兰州市交通拥堵研究
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摘要
以兰州市为例,从导致兰州市交通拥堵的一系列因素入手,运用因子分析法提取公因子,再利用聚类分析发掘各路口之间的相关性。运用主成分分析法提取主成分,通过对比总结造成兰州市交通拥堵的深层次原因。因子分析法提取出的两个公共因子分别为地形因子和车量因子,表明其对兰州市交通状况影响较大。主成分分析结果表明,机动车流量、非机动车流量、引道延误的累积贡献率分别为43. 771 2%,37. 655 8%,10. 336 5%。两者的分析结果都表明,地形和车流量是制约兰州市交通发展的主要因素。
Taking Lanzhou City as an example,starting from a series of factors that cause traffic congestion in Lanzhou City,factor analysis is used to extract common factors,and then cluster analysis is used to explore the correlation between intersections. The principal component analysis method is used to extract the principal components,and the deep-seated causes of traffic congestion in Lanzhou City is summarized. The two common factors extracted by the factor analysis method are the terrain factor and the vehicle factor,indicating that it has a greater impact on the traffic conditions in Lanzhou City. The results of principal component analysis show that the cumulative contribution rates of motor vehicle flow,non-motor vehicle flow,and approach delay are43. 771 2%,37. 655 8%,and 10. 336 5% respectively. Both of the analysis results indicate that the terrain and traffic flow are the main factor restricting the development of traffic in Lanzhou City.
Taking Lanzhou City as an example,starting from a series of factors that cause traffic congestion in Lanzhou City,factor analysis is used to extract common factors,and then cluster analysis is used to explore the correlation between intersections. The principal component analysis method is used to extract the principal components,and the deep-seated causes of traffic congestion in Lanzhou City is summarized. The two common factors extracted by the factor analysis method are the terrain factor and the vehicle factor,indicating that it has a greater impact on the traffic conditions in Lanzhou City. The results of principal component analysis show that the cumulative contribution rates of motor vehicle flow,non-motor vehicle flow,and approach delay are43. 771 2%,37. 655 8%,and 10. 336 5% respectively. Both of the analysis results indicate that the terrain and traffic flow are the main factor restricting the development of traffic in Lanzhou City.
引文
[1]李文生.兰州市交通拥堵及对策研究[D].天津:天津大学,2013.
[2]郭继孚,刘莹,余柳.对中国大城市交通拥堵问题的认识[J].北京交通发展研究中心,2011,9(2):8-15.
[3]杨浩雄,李金丹,张浩,等.基于系统动力学的城市交通拥堵治理问题研究[J].系统工程理论与实践,2014,34(8):2135-2145.
[4]WEN Huimin,SUN Jianping,ZHANG Xi.Study on traffic congestion patterns of large city in China taking Beijing as an example[J].Procedia-Social and Behavioral Sciences,2014,138:482-491.
[5]谢素华,林小平,黄崇伟,等.基于因子分析的西部交通科技项目评价指标体系降维处理[J].公路交通科技,2009,26(4):148-153.
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[7]李琦,姜桂艳,杨聚芬.基于因子分析与聚类分析的交通事件自动检测算法融合[J].吉林大学学报(工学版),2012,42(5):1191-1197.
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[9]温瑞英,王红勇.基于因子分析和K-means聚类的空中交通复杂性评价[J].太原理工大学学报,2016,47(3):384-404.
[10]姚佼,徐洁琼,韩印.基于聚类分析的城市交通TOD优化控制方法[J].交通运输工程学报,2014,14(6):110-116.
[11]何兆成,周亚强,余志.基于数据可视化的区域交通状态特征评价方法[J].交通运输工程学报,2016,16(1):33-140.
[12]薛薇.SPSS统计分析方法及应用[M].北京:电子工业出版社,2004.
[13]陈一,唐飞,李铁刚,等.因子分析法在质谱成像数据分析中的应用[J].分析化学,2014,42(8):1099-1103.
[14]朱林波.主成分分析法在城市交通可持续发展评价中的应用[J].西华大学学报,2013,32(1):63-66.
[15]顾政华,李旭宏.基于改进主成分分析法城市交通管理规划方案评价[J].交通运输系统工程与信息,2004,4(2):51-56.
[16]HUA Shaoyang,WANG Junli,ZHU Yin.Cause analysis and countermeasures of Beijing City congestion[J].Procedia-Social and Behavioral Sciences,2013,96:1426-1432.
[2]郭继孚,刘莹,余柳.对中国大城市交通拥堵问题的认识[J].北京交通发展研究中心,2011,9(2):8-15.
[3]杨浩雄,李金丹,张浩,等.基于系统动力学的城市交通拥堵治理问题研究[J].系统工程理论与实践,2014,34(8):2135-2145.
[4]WEN Huimin,SUN Jianping,ZHANG Xi.Study on traffic congestion patterns of large city in China taking Beijing as an example[J].Procedia-Social and Behavioral Sciences,2014,138:482-491.
[5]谢素华,林小平,黄崇伟,等.基于因子分析的西部交通科技项目评价指标体系降维处理[J].公路交通科技,2009,26(4):148-153.
[6]殷继旺.基于多个城市因子分析模型的北京市交通拥堵治理策略研究[D].北京:北京交通大学,2012.
[7]李琦,姜桂艳,杨聚芬.基于因子分析与聚类分析的交通事件自动检测算法融合[J].吉林大学学报(工学版),2012,42(5):1191-1197.
[8]FENG Y L.AFFONSO R C,ZOLGHADRI M.Analysis of bike sharing system by clustering:The Vélib'case[J].IFAC Papers on line,2017,50(1):12422-12427.
[9]温瑞英,王红勇.基于因子分析和K-means聚类的空中交通复杂性评价[J].太原理工大学学报,2016,47(3):384-404.
[10]姚佼,徐洁琼,韩印.基于聚类分析的城市交通TOD优化控制方法[J].交通运输工程学报,2014,14(6):110-116.
[11]何兆成,周亚强,余志.基于数据可视化的区域交通状态特征评价方法[J].交通运输工程学报,2016,16(1):33-140.
[12]薛薇.SPSS统计分析方法及应用[M].北京:电子工业出版社,2004.
[13]陈一,唐飞,李铁刚,等.因子分析法在质谱成像数据分析中的应用[J].分析化学,2014,42(8):1099-1103.
[14]朱林波.主成分分析法在城市交通可持续发展评价中的应用[J].西华大学学报,2013,32(1):63-66.
[15]顾政华,李旭宏.基于改进主成分分析法城市交通管理规划方案评价[J].交通运输系统工程与信息,2004,4(2):51-56.
[16]HUA Shaoyang,WANG Junli,ZHU Yin.Cause analysis and countermeasures of Beijing City congestion[J].Procedia-Social and Behavioral Sciences,2013,96:1426-1432.