基于可拓理论的城市中心区交通组织方案评价方法研究
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摘要
近年来,城市机动车保有量大幅增加,增长速度远远超过道路改扩建的速度,同时,城市经济快速发展所生成的交通需求远远大于城市特别是中心区域已有道路资源的供给能力。然而,城市中心区道路资源的有限性,以及近期内不可能无限度地增扩性,也就限制了城市中心区交通需求的过快增长。本文分析城市中心区基本特性入手,提出针对某一城市的中心区交通组织方案,为决策者提供理论支持依据。
本文首先分析城市中心区的职能、用地结构和交通等三方面特性,指出中心区土地利用强度较高、容易产生局部或全区域的交通拥堵等特点。根据中心区交通组织原则,特别是最低可接受服务水平的原则,提出管理措施排优和基于拥堵范围进行交通组织管理的两种城市中心区交通组织的方法思想。结合交通组织的一般管理措施,提出中心区交通组织的方法步骤。
利用可拓理论解决矛盾问题的思想,对中心区交通组织方案进行评价。在进行评价之前,首先对评价指标的选取进行科学系统的归纳总结,结合国内外相关论述,提出一套适用于城市中心区交通组织方案评价的指标体系。接下来根据可拓层次分析法构建中心区交通组织方案的评价思路,并对可拓理论关于中心区交通组织方案评价的适用性的进行描述。最后建立物元可拓评价模型,完成城市中心区交通组织方案评价的理论框架模型。
以河南省商丘市城市中心区为实例研究对象,首先分析商丘市中心区路网现状、土地利用现状及交通现状。随后针对中心区存在的交通问题等提出一套适用于商丘市中心区的交通组织方案,并以商丘市中心区路网现状交通组织作为初始方案最为对比方案,运用交通规划软件TransCAD,分配路网交通流量,并取得各项评价指标的确切数值。最后运用物元可拓评价模型,通过确切的数值显示表明交通组织方案的可取性。
During the last decades, the quantities of motor vehicles have increased a lot with a rapid increase speed which is far larger than that of the road expansion, and the requirement of transportation caused by the development of economy has exceeded the ability of supply. However, the limitation of the road resource, and the impossibility of unlimited growth have become the factors limiting the increase of traffic demand of the city center. Therefore, an optimized plan is proposed to the managers in this work.
By analyzing the performance of function, the structure of land using, transportation of the center area of the city, the characteristics of higher intensity of land using and part or all prone to traffic jams are pointed out. A method of management scheduling priority and congestion optimization based on the range is brought out based on the rule of minimum acceptable level of service, and then the details are given considering the common.
The plan of optimal traffic organization of the central area of program evaluation is evaluated with the theory of matter-element extension method. And before the evaluation, first of all, the selection of a scientific evaluation system must be summarized, and discourses at home and abroad, getting an excellent evaluation index system of traffic organization and optimization program. And then, the ideas of the evaluation of traffic organization and optimization program can be described according to the matter-element extension method. Finally, the matter-element extension model and downtown traffic organization and optimization program evaluation model are built.
Taking the center area of Shangqiu, Henan as an example, first of all, the status of the central area road network and land use and transportation are analyzed. And then a program of traffic organization and optimization for Shangqiu is worked out, and the transportation flux is calculated with TransCAD. The results are compared with that of the current traffic organization and optimization. The results show that the plan in this work will lead to a nicer one.
本文首先分析城市中心区的职能、用地结构和交通等三方面特性,指出中心区土地利用强度较高、容易产生局部或全区域的交通拥堵等特点。根据中心区交通组织原则,特别是最低可接受服务水平的原则,提出管理措施排优和基于拥堵范围进行交通组织管理的两种城市中心区交通组织的方法思想。结合交通组织的一般管理措施,提出中心区交通组织的方法步骤。
利用可拓理论解决矛盾问题的思想,对中心区交通组织方案进行评价。在进行评价之前,首先对评价指标的选取进行科学系统的归纳总结,结合国内外相关论述,提出一套适用于城市中心区交通组织方案评价的指标体系。接下来根据可拓层次分析法构建中心区交通组织方案的评价思路,并对可拓理论关于中心区交通组织方案评价的适用性的进行描述。最后建立物元可拓评价模型,完成城市中心区交通组织方案评价的理论框架模型。
以河南省商丘市城市中心区为实例研究对象,首先分析商丘市中心区路网现状、土地利用现状及交通现状。随后针对中心区存在的交通问题等提出一套适用于商丘市中心区的交通组织方案,并以商丘市中心区路网现状交通组织作为初始方案最为对比方案,运用交通规划软件TransCAD,分配路网交通流量,并取得各项评价指标的确切数值。最后运用物元可拓评价模型,通过确切的数值显示表明交通组织方案的可取性。
During the last decades, the quantities of motor vehicles have increased a lot with a rapid increase speed which is far larger than that of the road expansion, and the requirement of transportation caused by the development of economy has exceeded the ability of supply. However, the limitation of the road resource, and the impossibility of unlimited growth have become the factors limiting the increase of traffic demand of the city center. Therefore, an optimized plan is proposed to the managers in this work.
By analyzing the performance of function, the structure of land using, transportation of the center area of the city, the characteristics of higher intensity of land using and part or all prone to traffic jams are pointed out. A method of management scheduling priority and congestion optimization based on the range is brought out based on the rule of minimum acceptable level of service, and then the details are given considering the common.
The plan of optimal traffic organization of the central area of program evaluation is evaluated with the theory of matter-element extension method. And before the evaluation, first of all, the selection of a scientific evaluation system must be summarized, and discourses at home and abroad, getting an excellent evaluation index system of traffic organization and optimization program. And then, the ideas of the evaluation of traffic organization and optimization program can be described according to the matter-element extension method. Finally, the matter-element extension model and downtown traffic organization and optimization program evaluation model are built.
Taking the center area of Shangqiu, Henan as an example, first of all, the status of the central area road network and land use and transportation are analyzed. And then a program of traffic organization and optimization for Shangqiu is worked out, and the transportation flux is calculated with TransCAD. The results are compared with that of the current traffic organization and optimization. The results show that the plan in this work will lead to a nicer one.
引文
[1]黄海军.交通行为建模—问题与机会[J].交通运输系统与工程信息, 2002, 2(1): 24-28.
[2]章辉美,谷章原.交通社会学对一门新生应用社会学的构想[J].湖南师范大学社会科学学报, 2003, 32(6): 48-52.
[3] Adolf D.May. Model for Free way Corridor Analysis[J]. TRB Special Report 194, Transportation, 2000, 27(1): 1-4.
[4] Bon-Akiya, M.Palma, A.D.,Kaysi. Dynamic network models and driver information systems[J]. Transportation Research, 1991, 25A: 251-266.
[5] Hussein Dia. An agent-based approach to modeling driver route choice behavior under the influence of real-time information[J]. Transportation Research, 2002, 25C: 331-334.
[6] Tsippy Lolan. Effects of Familiarity on Route Choice Behavior in the Presence of Information[J]. Transportation Research, 1997, 5C: 255-243.
[7] Wafaa Saleh Seona Farrell. Investigation and analysis of evidence of asymmetric churn in travel demand models[J]. Transportation Research, 2006, 12A: 671-702.
[8] Yaron Hollander. Direct versus indirect models for the effects of unreliability [R]. Transportation Research, 2006, 40A: 699-711.
[9] Haitham m.al-deek, Asadj khattak, Paramsothy thananjeyan. A combined traveler behavior and system performance model with advanced traveler information systems[J]. Transportation Research, 1998, 32A: 479-493.
[10] Kara maria, Kockelman. A model for time-and budget-constrained activity demand analysis[J]. Transportation Research, 2001, 35B: 255-269.
[11]李志瑶,隽恚才,宗芳.居民出行时间选择及拥挤收费政策[J].交通运输工程学报, 2005, 5(3): 105-110.
[12]林震,杨浩.交通信息诱导系统对出行选择的影响分析[J].交通运输系统与工程, 2002, 4: 21-24.
[13]石小法,王炜,卢林等.交通信息影响下的动态路径选择模型研究[J].公路交通科技, 2000, 17(4): 35-37.
[14]李佳,张成,范文博.私家车交通行为分析[J].交通与安全, 2000, 17(149): 97-100.
[15]关宏志,绍洁,李亚茹等.自驾车旅游交通的基础研究[J].北京工业大学学报, 2005, 31(2): 151-154.
[16] Guowei Yang. Intelligent and Modeling Conceptual Design Based on the Analysis of Matter Element Dynamic System[J]. Computer Engineering and Applications, 2005, 41(16): 109-113.
[17]邵春福.交通规划原理[M].北京:中国铁道出版社, 2004: 99-120.
[18] Dijker T, etal. Car-following under congested condition[J]. Transportation Research Board, 1998: 20-28.
[19] Frank S. Koppelmaa, Chandra Bhat, Yang D. A Self instructing Course in Mode Choice Modeling: Multinomail and Nested Logit Models[J]. TRR, 2006: 57-94.
[20]徐丽丽,郡春福.交通信息对出行者路径选择行为影响调查结果分析与研究[R].第九届多国城市交通学术会议论文集, 2005: 306-313.
[21]徐丽丽,邵春福.基于双层规划模型的路径信息诱导研究[J].交通运输工程学报, 2007, 7(5): 93-96.
[22]任福田,刘小明,荣建等.交通工程学[M].北京:人民交通出版社, 2003: 57-71.
[23]车广侠,石建军,隋莉颖. VMS交通诱导系统现状分析[J].道路交通与安全, 2006, 6(8): 19-2l.
[24]包煊,朱雪良,王义生等. VMS发布动态交通诱导信息的探讨[J].现代显示, 2006, 6: 63-65.
[25]孙宝凤,隽志才,吴文静.高速公路VMS项目社会经济影响评价研究综述[J].交通运输系统工程与信息, 2005, 5(5): l8-22.
[26]卢守峰,杨兆升,刘喜敏.基于元胞自动机的VMS诱导信息系统研究[J].交通与计算机, 2006, 24(2): 9-12.
[27]史志法.非集计模型下公交规划的调查工作研究[J].交通与运输, 2006, 7: 6-9.
[28]焦朋朋,陆化普.基于意向调查数据的非集计模型研究[J].公路交通科技, 2005, 22(6): 114-116.
[29] Cai Wen. Extension theory and its application[J]. Chinese Science Bulletin, 1999, 44(17): 1538-1548.
[30] Cai Wen, Yang Chunyan, Lin Weichu. Extension Engineering Methods[M]. Beijing: Science Press, 2003.
[31]隽志才,李志瑶,宗芳.基于活动链的出行需求预测方法综述[J].公路交通科技, 2005, 22(6): 108-113.
[32]林震,杨洁.不同条件下出行方式平衡模型及特性分析[J].管理工程学报,2004, 18(2): 30-34.
[33]罗建国.旅客交通行为分析理论与模型口[J].公路与汽车, 2002, 3(6): 72-73.
[34]颜月霞,王花兰.基于偏差最大化和信息熵定量比较多种城市交通方式的研究[J].石家庄铁道学院学报, 2006, 19(3): 89-92.
[35]马超群,王玉萍,陈宽民.城市轨道交通与常规公交之竞争模型[J].交通运输系统工程与信息, 2007, 7(3): 140-143.
[36]何瑞春,李引珍,张峻屹等.城市居民出行选择预测模型及实证研究[J].交通运输系统工程与信息, 2007, 7(6): 80-84.
[37]王方,陈金川,张德欣. SP调查在交通方式选择中的应用[J].交通运输系统工程与信息, 2007, 7(5): 90-95.
[38]姚荣涵,王殿海.模拟量子跃迁的出行方式转移模型[J].交通运输工程学报, 2007, 7(3): 111-115.
[39] Relf. Pfeifer, Hans-Jacob Liithi. Decision Support Systems and Expert Systems[M]. NJ, 3rd Prentice Hall PTRUpper Saddle River, 1993.
[40] Beulence A.J. The use of Expert Systems Technolodge in DSS[J]. Decision Support Systems, 1988, 14(4): 74-79.
[41] Shaw, M.J. Applying Machine Learning to Model Management in Decision Support Systems[J]. Decision Support Systems, 1988, 4(3): 88-92.
[42] Robert H. Bonezek, et al. Foundations of Decision Support Systems[M]. New York, Computer Engineering and Applications, 1981.
[43] Jennifer Nee, Mark E, Hallenbeck. Surveillance Option for Monitoring Arterial Traffic Condition[R]. Washington State Transportation Center (TRAC) Report No. WA-RD 510.1. June 2001: 9-13.
[44] Dowling Associates. Metropolitan Transportation Commission Travel Data Collection Pilot Project-Final Report[J], Decision Support Systems, 1995: 27-39.
[45] Dr.Peter, T.Marrtin, Yuqi Feng, XiaoDong Wang. Detector Technology Evaluation[J]. Department of Civil and Engineering University of Utah Traffic Lab. November 2003: 63-65.
[46] Bongers E A I, Viti F and Hoogendoom S P. Joint modeling of ATIS, habit and learning impacts on route choice by laboratory simulator experiments[R]. 84th Annual meeting of the Transportation Research Board, Washington DC, 2005: 1-1.
[47]王健,胡运权,安实.城市道路拥挤定价中的交通需求分析[M].数量经济技术经济研究, 2003(7): 45-46.
[48] Underwood R T·Speed. Volume and Density Relation-ships: Quality and Theory of Traffic Flow[R]. New Haven Connecticut: Yale Bureau of Highway Traffic, 1961: 141-188.
[49]胡守仁,沈青.神经网络应用技术[M].长沙:国防科技大学出版社, 1993.
[2]章辉美,谷章原.交通社会学对一门新生应用社会学的构想[J].湖南师范大学社会科学学报, 2003, 32(6): 48-52.
[3] Adolf D.May. Model for Free way Corridor Analysis[J]. TRB Special Report 194, Transportation, 2000, 27(1): 1-4.
[4] Bon-Akiya, M.Palma, A.D.,Kaysi. Dynamic network models and driver information systems[J]. Transportation Research, 1991, 25A: 251-266.
[5] Hussein Dia. An agent-based approach to modeling driver route choice behavior under the influence of real-time information[J]. Transportation Research, 2002, 25C: 331-334.
[6] Tsippy Lolan. Effects of Familiarity on Route Choice Behavior in the Presence of Information[J]. Transportation Research, 1997, 5C: 255-243.
[7] Wafaa Saleh Seona Farrell. Investigation and analysis of evidence of asymmetric churn in travel demand models[J]. Transportation Research, 2006, 12A: 671-702.
[8] Yaron Hollander. Direct versus indirect models for the effects of unreliability [R]. Transportation Research, 2006, 40A: 699-711.
[9] Haitham m.al-deek, Asadj khattak, Paramsothy thananjeyan. A combined traveler behavior and system performance model with advanced traveler information systems[J]. Transportation Research, 1998, 32A: 479-493.
[10] Kara maria, Kockelman. A model for time-and budget-constrained activity demand analysis[J]. Transportation Research, 2001, 35B: 255-269.
[11]李志瑶,隽恚才,宗芳.居民出行时间选择及拥挤收费政策[J].交通运输工程学报, 2005, 5(3): 105-110.
[12]林震,杨浩.交通信息诱导系统对出行选择的影响分析[J].交通运输系统与工程, 2002, 4: 21-24.
[13]石小法,王炜,卢林等.交通信息影响下的动态路径选择模型研究[J].公路交通科技, 2000, 17(4): 35-37.
[14]李佳,张成,范文博.私家车交通行为分析[J].交通与安全, 2000, 17(149): 97-100.
[15]关宏志,绍洁,李亚茹等.自驾车旅游交通的基础研究[J].北京工业大学学报, 2005, 31(2): 151-154.
[16] Guowei Yang. Intelligent and Modeling Conceptual Design Based on the Analysis of Matter Element Dynamic System[J]. Computer Engineering and Applications, 2005, 41(16): 109-113.
[17]邵春福.交通规划原理[M].北京:中国铁道出版社, 2004: 99-120.
[18] Dijker T, etal. Car-following under congested condition[J]. Transportation Research Board, 1998: 20-28.
[19] Frank S. Koppelmaa, Chandra Bhat, Yang D. A Self instructing Course in Mode Choice Modeling: Multinomail and Nested Logit Models[J]. TRR, 2006: 57-94.
[20]徐丽丽,郡春福.交通信息对出行者路径选择行为影响调查结果分析与研究[R].第九届多国城市交通学术会议论文集, 2005: 306-313.
[21]徐丽丽,邵春福.基于双层规划模型的路径信息诱导研究[J].交通运输工程学报, 2007, 7(5): 93-96.
[22]任福田,刘小明,荣建等.交通工程学[M].北京:人民交通出版社, 2003: 57-71.
[23]车广侠,石建军,隋莉颖. VMS交通诱导系统现状分析[J].道路交通与安全, 2006, 6(8): 19-2l.
[24]包煊,朱雪良,王义生等. VMS发布动态交通诱导信息的探讨[J].现代显示, 2006, 6: 63-65.
[25]孙宝凤,隽志才,吴文静.高速公路VMS项目社会经济影响评价研究综述[J].交通运输系统工程与信息, 2005, 5(5): l8-22.
[26]卢守峰,杨兆升,刘喜敏.基于元胞自动机的VMS诱导信息系统研究[J].交通与计算机, 2006, 24(2): 9-12.
[27]史志法.非集计模型下公交规划的调查工作研究[J].交通与运输, 2006, 7: 6-9.
[28]焦朋朋,陆化普.基于意向调查数据的非集计模型研究[J].公路交通科技, 2005, 22(6): 114-116.
[29] Cai Wen. Extension theory and its application[J]. Chinese Science Bulletin, 1999, 44(17): 1538-1548.
[30] Cai Wen, Yang Chunyan, Lin Weichu. Extension Engineering Methods[M]. Beijing: Science Press, 2003.
[31]隽志才,李志瑶,宗芳.基于活动链的出行需求预测方法综述[J].公路交通科技, 2005, 22(6): 108-113.
[32]林震,杨洁.不同条件下出行方式平衡模型及特性分析[J].管理工程学报,2004, 18(2): 30-34.
[33]罗建国.旅客交通行为分析理论与模型口[J].公路与汽车, 2002, 3(6): 72-73.
[34]颜月霞,王花兰.基于偏差最大化和信息熵定量比较多种城市交通方式的研究[J].石家庄铁道学院学报, 2006, 19(3): 89-92.
[35]马超群,王玉萍,陈宽民.城市轨道交通与常规公交之竞争模型[J].交通运输系统工程与信息, 2007, 7(3): 140-143.
[36]何瑞春,李引珍,张峻屹等.城市居民出行选择预测模型及实证研究[J].交通运输系统工程与信息, 2007, 7(6): 80-84.
[37]王方,陈金川,张德欣. SP调查在交通方式选择中的应用[J].交通运输系统工程与信息, 2007, 7(5): 90-95.
[38]姚荣涵,王殿海.模拟量子跃迁的出行方式转移模型[J].交通运输工程学报, 2007, 7(3): 111-115.
[39] Relf. Pfeifer, Hans-Jacob Liithi. Decision Support Systems and Expert Systems[M]. NJ, 3rd Prentice Hall PTRUpper Saddle River, 1993.
[40] Beulence A.J. The use of Expert Systems Technolodge in DSS[J]. Decision Support Systems, 1988, 14(4): 74-79.
[41] Shaw, M.J. Applying Machine Learning to Model Management in Decision Support Systems[J]. Decision Support Systems, 1988, 4(3): 88-92.
[42] Robert H. Bonezek, et al. Foundations of Decision Support Systems[M]. New York, Computer Engineering and Applications, 1981.
[43] Jennifer Nee, Mark E, Hallenbeck. Surveillance Option for Monitoring Arterial Traffic Condition[R]. Washington State Transportation Center (TRAC) Report No. WA-RD 510.1. June 2001: 9-13.
[44] Dowling Associates. Metropolitan Transportation Commission Travel Data Collection Pilot Project-Final Report[J], Decision Support Systems, 1995: 27-39.
[45] Dr.Peter, T.Marrtin, Yuqi Feng, XiaoDong Wang. Detector Technology Evaluation[J]. Department of Civil and Engineering University of Utah Traffic Lab. November 2003: 63-65.
[46] Bongers E A I, Viti F and Hoogendoom S P. Joint modeling of ATIS, habit and learning impacts on route choice by laboratory simulator experiments[R]. 84th Annual meeting of the Transportation Research Board, Washington DC, 2005: 1-1.
[47]王健,胡运权,安实.城市道路拥挤定价中的交通需求分析[M].数量经济技术经济研究, 2003(7): 45-46.
[48] Underwood R T·Speed. Volume and Density Relation-ships: Quality and Theory of Traffic Flow[R]. New Haven Connecticut: Yale Bureau of Highway Traffic, 1961: 141-188.
[49]胡守仁,沈青.神经网络应用技术[M].长沙:国防科技大学出版社, 1993.