queuing-to-out time sub-model, idle time sub-model and operating margin sub-model, have been established to constitute the capacity calculation model, basing on analysis about the microscopic behaviors of bus in the bus stop. From the results of case study, the effects of dwell time random level on the capacity calculation factors, the general relation between operating margin as well as capacity and queue rate, and the trend of operating margin and capacity for different service level, are analyzed.
(5) Exploratory research on the three-berth bus stop capacity calculation. After situation and possibility analysis, this chapter models the queue-to-out time under different condition, then gets the average queue time model. As the conclusion of case study, the average queuing time is increasing with the elevation of traffic density and the average dwell time.
大城市中心区的公交车站具有停靠线路多、车辆运行准时性差、停靠时间波动大等特点。美国道路通行能力手册推荐的车站能力计算方法,没有充分考虑到公交车辆到达的随机性,对停靠的波动性处理又过于理想化；有些学者采用的随机服务系统方法与公交车辆排队进出车站的实际情况有差异；多停靠位的车站能力计算方法一般采用简单的累计有效停靠位来体现停靠位的不完全利用问题,难以体现不同车站不同运行状态的差异及车站内公交车辆的相互影响。有鉴于此,本文根据我国城市地区公交车站的实际运行情况,考虑了公交车辆到达以及停靠时间的随机分布问题,构建了基于服务水平的车站能力计算模型,并扩展到多停靠位车站。主要工作和结论包括：
(1)在分析国内外公交车站能力研究现状的基础上,探讨了理论计算方法、随机服务系统方法、饱和车头时距方法、统计回归方法及仿真等方法的计算原理,总结了各种方法的优缺点和适用情形,指出现有研究存在的问题,并分析了公交车站能力“量”与“质”的双重属性。
(2)从城市客流分布以及土地资源利用的角度,分析了大城市中心区车站设置的特征和发展趋势,多线路共用站已成为普遍采用的车站形式。以北京地区的公交车站为实例,研究了多线路共用站在实际应用中存在的问题,指出能力估计过高导致的车站排队是最普遍,也是最根本的问题。从车站形式及内部设计、公交车辆外形与性能、乘客乘降及候车、车站周边交通环境四方面,分析了车站能力的影响因素。
(3)构建了基于服务水平、考虑公交车辆到达分布和停靠时间分布的单停靠位公交车站能力计算模型。调查数据表明,单位时间到达车站的公交车辆数量服从泊松分布,公交车辆的停靠时间服从负指数分布或k阶爱尔朗分布(k为自然数),根据k值的不同,停靠时间呈现不同的分布状态,k值越大,分布的随机性越小。选取排队概率作为服务水平的衡量指标,在到达服从泊松分布的基础上,分别建立了停靠时间服从负指数分布和k阶爱尔朗分布的单停靠位车站能力计算模型。通过算例分析,得到车站能力随设计服务水平的升高而降低,随停靠时间的随机性降低而升高的主要结论,并且k≤15,特别是k≤5的范围内,k值对车站能力的影响最为显著。
(4)以单停靠位车站能力计算模型为基础,通过研究公交车辆在车站范围内的微观行为,分别建立了出站排队时间模型、空置时间模型、运营裕量模型,共同构成两停靠位车站能力的计算模型。通过算例分析了车站能力各个计算因素在不同的停靠时间分布随机程度下的变化情况,运营裕量和车站能力与排队概率的整体关系,不同的服务水平对应的运营裕量ts与车站能力Cs的具体变化情况。
(5)对三停靠位公交车站的能力计算模型进行了探索性研究,根据事件发生的情形和概率,构建不同情形下的出站排队时间计算模型,进而得到平均出站排队时间的计算模型。通过算例得到3号停靠位公交车辆的出站排队时间tcp3随交通强度的增加而增加,且随平均停靠时间的升高而整体水平上升的结论。
Public transport system is the basic infrastructure in city, and also the social commonweal concerning the national economy and the people's livelihood. Transit priority policies are not only the effective measures that release traffic jam, but also the demand of city's sustainable development. The traditional transit mode (in fact, bus) is occupying the main part of transport in a long time for the advantage of low energy and land cost, flexible operation and large coverage of network. As the nodes of transit network, bus stops are the basic facilities of bus service, also the bottleneck of traffic where a lot of traffic problems happen. Therefore, it has great theoretical significance and real world demand to built capacity calculation method basing on the real situation in China after an in-depth analysis on the vehicle behavior around and inside bus stops.
Bus stops in urban area of big cities have several vivid characteristics, which include large number of bus lines, poor punctuality, and strong fluctuation of dwell time. The classic bus stop capacity calculation formula presented by HCM (Highway Capacity Manual, HCM) didn't fully considering the bus arriving and dwelling random, for this, some researcher used the stochastic service method to calculate bus stop capacity. However, the actual bus in-and-out rule can not be followed in stochastic service method. Moreover, for multi-berth bus stop, the existing models only introduce an effective berth number to show the effect of incomplete use of the berths in the capacity calculation formula, but the real situation is complicated and varied among different bus stops and different periods in the same stop, so the effective berth number is too simple and inflexible to describe the variation of capacity. Considering the disadvantage of existing methods, this dissertation develops a novel method for bus stop capacity calculation that based on the recognition and discrimination of random bus arriving time, random dwelling time and in-and-out-of-berth rule which are the facts in the operation of bus stop in urban area of big cities. Main works of this dissertation are summarized as below:
(1) Introduction on the previous studies of the bus stop capacity calculation methods and discussion on the advantage and disadvantage of these methods, which include theoretical calculation method, stochastic service method, saturated headway method, statistical regression method, and simulation method. As a production, the unsuitability of these methods on the capacity calculation of bus stops in urban area is summarized and the quantity and quality of bus stop capacity are analyzed.
(2) Analysis on the characteristics and trends of bus stops setting in urban area of big cities, from aspects of passenger flow distribution and land source using. As a conclusion of the analysis, the multi-lines design (there are more than one line that dwelling on the bus stop) is widely used and will be the trend in future. The practical problems happening in multi-lines stop are figured out from the real cases in the city of Beijing, and the overestimation on capacity is found to be the most fundamental and common problem. Moreover, this dissertation is analyzing the influencing factors of capacity from four aspects, including bus stop setting and interior design, bus properties and operation, passenger loading-and-unloading and arriving characteristics, and traffic surrounding.
(3) Development of a novel method for capacity analysis and estimation, based on the bus arrival and dwell time distribution, as well as the designed service level. As known from the observed data, bus arrival in unit time follows Poisson distribution, and dwell time follows either negative exponential distribution or k-order Erlang distribution. The order k presents the random level of dwell time, and the bigger is k, the lower is the random level. While queue rate is selected as the measure index, and arrival distribution is set to be Poisson, the calculation models of bus stop capacity is developed separately for dwell time following negative exponential distribution and k-order Erlang distribution. As the conclusion of case study, the capacity is decreasing with the elevation of designed service level and dwell time random, furthermore when in the range of k≦ 15 especially k≦ 5, k has great effect on the capacity.
(4) Development of a novel method on the two-berth bus stop capacity calculation. Deriving from the method proposed in anterior chapter, three sub-models, including queuing-to-out time sub-model, idle time sub-model and operating margin sub-model, have been established to constitute the capacity calculation model, basing on analysis about the microscopic behaviors of bus in the bus stop. From the results of case study, the effects of dwell time random level on the capacity calculation factors, the general relation between operating margin as well as capacity and queue rate, and the trend of operating margin and capacity for different service level, are analyzed.
(5) Exploratory research on the three-berth bus stop capacity calculation. After situation and possibility analysis, this chapter models the queue-to-out time under different condition, then gets the average queue time model. As the conclusion of case study, the average queuing time is increasing with the elevation of traffic density and the average dwell time.
引文
[1]Adebisi O. A mathematical model for headway variance of fixed-route buses[J]. Transportation Research Part B:Methodological,1986,20(1):59-70.
[2]Andrzej A. Probabilistic Models of Passengers Service Processes at Bus Stops[J], Transportation Research Part B:Methodological,1992,26(4):253-259.
[3]Banks H. J., Introduction to Traffic Engineering 2nd ed[M]. McGraw-Hill series in transportation, McGraw-Hill companies, Inc.,2002
[4]Bernick M., et al. Transit-Based Development in the United States:A Review of Recent Experiences[R]. University of California at Berkeley, Institute of Urban andRegional Development, Berkeley, California,1994.
[5]Bernick M., Cervero R. Transit Villages for the 21st Century [M]. New York, McGraw Hill,1996.
[6]Boarnet M., Crane R.B. Public Finance and Transit-Oriented Planning:New Evidence from Southern California [J]. Journal of Planning Education and Research,1998,17:206-219.
[7]Box P. C. The Location and Design of Bus Transfer Facilities[C]. Institute of Transportation Engineers, Technical Council Committee 5C-1A, Washington, DC,1992.
[8]Bus Transfer Center Study. Statewide Transit-Oriented Development Study: Factors for Success in California[R]. Working Paper, Project for Public Spaces, Inc. Publication. California Department of Transportation,2002:8-2.
[9]Cervero R. Transit-Based Housing in California:Evidence on Ridership Impacts [J]. Transport Policy,1994(3):174-183.
[10]Cervero R., Mark D., An Assessment of Suburban Targeted Transit Service Strategies in the United States[R]. University of California, Transportation Center, Berkeley, California,1993.
[11]Chen X. M., Yu L., Zhang Y. S., Guo J. F. Analyzing urban bus service reliability at the stop, route, and network levels [J]. Transportation Research Part A:Policy and Practice,2009,43(8):722-734.
[12]Chen Y. Z., Li N., He D. R., A study on some urban bus transport networks [J]. Physica A:Statistical Mechanics and its Applications,2007,376(15):747-754.
[13]Daganzo C. F. A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons. Transportation Research Part B,2009, 43(10):913-921.
[14]Daniel J., Konon W. Effectiveness of Bus Bulbs for Bus Stops-Final Report[R]. 2005(1).http://transportation.njit.edu/nctip/research/ResRep.asp?status =Completed&proj ectNo= 111&grantNumber=992530
[15]Davison L. J., Knowles D. R. Bus quality partnerships, modal shift and traffic decongestion [J]. Journal of Transport Geography,2006,14(3):177-194.
[16]Dejeammes M., Coffin F. Bus Stop Design and Automated Guidance for Low-floor Buses[C]. Transportation Research Record, Nation Research Council. Washington D.C.1999:85-91.
[17]Demetsky J. M., et al. Bus Stop Loacation and Design [J]. Journal of Transportation Engineering,1982.7:313-327.
[18]Dessouky M., Hall R., Nowroozi A., Mourikas K. Bus dispatching at timed transfer transit stations using bus tracking technology [J]. Transportation Research Part C:Emerging Technologies,1999,7(4):187-208.
[19]Dobies J. J. Customer Information at Bus Stops. TCRP Synthesis 17. Washington, D.C.1996.
[20]Federal Transport Administration (FTA), Transit Capacity and Quality of Service Manual, Transit Cooperative Research Program Web Document No.6, 1999.
[21]Fernandez R., Planzer R.. On the Capacity of Bus Transit Systems [J]. Transport Reviews,2002a,22(3):267-293.
[22]Fernandez R., Tyler N. Effect of Passenger-Bus-Traffic Interactions on Bus Stop Operation [J]. Transportation Planning and Technology,2005,28(4):273-292.
[23]Fernandez R., Tyler N. Study of Passenger-Bus-Traffic Interactions on Bus Stop Operations[R]. Centre for Transport Studies, University College London, United Kingdom,2004b, June
[24]Fernandez R., Valenzuela E. A model to predict bus commercial speed. Traffic Engineering and Control [J],2003,44(2):67-71.
[25]Fernandez R. A Model for Microscopic Simulation of Multiple-Berth Bus Stops [J]. Traffic Engineering and Control,2007,48(7):324-328.
[26]Fernandez R. A New Approach to Bus Stop Modelling [J]. Traffic Engineering and Control.2001,21(9):240-246.
[27]Fernandez R. Design Issues on High-Standard Bus Stops. ITE Journal. Chile. 2004a, (2):77-83.
[28]Fernandez R. Modelling Public Transport Stops By Microscopic Simulation[J]. Transportation Research Part C:Emerging Technologies, In Press, Corrected Proof, Available online March 2010
[29]Fernandez R. Rosemarie Planzer. On the Capacity of Bus Transit Systems[R]. Transport Reviews,2002b,22 (3):267-293.
[30]Fisher K.M., Transit-Oriented Design[R]. ULI Research Working Paper Series No.635. The Urban Land Institute, Washington, DC,1994.
[31]Fitzpatrick K., Hall K., Farnsworth S., Finley D. M. An Evaluation of Bus Bulbs on Transit, Traffic, and Pedestrian Operations. TCRP Web Document 19 (Project A-10A):Contractor's Final Report.2000.
[32]Folkenbrock D.J. etal.. Transit-Related Joint Development in Small Cities:An Appraisal of Opportunities and Practice[R]. University of Iowa, Iowa City, Iowa 1990.
[33]Fox K. SMARTEST-new tools for evaluating ITS [J]. Traffic Engineering and Control,2000,41(1):20-22.
[34]Fruin J. J. Pedestrian Planning and Design [M]. New York:Metropolitan Association of Urban Designer and Environmental Planners Inc.1971.
[35]Gibson J., Baeza I., Willlumsen L. Bus-Stops, Congestion and Congested Bus-stops[J]. Traffic Engineering& Control,1989. v20(6):291-296
[36]Holroyd E.M., Scraggs D.A. Waiting times for buses in Central London [J]. Traffic Engineering and Control,1966,8(3):158-160.
[37]Ibeas A., Olio L., Alonso B., Sainz O. Optimizing Bus Stop Spacing in Urban Areas[J]. Transportation Research Part E:Logistics and Transportation Review, 2010,46(3):446-458.
[38]Kevin S.J., Levinson S.H. TCRP Report 26:Operational Analysis of Bus Lanes on Arterials, TRB, National Academy Press, Washington, DC (1997) http://gulliver.trb.org/publications/tcrp/tcrp_rpt_26-a.pdf
[39]Koehler A.L., Kraus W. Simultaneous Control of Traffic Lights and Bus Departure for Priority Operation[J]. Transportation Research Part C:Emerging Technologies, In Press, Corrected Proof, Available online 17 March 2009.
[40]Koshy R. Z., Arasan V. T. Influence of Bus Stops on Flow Characteristics of Mixed Traffic[J]. Journal of Transportation Engineering,2005,131(8):640-643.
[41]Lam S. W., Tang L. C., Goh T. N., Tony Halim. Multiresponse optimization of dispatch rules for public bus services, Computers& Industrial Engineering, 56(1):77-86.
[42]Lao Y., Liu L. Performance Evaluation of Bus Lines With Data Envelopment Analysis and Geographic Information Systems[J]. Computers, Environment and Urban Systems,33(4):247-255.
[43]Lebacque J. P., Lesort J. B., and Giorgi F. Introducing Bus into First-order Macroscopic Flow Models. Transportation Research Record 1664[C], Nation Research Council, Washington D. C.,1998:70-80.
[44]Leiva C., Munoz J. C., Giesen R., Larrain H. Design of Limited-Stop Services for an Urban Bus Corridor with Capacity Constraints [J]. Transportation Research Part B:Methodological, In Press, Corrected Proof, Available online 10 February 2010.
[45]Levinson H. S. Analyzing Transit Travel Time Performance[C]. Transportation research record 915, Nation Research Council, Washington D.C.,1983:1-6.
[46]Levinson H.S. etal. Bus Lane Capacity Revisited. TRB the 77th.1998.
[47]Li Q., Wang Y. J., Zhou Y. Readjustment Effect Analysis of Public Bus Network in Beijing[J], Journal of Transportation Systems Engineering and Information Technology,2008,8(2):27-33.
[48]Morgan J. D., A Microscopic Simulation Laboratory for Advanced Public Transportation System Evaluation [J]. University of Texas, Austin, TX,2000.
[49]Reading F. J., Fu J. The Bus Stop Effect Revisited [J]. Nuclear Instruments and Methods in Physics Research Section B:Beam Interactions with Materials and Atoms,2004,214:126-130.
[50]Richard B., Briggs L. Transportation for Livable Communities:A Powerful New Approach to Transportation Policy[R]. Business Transportation Council, Washington, DC,1993.
[51]Sam Yagar, M. A. P. Jacques. Representing the Effects of Transit Stops at Signalized Intersection[C]. Proceedings of the International Symposium on Highway Capacity, Highway Capacity and Level of Service,1991:485-492.
[52]Sato T., Hino S. A Spatial CGE Analysis of Road Pricing in the Tokyo Metropolitan Area[J]. Journal of the Eastern Asia Society for Transportation Studies,2005,6:608-623.
[53]Schrank D., Lomax T. The 2007 Urban Mobility Report. Texas Transportation Institute[R]. The Texas A&M University System, September 2007:33-36.
[54]Shi H.W., Luo L.X., Bao T.Z. Research on the Way to Determine Types and Scales of Bus Stops[J], Journal of Transportation Systems Engineering and Information Technology,2007,7(2):83-86.
[55]Silva. P.C.M.,2000. Simulating bus stops in mixed traffic. Traffic Engineering and Control 41 (4),160-167.
[56]St. Jaques K., Levinson H. S.1997. Operational analysis of bus lanes on arterials. TCRP Report 26, Transportation Research Board, Washington, DC.
[57]Tiwari G. Urban Transport Priorities Meeting the Challenge of Socio-economic Diversity in Cities-Case Study Delhi, India.20th South African Transport Conference. South Africa,2001(7).
[58]Transit Cooperative Research Program(TCRP), Guidelines for the Location and Design of Bus Stops. TCRP Report 19. Washington, D.C.1996.
[59]Transportation Research Board (TRB), Bus Operator Workstation Evaluation and Design Guidelines. TCRP Report 25, Washington, D.C.1997.
[60]Transportation Research Board (TRB), Transit Capacity and Quality of Service Manual Part B:Bus transit Capacity. National Research Council, Washington, D.C.,1999,12.
[61]Transportation Research Board (TRB), Transit Capacity and Quality of Service Manual Part B:Bus Transit Capacity,2nd editon, National Research Council, Washington, D.C.,2004.
[62]Transportation Research Board (TRB). Highway Capacity Manual,1st edition. National Research Council. Washington D. C.,1950.
[63]Transportation Research Board (TRB). Highway Capacity Manual,2nd edition. National Research Council. Washington D. C.,1965.
[64]Transportation Research Board (TRB). Highway Capacity Manual,3rd edition. National Research Council. Washington D. C.,1985.
[65]Transportation Research Board (TRB). Highway Capacity Manual,4th edition. National Research Council, Washington, D.C.,2000.
[66]Transportation Research Board (TRB). Highway Capacity Manual. National Research Council. Washington D. C.,1994.
[67]Transportation Research Board (TRB). Operational Analysis of Bus Lanes on Arterials:Application and Refinement. Transportation Research Board,2000.
[68]Tyler N., Silva P., Brown N., Fenandez R., Operational impacts of bus stops. In: Tyler, N. (Ed.), Accessibility and the Bus System:From Concepts to Practice. Thomas Telford,2002, London, pp:99-137.
[69]Vaughan R. Optimum polar networks for an urban bus system with a many-to-many travel demand[J]. Transportation Research Part B: Methodological,1986,20(3):215-224.
[70]VISSIM User Manual-Version 3.60. PTV Planung Transport Verkehr AG,2001, 12.
[71]Wong S.C. Yang H. Delay at Signal-controlled Intersection with Bus Stop Upstream. Journal of Transportation Engineering,1998,124(3):229-234.
[72]Zhao X. M., Gao Z. Y., Jia B. The Capacity Drop Caused by the Combined Effect of the Intersection and the Bus Stop in a CA Model[J]. Physica A: Statistical Mechanics and its Applications,2007,385(2):645-658.
[73]Zhao X. M., Gao Z. Y, Li K. P. The Capacity of Two Neighbour Intersections Considering the Influence of the Bus Stop [J]. Physica A:Statistical Mechanics and its Applications,2008,387(18):4649-4656.
[74]柏海舰,李文权.常规公交站台容纳线路能力计算模型[J].东南大学学报,2007,11(6)：1011-1013.
[75]北京交通研究发展中心(Beijing Transportation Research Center, BJTRC),2009北京市交通发展年度报告[R],2009.
[76]北京市质量技术监督局.公共气电车场站建设标准[S].2008.6.
[77]陈宽民,严宝杰.道路通行能力分析[M].北京：人民交通出版社,2003.
[78]陈盛.城市道路交通流速度流量实用关系模型研究[D].南京：东南大学,2003.
[79]丁创新,曾应昆.高等级公路收费站通行能力分析[J].昆明理工大学学报2005,30(6)：90-93,104.
[80]付强,林航飞,杨晓芳,李晔.基于服务水平的车辆折算系数[J].同济大学学报,2007,35(1)：67-71.
[81]葛宏伟,王炜,陈学武,梅振宇.城市公交停靠站规划设置方法综述[J].现代城市研究,2004(11)：53-57.
[82]葛宏伟.城市公交停靠车站交通影响分析及优化技术研究[D].南京：东南大学,2006.
[83]关伟,申金升,葛芳.公交优先的信号控制策略研究[J].系统工程学报,2001,16(3)：176-180.
[84]郭冠英.中途停靠站公交线路数上限的确定及驻站时间计算模型[J].上海公路,2000,2：27-10
[85]郭中华.城市道路路段交通流特性分析与模型研究[D].南京：东南大学.2005.6
[86]何宁,马健宵,李娜.公交车站停靠能力的研究[J].城市轨道交通研究,2004.2：78-80.
[87]黄海鸥,张玮,李骁春.基于排队理论的京杭运河船闸通过能力研究[J].武汉理工大学学报：交通科学与工程版,2009,33(3)：604-607.
[88]黄敏,刘帅,周涛.港湾式公交车出站对道路交通流影响分析[J].西华大学学报,2007,9(5)：33-34.
[89]黄艳君.城市公共交通路段优先通行技术及评价方法研究[D].南京：东南大学,2003.
[90]建设部.建设部关于优先发展城市公共交通的意见.建城[2004]38号,2004.03.06.来源：建设部网站.
[91]解建华,徐康明.北京快速公交乘客登降速度调查研究[R].BRT报告,2006.
[92]况爱武,黄中祥.随机供求下的道路服务水平可靠性[J].系统工程,2007,25(6)：25-30.
[93]李得伟.城市轨道交通枢纽乘客集散模型及微观仿真理论[D].北京：北京交通大学,2007.
[94]李欢.道路交通设计与组织对公交运行的影响分析[D].北京： 北京交通大学.2007.
[95]李建新,毛保华.混合交通环境下有信号交叉口通行能力研究[J].交通运输系统工程与信息,2001,2(1)：119-123.
[96]李江.交通工程学[M].北京：人民交通出版社.2004.
[97]李明.快速公交车站客流预测模型及其选型设计问题研究[D].北京交通大学.2008,6.
[98]李娜,陈学武.公交车中途停靠站停靠能力及设计站长初算[J].土木工程学报,2003,36(7)：72-77.
[99]李振龙,陈德望.公交车站交通拥挤的车流波动理论分析[J].交通与计算机,2005,6(23)：62-65.
[100]李之红,袁振洲.基于多目标的城市公交车站布设模型的研究[J].交通标准化,2006(10)：180-182.
[101]廖鹏.内河船闸通过能力研究进展[J].水利水运工程学报,2009,(3)：34-40.
[102]刘安.公交停靠站位置分布的研究[J].中国交通工程,1995,2：30-31.
[103]刘惠玲,关伟.基于系统动力学的城市公交系统模型[J].城市公共交通,2006(6)：24-27,31.
[104]刘锐,严宝杰.公交车站有效泊位换算系数的元胞自动机仿真分析[J].西安建筑科技大学学报,2008,40(3)：434-438.
[105]刘爽,陈绍宽,郭谨一.基于GIS的区域交通网络描述及构建技术研究[J].交通运输工程与信息学报,2005,3(1)：51-56.
[106]刘武,李文子.城市公交服务乘客满意度指数模型[J].城市交通,2007,11(6)：65-69,13.
[107]陆春其.城市公交车站布局优化研究[D].南京：东南大学,2002.
[108]吕杰.公交停靠站对信号交叉口通行能力的影响分析[D].上海：同济大学,1999.
[109]吕林.城市公交车站优化设计方法研究[D].南京：东南大学.2006.
[110]马宏伟,李刚炎,胡剑,于翔鹏.城市公交停靠站时间延误分析与对策[J],公路与汽运,2006,(6)：25-27.
[111]马继辉,关伟.何蜀燕,陈鹏.公共交通线路调整影响分析系统的设计与实现[J],交通运输系统工程与信息,2007,7(2)：58-62.
[112]毛保华,孙壮志,贾顺平.区域交通组织优化方法及实践研究[M].北京：人民交通出版社.2007.
[113]毛保华,杨方,刘海东等.我国道路交通拥挤成因及解决策略探讨[J].道路交通与安全,2001,2：20-22.
[114]毛保华,杨肇夏,陈海波.道路交通仿真技术与系统研究[J].北方交通大学学报,2002,26(5)：37-46.
[115]毛保华等.北京市交通拥堵评价与缓解实施方案研究2008[R].北京：北京交通研究发展中心,2008.
[116]毛保华等.北京市三里河至西二环地区交通组织优化研究报告[R].北京：北京交通研究发展中心,2006.
[117]潘全如.随机服务系统在交通网络中的应用[D].镇江：江苏大学,2007.
[118]彭春露,彭国雄.一种新的城市主干道公交停靠站的布置方法探讨[J].土木工程学报,2003,36(1)：64-67.
[119]彭国雄,莫汉康.城市公交停靠站设置常见问题及对策[J].交通运输工程学报,2001(3)：77-80.
[120]任福田,刘小明等.道路通行能力手册[M].北京：人民交通出版社,2007.
[121]荣建,常成利,刘小明,任福田.标定交通流模型时最小统计间隔的选择[J].北京工业大学学报,1992,25(4)：49-55.
[122]邵俊,杨晓光,史春华.部分锯齿形公交优先进口道的交通设计与分析[J].同济大学学报：自然科学版,2001,29(10)：1175-1180.
[123]邵俊.公共汽车交通专用道(路)系统设计与评价方法研究[D].上海：同济大学,2000.
[124]沈景炎.乘客动态分布与站台宽度的研究[J].城市轨道交通研究,2001(1)：21-27.
[125]石道华,丁勇,毛保华.基于设备能力利用的铁路运输服务水平研究[J].交通运输系统工程与信息,2003,3(1)：45-50.
[126]石红文,罗良鑫,鲍同振.公交中间站类型与规模的确定方法研究[J].交通运输系统工程与信息,2007,7(2)：83-87.
[127]孙荣恒,李建平.排队论基础[M].北京：科学出版社,2002.
[128]谭满春,徐建闽,毛宗元.城市公共汽车停靠站选址模型[J].公路交通科技,1999,16(2)：59-61.
[129]王敬东.港湾式公交停靠站设置问题研究[D].大连：大连理工大学,2003.
[130]王兰兰.公交专用车道设置条件研究[D].哈尔滨：哈尔滨工业大学,2004.
[131]王炜.道路交通工程系统分析方法[M].北京：人民交通出版社,2004.
[132]魏军,王守宝.基于服务水平与道路等级公交专用道设置研究[J].城市道桥与防洪,2009,(4)：114-116.
[133]吴洋,罗霞.公交车辆站停时间与乘客行为的关系[J].西南交通大学学报,2007,42(2)：243-248.
[134]伍拾煤.公交停靠站设置问题的研究[D].哈尔滨：哈尔滨工业大学,2002.
[135]夏少刚.运筹学-经济优化方法与模型[M].北京：清华大学出版社,2005.
[136]熊烈强,刘海岷.混合交通流参数之间关系模型标定[J].武汉理工大学学报,2008,32(3)：561-564.
[137]徐林,杨孝宽,艾树波,金冰峰,北京市城市道路服务水平分级研究[J].交通与运输,2008,24(5)：43-45.
[138]徐林,杨孝宽,艾树波,金冰峰.北京市城市道路服务水平分级研究[J].交通与运输,2008(5)：43-45.
[139]许添本,简正铨.CORSIM与VISSIM仿真软件跟车行为与不稳定流应用之比较研究.www. its-taiwan. org. tw/memoir/memoir2.htm
[140]姚荣涵.车辆排队模型研究[D].长春：吉林大学,2007.
[141]尹红亮,王炜,王锦尧.公交运行对行驶车速影响的实验研究[J].公路交通科技,2002(4)：93-96.
[142]运筹学教材编写组.运筹学[M].北京：清华大学出版社,1990.
[143]曾奕林.公交停靠站站台尺寸的研究[J].交通与运输,2005,7(2)：64-69.
[144]张国权,吕小欢,杨君.最小综合损失准则与多指标均匀正交试验设计的优 化[J].华南农业大学学报,2002,23(1)：85-88.
[145]张南.公交优先通行系统研究[D].成都：西南交通大学,2003.
[146]张卫华.城市公共交通优先通行技术及评价方法研究[D].南京：东南大学,2004.
[147]张香平,陈振起.城市车辆速度对道路交通影响的评估[J].交通运输系统工程与信息,2005,5(6)：72-77.
[148]张亚平,裴玉龙,周刚.珠江三角洲地区城际道路服务水平评估研究[J].公路交通科技,2003,20(3)：108-112,128.
[149]章小军,彭国雄,董博,张鹍鹏.非港湾式停靠站对路段通行能力的影响研究[J].2007,24(1)：143-146.
[150]郑丽丽,宋瑞.利用公交通行能力解决公交问题的探讨,公路交通科技,2005年22(6),143-146.
[151]郑丽丽.公交运输能力研究[D].北京：北京交通大学,2005.
[152]郑远,杜豫川,孙立军.美国联邦公路局路阻函数探讨[J].交通与运输,2007,7：24-26.
[153]中国公路协会.交通工程手册[M].北京：人民交通出版社,1998.
[154]中华人民共和国建设部标准.城市道路交通规划设计规范GB50220-95,1995.
[155]周刚,常成利.高速公路收费站通行能力研究[J].公路交通科技,2001,18(3)：56-59.
[156]朱祎,陈学武.多线路公交站台车辆延误分析与对策[J].中国市政工程,2002,97：7-9.
[157]祝付玲,邓卫,葛亮.公交线路运力配备方法研究[J].交通运输工程与信息学报,2005,3(1)：93-97.
[158]庄楚强,吴亚森.应用数理统计基础[M].广州：华南理工大学出版社,2002.
[2]Andrzej A. Probabilistic Models of Passengers Service Processes at Bus Stops[J], Transportation Research Part B:Methodological,1992,26(4):253-259.
[3]Banks H. J., Introduction to Traffic Engineering 2nd ed[M]. McGraw-Hill series in transportation, McGraw-Hill companies, Inc.,2002
[4]Bernick M., et al. Transit-Based Development in the United States:A Review of Recent Experiences[R]. University of California at Berkeley, Institute of Urban andRegional Development, Berkeley, California,1994.
[5]Bernick M., Cervero R. Transit Villages for the 21st Century [M]. New York, McGraw Hill,1996.
[6]Boarnet M., Crane R.B. Public Finance and Transit-Oriented Planning:New Evidence from Southern California [J]. Journal of Planning Education and Research,1998,17:206-219.
[7]Box P. C. The Location and Design of Bus Transfer Facilities[C]. Institute of Transportation Engineers, Technical Council Committee 5C-1A, Washington, DC,1992.
[8]Bus Transfer Center Study. Statewide Transit-Oriented Development Study: Factors for Success in California[R]. Working Paper, Project for Public Spaces, Inc. Publication. California Department of Transportation,2002:8-2.
[9]Cervero R. Transit-Based Housing in California:Evidence on Ridership Impacts [J]. Transport Policy,1994(3):174-183.
[10]Cervero R., Mark D., An Assessment of Suburban Targeted Transit Service Strategies in the United States[R]. University of California, Transportation Center, Berkeley, California,1993.
[11]Chen X. M., Yu L., Zhang Y. S., Guo J. F. Analyzing urban bus service reliability at the stop, route, and network levels [J]. Transportation Research Part A:Policy and Practice,2009,43(8):722-734.
[12]Chen Y. Z., Li N., He D. R., A study on some urban bus transport networks [J]. Physica A:Statistical Mechanics and its Applications,2007,376(15):747-754.
[13]Daganzo C. F. A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons. Transportation Research Part B,2009, 43(10):913-921.
[14]Daniel J., Konon W. Effectiveness of Bus Bulbs for Bus Stops-Final Report[R]. 2005(1).http://transportation.njit.edu/nctip/research/ResRep.asp?status =Completed&proj ectNo= 111&grantNumber=992530
[15]Davison L. J., Knowles D. R. Bus quality partnerships, modal shift and traffic decongestion [J]. Journal of Transport Geography,2006,14(3):177-194.
[16]Dejeammes M., Coffin F. Bus Stop Design and Automated Guidance for Low-floor Buses[C]. Transportation Research Record, Nation Research Council. Washington D.C.1999:85-91.
[17]Demetsky J. M., et al. Bus Stop Loacation and Design [J]. Journal of Transportation Engineering,1982.7:313-327.
[18]Dessouky M., Hall R., Nowroozi A., Mourikas K. Bus dispatching at timed transfer transit stations using bus tracking technology [J]. Transportation Research Part C:Emerging Technologies,1999,7(4):187-208.
[19]Dobies J. J. Customer Information at Bus Stops. TCRP Synthesis 17. Washington, D.C.1996.
[20]Federal Transport Administration (FTA), Transit Capacity and Quality of Service Manual, Transit Cooperative Research Program Web Document No.6, 1999.
[21]Fernandez R., Planzer R.. On the Capacity of Bus Transit Systems [J]. Transport Reviews,2002a,22(3):267-293.
[22]Fernandez R., Tyler N. Effect of Passenger-Bus-Traffic Interactions on Bus Stop Operation [J]. Transportation Planning and Technology,2005,28(4):273-292.
[23]Fernandez R., Tyler N. Study of Passenger-Bus-Traffic Interactions on Bus Stop Operations[R]. Centre for Transport Studies, University College London, United Kingdom,2004b, June
[24]Fernandez R., Valenzuela E. A model to predict bus commercial speed. Traffic Engineering and Control [J],2003,44(2):67-71.
[25]Fernandez R. A Model for Microscopic Simulation of Multiple-Berth Bus Stops [J]. Traffic Engineering and Control,2007,48(7):324-328.
[26]Fernandez R. A New Approach to Bus Stop Modelling [J]. Traffic Engineering and Control.2001,21(9):240-246.
[27]Fernandez R. Design Issues on High-Standard Bus Stops. ITE Journal. Chile. 2004a, (2):77-83.
[28]Fernandez R. Modelling Public Transport Stops By Microscopic Simulation[J]. Transportation Research Part C:Emerging Technologies, In Press, Corrected Proof, Available online March 2010
[29]Fernandez R. Rosemarie Planzer. On the Capacity of Bus Transit Systems[R]. Transport Reviews,2002b,22 (3):267-293.
[30]Fisher K.M., Transit-Oriented Design[R]. ULI Research Working Paper Series No.635. The Urban Land Institute, Washington, DC,1994.
[31]Fitzpatrick K., Hall K., Farnsworth S., Finley D. M. An Evaluation of Bus Bulbs on Transit, Traffic, and Pedestrian Operations. TCRP Web Document 19 (Project A-10A):Contractor's Final Report.2000.
[32]Folkenbrock D.J. etal.. Transit-Related Joint Development in Small Cities:An Appraisal of Opportunities and Practice[R]. University of Iowa, Iowa City, Iowa 1990.
[33]Fox K. SMARTEST-new tools for evaluating ITS [J]. Traffic Engineering and Control,2000,41(1):20-22.
[34]Fruin J. J. Pedestrian Planning and Design [M]. New York:Metropolitan Association of Urban Designer and Environmental Planners Inc.1971.
[35]Gibson J., Baeza I., Willlumsen L. Bus-Stops, Congestion and Congested Bus-stops[J]. Traffic Engineering& Control,1989. v20(6):291-296
[36]Holroyd E.M., Scraggs D.A. Waiting times for buses in Central London [J]. Traffic Engineering and Control,1966,8(3):158-160.
[37]Ibeas A., Olio L., Alonso B., Sainz O. Optimizing Bus Stop Spacing in Urban Areas[J]. Transportation Research Part E:Logistics and Transportation Review, 2010,46(3):446-458.
[38]Kevin S.J., Levinson S.H. TCRP Report 26:Operational Analysis of Bus Lanes on Arterials, TRB, National Academy Press, Washington, DC (1997) http://gulliver.trb.org/publications/tcrp/tcrp_rpt_26-a.pdf
[39]Koehler A.L., Kraus W. Simultaneous Control of Traffic Lights and Bus Departure for Priority Operation[J]. Transportation Research Part C:Emerging Technologies, In Press, Corrected Proof, Available online 17 March 2009.
[40]Koshy R. Z., Arasan V. T. Influence of Bus Stops on Flow Characteristics of Mixed Traffic[J]. Journal of Transportation Engineering,2005,131(8):640-643.
[41]Lam S. W., Tang L. C., Goh T. N., Tony Halim. Multiresponse optimization of dispatch rules for public bus services, Computers& Industrial Engineering, 56(1):77-86.
[42]Lao Y., Liu L. Performance Evaluation of Bus Lines With Data Envelopment Analysis and Geographic Information Systems[J]. Computers, Environment and Urban Systems,33(4):247-255.
[43]Lebacque J. P., Lesort J. B., and Giorgi F. Introducing Bus into First-order Macroscopic Flow Models. Transportation Research Record 1664[C], Nation Research Council, Washington D. C.,1998:70-80.
[44]Leiva C., Munoz J. C., Giesen R., Larrain H. Design of Limited-Stop Services for an Urban Bus Corridor with Capacity Constraints [J]. Transportation Research Part B:Methodological, In Press, Corrected Proof, Available online 10 February 2010.
[45]Levinson H. S. Analyzing Transit Travel Time Performance[C]. Transportation research record 915, Nation Research Council, Washington D.C.,1983:1-6.
[46]Levinson H.S. etal. Bus Lane Capacity Revisited. TRB the 77th.1998.
[47]Li Q., Wang Y. J., Zhou Y. Readjustment Effect Analysis of Public Bus Network in Beijing[J], Journal of Transportation Systems Engineering and Information Technology,2008,8(2):27-33.
[48]Morgan J. D., A Microscopic Simulation Laboratory for Advanced Public Transportation System Evaluation [J]. University of Texas, Austin, TX,2000.
[49]Reading F. J., Fu J. The Bus Stop Effect Revisited [J]. Nuclear Instruments and Methods in Physics Research Section B:Beam Interactions with Materials and Atoms,2004,214:126-130.
[50]Richard B., Briggs L. Transportation for Livable Communities:A Powerful New Approach to Transportation Policy[R]. Business Transportation Council, Washington, DC,1993.
[51]Sam Yagar, M. A. P. Jacques. Representing the Effects of Transit Stops at Signalized Intersection[C]. Proceedings of the International Symposium on Highway Capacity, Highway Capacity and Level of Service,1991:485-492.
[52]Sato T., Hino S. A Spatial CGE Analysis of Road Pricing in the Tokyo Metropolitan Area[J]. Journal of the Eastern Asia Society for Transportation Studies,2005,6:608-623.
[53]Schrank D., Lomax T. The 2007 Urban Mobility Report. Texas Transportation Institute[R]. The Texas A&M University System, September 2007:33-36.
[54]Shi H.W., Luo L.X., Bao T.Z. Research on the Way to Determine Types and Scales of Bus Stops[J], Journal of Transportation Systems Engineering and Information Technology,2007,7(2):83-86.
[55]Silva. P.C.M.,2000. Simulating bus stops in mixed traffic. Traffic Engineering and Control 41 (4),160-167.
[56]St. Jaques K., Levinson H. S.1997. Operational analysis of bus lanes on arterials. TCRP Report 26, Transportation Research Board, Washington, DC.
[57]Tiwari G. Urban Transport Priorities Meeting the Challenge of Socio-economic Diversity in Cities-Case Study Delhi, India.20th South African Transport Conference. South Africa,2001(7).
[58]Transit Cooperative Research Program(TCRP), Guidelines for the Location and Design of Bus Stops. TCRP Report 19. Washington, D.C.1996.
[59]Transportation Research Board (TRB), Bus Operator Workstation Evaluation and Design Guidelines. TCRP Report 25, Washington, D.C.1997.
[60]Transportation Research Board (TRB), Transit Capacity and Quality of Service Manual Part B:Bus transit Capacity. National Research Council, Washington, D.C.,1999,12.
[61]Transportation Research Board (TRB), Transit Capacity and Quality of Service Manual Part B:Bus Transit Capacity,2nd editon, National Research Council, Washington, D.C.,2004.
[62]Transportation Research Board (TRB). Highway Capacity Manual,1st edition. National Research Council. Washington D. C.,1950.
[63]Transportation Research Board (TRB). Highway Capacity Manual,2nd edition. National Research Council. Washington D. C.,1965.
[64]Transportation Research Board (TRB). Highway Capacity Manual,3rd edition. National Research Council. Washington D. C.,1985.
[65]Transportation Research Board (TRB). Highway Capacity Manual,4th edition. National Research Council, Washington, D.C.,2000.
[66]Transportation Research Board (TRB). Highway Capacity Manual. National Research Council. Washington D. C.,1994.
[67]Transportation Research Board (TRB). Operational Analysis of Bus Lanes on Arterials:Application and Refinement. Transportation Research Board,2000.
[68]Tyler N., Silva P., Brown N., Fenandez R., Operational impacts of bus stops. In: Tyler, N. (Ed.), Accessibility and the Bus System:From Concepts to Practice. Thomas Telford,2002, London, pp:99-137.
[69]Vaughan R. Optimum polar networks for an urban bus system with a many-to-many travel demand[J]. Transportation Research Part B: Methodological,1986,20(3):215-224.
[70]VISSIM User Manual-Version 3.60. PTV Planung Transport Verkehr AG,2001, 12.
[71]Wong S.C. Yang H. Delay at Signal-controlled Intersection with Bus Stop Upstream. Journal of Transportation Engineering,1998,124(3):229-234.
[72]Zhao X. M., Gao Z. Y., Jia B. The Capacity Drop Caused by the Combined Effect of the Intersection and the Bus Stop in a CA Model[J]. Physica A: Statistical Mechanics and its Applications,2007,385(2):645-658.
[73]Zhao X. M., Gao Z. Y, Li K. P. The Capacity of Two Neighbour Intersections Considering the Influence of the Bus Stop [J]. Physica A:Statistical Mechanics and its Applications,2008,387(18):4649-4656.
[74]柏海舰,李文权.常规公交站台容纳线路能力计算模型[J].东南大学学报,2007,11(6)：1011-1013.
[75]北京交通研究发展中心(Beijing Transportation Research Center, BJTRC),2009北京市交通发展年度报告[R],2009.
[76]北京市质量技术监督局.公共气电车场站建设标准[S].2008.6.
[77]陈宽民,严宝杰.道路通行能力分析[M].北京：人民交通出版社,2003.
[78]陈盛.城市道路交通流速度流量实用关系模型研究[D].南京：东南大学,2003.
[79]丁创新,曾应昆.高等级公路收费站通行能力分析[J].昆明理工大学学报2005,30(6)：90-93,104.
[80]付强,林航飞,杨晓芳,李晔.基于服务水平的车辆折算系数[J].同济大学学报,2007,35(1)：67-71.
[81]葛宏伟,王炜,陈学武,梅振宇.城市公交停靠站规划设置方法综述[J].现代城市研究,2004(11)：53-57.
[82]葛宏伟.城市公交停靠车站交通影响分析及优化技术研究[D].南京：东南大学,2006.
[83]关伟,申金升,葛芳.公交优先的信号控制策略研究[J].系统工程学报,2001,16(3)：176-180.
[84]郭冠英.中途停靠站公交线路数上限的确定及驻站时间计算模型[J].上海公路,2000,2：27-10
[85]郭中华.城市道路路段交通流特性分析与模型研究[D].南京：东南大学.2005.6
[86]何宁,马健宵,李娜.公交车站停靠能力的研究[J].城市轨道交通研究,2004.2：78-80.
[87]黄海鸥,张玮,李骁春.基于排队理论的京杭运河船闸通过能力研究[J].武汉理工大学学报：交通科学与工程版,2009,33(3)：604-607.
[88]黄敏,刘帅,周涛.港湾式公交车出站对道路交通流影响分析[J].西华大学学报,2007,9(5)：33-34.
[89]黄艳君.城市公共交通路段优先通行技术及评价方法研究[D].南京：东南大学,2003.
[90]建设部.建设部关于优先发展城市公共交通的意见.建城[2004]38号,2004.03.06.来源：建设部网站.
[91]解建华,徐康明.北京快速公交乘客登降速度调查研究[R].BRT报告,2006.
[92]况爱武,黄中祥.随机供求下的道路服务水平可靠性[J].系统工程,2007,25(6)：25-30.
[93]李得伟.城市轨道交通枢纽乘客集散模型及微观仿真理论[D].北京：北京交通大学,2007.
[94]李欢.道路交通设计与组织对公交运行的影响分析[D].北京： 北京交通大学.2007.
[95]李建新,毛保华.混合交通环境下有信号交叉口通行能力研究[J].交通运输系统工程与信息,2001,2(1)：119-123.
[96]李江.交通工程学[M].北京：人民交通出版社.2004.
[97]李明.快速公交车站客流预测模型及其选型设计问题研究[D].北京交通大学.2008,6.
[98]李娜,陈学武.公交车中途停靠站停靠能力及设计站长初算[J].土木工程学报,2003,36(7)：72-77.
[99]李振龙,陈德望.公交车站交通拥挤的车流波动理论分析[J].交通与计算机,2005,6(23)：62-65.
[100]李之红,袁振洲.基于多目标的城市公交车站布设模型的研究[J].交通标准化,2006(10)：180-182.
[101]廖鹏.内河船闸通过能力研究进展[J].水利水运工程学报,2009,(3)：34-40.
[102]刘安.公交停靠站位置分布的研究[J].中国交通工程,1995,2：30-31.
[103]刘惠玲,关伟.基于系统动力学的城市公交系统模型[J].城市公共交通,2006(6)：24-27,31.
[104]刘锐,严宝杰.公交车站有效泊位换算系数的元胞自动机仿真分析[J].西安建筑科技大学学报,2008,40(3)：434-438.
[105]刘爽,陈绍宽,郭谨一.基于GIS的区域交通网络描述及构建技术研究[J].交通运输工程与信息学报,2005,3(1)：51-56.
[106]刘武,李文子.城市公交服务乘客满意度指数模型[J].城市交通,2007,11(6)：65-69,13.
[107]陆春其.城市公交车站布局优化研究[D].南京：东南大学,2002.
[108]吕杰.公交停靠站对信号交叉口通行能力的影响分析[D].上海：同济大学,1999.
[109]吕林.城市公交车站优化设计方法研究[D].南京：东南大学.2006.
[110]马宏伟,李刚炎,胡剑,于翔鹏.城市公交停靠站时间延误分析与对策[J],公路与汽运,2006,(6)：25-27.
[111]马继辉,关伟.何蜀燕,陈鹏.公共交通线路调整影响分析系统的设计与实现[J],交通运输系统工程与信息,2007,7(2)：58-62.
[112]毛保华,孙壮志,贾顺平.区域交通组织优化方法及实践研究[M].北京：人民交通出版社.2007.
[113]毛保华,杨方,刘海东等.我国道路交通拥挤成因及解决策略探讨[J].道路交通与安全,2001,2：20-22.
[114]毛保华,杨肇夏,陈海波.道路交通仿真技术与系统研究[J].北方交通大学学报,2002,26(5)：37-46.
[115]毛保华等.北京市交通拥堵评价与缓解实施方案研究2008[R].北京：北京交通研究发展中心,2008.
[116]毛保华等.北京市三里河至西二环地区交通组织优化研究报告[R].北京：北京交通研究发展中心,2006.
[117]潘全如.随机服务系统在交通网络中的应用[D].镇江：江苏大学,2007.
[118]彭春露,彭国雄.一种新的城市主干道公交停靠站的布置方法探讨[J].土木工程学报,2003,36(1)：64-67.
[119]彭国雄,莫汉康.城市公交停靠站设置常见问题及对策[J].交通运输工程学报,2001(3)：77-80.
[120]任福田,刘小明等.道路通行能力手册[M].北京：人民交通出版社,2007.
[121]荣建,常成利,刘小明,任福田.标定交通流模型时最小统计间隔的选择[J].北京工业大学学报,1992,25(4)：49-55.
[122]邵俊,杨晓光,史春华.部分锯齿形公交优先进口道的交通设计与分析[J].同济大学学报：自然科学版,2001,29(10)：1175-1180.
[123]邵俊.公共汽车交通专用道(路)系统设计与评价方法研究[D].上海：同济大学,2000.
[124]沈景炎.乘客动态分布与站台宽度的研究[J].城市轨道交通研究,2001(1)：21-27.
[125]石道华,丁勇,毛保华.基于设备能力利用的铁路运输服务水平研究[J].交通运输系统工程与信息,2003,3(1)：45-50.
[126]石红文,罗良鑫,鲍同振.公交中间站类型与规模的确定方法研究[J].交通运输系统工程与信息,2007,7(2)：83-87.
[127]孙荣恒,李建平.排队论基础[M].北京：科学出版社,2002.
[128]谭满春,徐建闽,毛宗元.城市公共汽车停靠站选址模型[J].公路交通科技,1999,16(2)：59-61.
[129]王敬东.港湾式公交停靠站设置问题研究[D].大连：大连理工大学,2003.
[130]王兰兰.公交专用车道设置条件研究[D].哈尔滨：哈尔滨工业大学,2004.
[131]王炜.道路交通工程系统分析方法[M].北京：人民交通出版社,2004.
[132]魏军,王守宝.基于服务水平与道路等级公交专用道设置研究[J].城市道桥与防洪,2009,(4)：114-116.
[133]吴洋,罗霞.公交车辆站停时间与乘客行为的关系[J].西南交通大学学报,2007,42(2)：243-248.
[134]伍拾煤.公交停靠站设置问题的研究[D].哈尔滨：哈尔滨工业大学,2002.
[135]夏少刚.运筹学-经济优化方法与模型[M].北京：清华大学出版社,2005.
[136]熊烈强,刘海岷.混合交通流参数之间关系模型标定[J].武汉理工大学学报,2008,32(3)：561-564.
[137]徐林,杨孝宽,艾树波,金冰峰,北京市城市道路服务水平分级研究[J].交通与运输,2008,24(5)：43-45.
[138]徐林,杨孝宽,艾树波,金冰峰.北京市城市道路服务水平分级研究[J].交通与运输,2008(5)：43-45.
[139]许添本,简正铨.CORSIM与VISSIM仿真软件跟车行为与不稳定流应用之比较研究.www. its-taiwan. org. tw/memoir/memoir2.htm
[140]姚荣涵.车辆排队模型研究[D].长春：吉林大学,2007.
[141]尹红亮,王炜,王锦尧.公交运行对行驶车速影响的实验研究[J].公路交通科技,2002(4)：93-96.
[142]运筹学教材编写组.运筹学[M].北京：清华大学出版社,1990.
[143]曾奕林.公交停靠站站台尺寸的研究[J].交通与运输,2005,7(2)：64-69.
[144]张国权,吕小欢,杨君.最小综合损失准则与多指标均匀正交试验设计的优 化[J].华南农业大学学报,2002,23(1)：85-88.
[145]张南.公交优先通行系统研究[D].成都：西南交通大学,2003.
[146]张卫华.城市公共交通优先通行技术及评价方法研究[D].南京：东南大学,2004.
[147]张香平,陈振起.城市车辆速度对道路交通影响的评估[J].交通运输系统工程与信息,2005,5(6)：72-77.
[148]张亚平,裴玉龙,周刚.珠江三角洲地区城际道路服务水平评估研究[J].公路交通科技,2003,20(3)：108-112,128.
[149]章小军,彭国雄,董博,张鹍鹏.非港湾式停靠站对路段通行能力的影响研究[J].2007,24(1)：143-146.
[150]郑丽丽,宋瑞.利用公交通行能力解决公交问题的探讨,公路交通科技,2005年22(6),143-146.
[151]郑丽丽.公交运输能力研究[D].北京：北京交通大学,2005.
[152]郑远,杜豫川,孙立军.美国联邦公路局路阻函数探讨[J].交通与运输,2007,7：24-26.
[153]中国公路协会.交通工程手册[M].北京：人民交通出版社,1998.
[154]中华人民共和国建设部标准.城市道路交通规划设计规范GB50220-95,1995.
[155]周刚,常成利.高速公路收费站通行能力研究[J].公路交通科技,2001,18(3)：56-59.
[156]朱祎,陈学武.多线路公交站台车辆延误分析与对策[J].中国市政工程,2002,97：7-9.
[157]祝付玲,邓卫,葛亮.公交线路运力配备方法研究[J].交通运输工程与信息学报,2005,3(1)：93-97.
[158]庄楚强,吴亚森.应用数理统计基础[M].广州：华南理工大学出版社,2002.