街道级小区域交通指数计算方法设计与分析
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摘要
为提高交通拥堵治理工作的精细化管理水平,并为城市内部街道社区级行政区域提供交通评价方法,解决交通运行评价指标的评价维度细化问题,设计了适用于街道级小区域的交通指数计算方法。首先总结国内外交通运行评价指标研究现状,引出城市动态交通运行的评价指标,以及对于评价指标的评价效果的判定指标。然后建立街道级小区域的交通指数计算方法,通过比较不同评价指标计算基础之间的区别,选择出了适用于评价街道级小区域的交通特征性评价指标;参考学者的研究,建立了有效样本路段的筛选准则,对评价街道级小区域城市道路网进行筛选;通过比较小区域交通运行状态的评价时间粒度,结合判定指标结果,选择出适合于街道级小区域交通运行状态评价标准的评价时间粒度;结合上述计算算法设计出小区域交通指数计算方法。最后以北京市中心城六区为例,对算法进行了案例分析,并将小区域交通指数反映出来的交通特征与街道社区的交通特征进行对比分析。案例计算结果表明:该方法可以较准确的表达街道级小区域的交通运行特征。
In order to improve the fine management level of traffic congestion control work, provide traffic evaluation method for urban administrative region of residential districts, and solve the problem of refinement of evaluation dimensions of traffic operation evaluation indicators, a traffic indicator calculation method suitable for residential districts is designed. First, we summarized the research status of traffic operation evaluation indicators at home and abroad, and introduced the evaluation indicators of urban dynamic traffic operation and the criterion of the evaluation effect of the evaluation indicators. Then, we established the calculation method of traffic indicator for residential districts, and selected the traffic characteristic evaluation indicators suitable for evaluating residential districts after comparing the difference between the calculation basises of different evaluation indicators. Referring to the researches of scholars, we established the screening criteria of effective sample sections, and screened the urban road network of the evaluated residential districts. By comparing the evaluation time granularities of traffic operation status of the residential districts and combining with the result of criterion, we selected the evaluation time granularity suitable for the evaluation criteria of traffic operation state of residential districts, and designed the calculation method of residential district traffic indicators based on the above calculation method. Finally, taking 6 districts of Beijing central city for example, we analyzed the calculation method by case study, and compared the traffic characteristics reflected by the traffic indicator of the residential districts with those of street community. The result of case calculation shows that this method can accurately express the traffic operation characteristics of residential districts.
In order to improve the fine management level of traffic congestion control work, provide traffic evaluation method for urban administrative region of residential districts, and solve the problem of refinement of evaluation dimensions of traffic operation evaluation indicators, a traffic indicator calculation method suitable for residential districts is designed. First, we summarized the research status of traffic operation evaluation indicators at home and abroad, and introduced the evaluation indicators of urban dynamic traffic operation and the criterion of the evaluation effect of the evaluation indicators. Then, we established the calculation method of traffic indicator for residential districts, and selected the traffic characteristic evaluation indicators suitable for evaluating residential districts after comparing the difference between the calculation basises of different evaluation indicators. Referring to the researches of scholars, we established the screening criteria of effective sample sections, and screened the urban road network of the evaluated residential districts. By comparing the evaluation time granularities of traffic operation status of the residential districts and combining with the result of criterion, we selected the evaluation time granularity suitable for the evaluation criteria of traffic operation state of residential districts, and designed the calculation method of residential district traffic indicators based on the above calculation method. Finally, taking 6 districts of Beijing central city for example, we analyzed the calculation method by case study, and compared the traffic characteristics reflected by the traffic indicator of the residential districts with those of street community. The result of case calculation shows that this method can accurately express the traffic operation characteristics of residential districts.
引文
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[17]刘梦涵.面向特大城市的分层次交通拥堵评价模型及算法[D].北京:北京交通大学,2009.LIU Meng-han.Stratified Traffic Congestion Measurement Model and Algorithm for Megacities[D].Beijing:Beijing Jiaotong University,2009.
[18]胡建建,曾培峰,唐莉萍,等.基于高斯低通滤波的音乐节拍提取[J].东华大学学报:自然科学版,2011,37(1):72-75,80.HU Jian-jian,ZENG Pei-feng,TANG Li-ping,et al.Music Beat Extraction Based on Low-pass Gaussian Filter[J].Journal of Donghua University:Natural Science Edition,2011,37(1):72-75,80.
[19]杜润乐.低通滤波与卡尔曼滤波相结合的制导率识别[J].哈尔滨工业大学学报,2017,49(4):66-72.DU Run-le.A LPF Enhanced Adaptive Kalman Filter for Guidance Law Recognition[J].Journal of Harbin Institute of Technology,2017,49(4):66-72.
[20]朱丽云,温慧敏,孙建平.北京市浮动车交通状况信息实时计算系统[J].城市交通,2008(1):77-80.ZHU Li-yun,WEN Hui-min,SUN Jian-ping.Floating Car Based Real-time-traffic-info Collection System in Beijing[J].Urban Transport of China,2008(1):77-80.
[2]BOARNET M G,KIM E J,PARKANY E.Measuring Traffic Congestion[J].Transportation Research Record,1998,1634:93-99.
[3]TURNER S,MARGIOTTA R,LOMAX T.Monitoring Urban Freeways in 2003:Current Conditions and Trends from Archived Operations Data[R].Washington,D.C.:Federal Highway Administration,2004.
[4]HABIB K M N.Evaluation of Planning Options to Alleviate Traffic Congestion and Resulting Air Pollution in Dhaka City[D].Dhaka:Bangladesh University of Engineering and Technology,2002.
[5]LINDLEY J.Quantification of Urban Freeway Congestion Analysis of Remedial Measures[R].Washington,D.C.:Federal Highway Administration,1987.
[6]LINDLEY J.A Methodology for Quantifying Urban Freeway Congestion[M].Washington,D.C.:Transportation Research Board,1987:1-7.
[7]LINDLEY J A.Urban Freeway Congestion:Quantification of the Problem and Effectiveness of Potential Solutions[J].ITE Journal,1987,57(1):27-32.
[8]郑淑鉴,杨敬锋.国内外交通拥堵评价指标计算方法研究[J].公路与汽运,2014(1):57-61.ZHENG Shu-jian,YANG Jing-feng.Research on Calculation Method of Traffic Congestion Evaluation Index at Home and Abroad[J].Highways&Automotive Applications,2014(1):57-61.
[9]VAZIRI M.Development of Highway Congestion Index with Fuzzy Set Models[J].Transportation Research Record,2002,2229:16-22.
[10]ISHIMARU J,HALLENBECK M,NEE J.Weekend Freeway Performance and the Use of HOV Lanes on Weekends[R].Washington,D.C.:Washington State Transportation Center,2000:1-39.
[11]LEVINSON H S,LOMAX T J.Developing a Travel Time Congestion Index[J].Transportation Research Record,1996,1564:1-10.
[12]KONG X,YANG J,YANG Z.Measuring Traffic Congestion with Taxi GPS Data and Travel Time Index[C]//15th COTA International Conference of Transportation Professionals.Beijing:Beijing Jiaotong University,2015:3751-3762.
[13]DB11/T 785-2011,城市道路交通运行评价指标体系[S].DB11/T 785-2011,Evaluation Index System for Urban Road Traffic Operation[S].
[14]DBJ440100/T 164-2013,城市道路交通运行评价指标体系[S].DBJ440100/T 164-2013,Evaluation Index System for Urban Road Traffic Operation[S].
[15]高德软件有限公司.2015年度中国主要城市交通分析报告[R].北京:高德软件有限公司,2016:1-39.Gaode Software.Traffic Analysis Report of Major Cities in China in 2015[R].Beijing:Gaode Software,2016:1-39.
[16]王璐媛,于雷,孙建平.交通运行指数的研究与应用综述[J].交通信息与安全,2016,34(3):1-9,26.WANG Lu-yuan,Yu-lei,SUN Jian-ping.An Overview of Studies and Applications on Traffic Performance Index[J].Journal of Transport Information and Safety,2016,34(3):1-9,26.
[17]刘梦涵.面向特大城市的分层次交通拥堵评价模型及算法[D].北京:北京交通大学,2009.LIU Meng-han.Stratified Traffic Congestion Measurement Model and Algorithm for Megacities[D].Beijing:Beijing Jiaotong University,2009.
[18]胡建建,曾培峰,唐莉萍,等.基于高斯低通滤波的音乐节拍提取[J].东华大学学报:自然科学版,2011,37(1):72-75,80.HU Jian-jian,ZENG Pei-feng,TANG Li-ping,et al.Music Beat Extraction Based on Low-pass Gaussian Filter[J].Journal of Donghua University:Natural Science Edition,2011,37(1):72-75,80.
[19]杜润乐.低通滤波与卡尔曼滤波相结合的制导率识别[J].哈尔滨工业大学学报,2017,49(4):66-72.DU Run-le.A LPF Enhanced Adaptive Kalman Filter for Guidance Law Recognition[J].Journal of Harbin Institute of Technology,2017,49(4):66-72.
[20]朱丽云,温慧敏,孙建平.北京市浮动车交通状况信息实时计算系统[J].城市交通,2008(1):77-80.ZHU Li-yun,WEN Hui-min,SUN Jian-ping.Floating Car Based Real-time-traffic-info Collection System in Beijing[J].Urban Transport of China,2008(1):77-80.
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