基于刷卡数据的公共自行车交通流特性研究
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摘要
传统的自行车交通流特征分析,主要采用在路段和交叉口实地观测的方法,记录自行车的到达时间、车头时距和车速,存在耗时费力、记录误差等缺点.本研究以南京公共自行车刷卡记录为数据来源,克服了传统调查手段的不足,以南京市典型公共自行车站点为例进行交通流特征分析.发现公共自行车的车辆到达分布服从泊松分布,车头时距在不拥挤情况下服从负指数分布;车速服从正态分布,而且在共享单车进入南京后公共自行车车速明显下降.研究结果对公共自行车运营管理和慢行交通系统改善提供了科学依据和决策支持,有利于进一步提升南京市公共自行车的服务水平.
The traditional bicycle traffic flow characteristics analysis mainly uses the method of field observations at roadside and intersections to record the arrival time of the bicycle,the headway distance and speed. It has the disadvantages of time-consuming and laborious,and recording errors. This study uses the Nanjing public bicycle smart card data. As a data source,it overcomes the shortcomings of traditional survey methods. The typical public bicycle station in Nanjing is taken as an example to analyze the traffic flow characteristics. It is found that the arrival and distribution of public bicycles obey the Poisson distribution,and the headway distance obeys the negative exponential distribution; the speed of the vehicle is normally distributed,and the speed of public bicycles has dropped significantly after the shared bicycles entered Nanjing. The research results provide a scientific basis and decision support for the improvement of public bicycle operation management,which is conducive to further upgrading the public bicycles in Nanjing.
The traditional bicycle traffic flow characteristics analysis mainly uses the method of field observations at roadside and intersections to record the arrival time of the bicycle,the headway distance and speed. It has the disadvantages of time-consuming and laborious,and recording errors. This study uses the Nanjing public bicycle smart card data. As a data source,it overcomes the shortcomings of traditional survey methods. The typical public bicycle station in Nanjing is taken as an example to analyze the traffic flow characteristics. It is found that the arrival and distribution of public bicycles obey the Poisson distribution,and the headway distance obeys the negative exponential distribution; the speed of the vehicle is normally distributed,and the speed of public bicycles has dropped significantly after the shared bicycles entered Nanjing. The research results provide a scientific basis and decision support for the improvement of public bicycle operation management,which is conducive to further upgrading the public bicycles in Nanjing.
引文
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[2]Midgley P.The role of smart bike-sharing systems in urban mobility[J].Journeys,2009,2(2):22-31.
[3]王志高,孔喆,谢建华,等.欧洲第三代公共自行车系统案例及启示[J].城市交通,2009,7(4):7-12.
[4]耿雪,田凯,张宇,等.巴黎公共自行车租赁点规划设计[J].城市交通,2009,7(4):21-29.
[5]钱俭,郑志锋,冯雨峰.杭州公共自行车设施现状调查与思考[J].规划师,2010,26(1):71-76.
[6]朱明.南京市公共自行车及其下一步发展规划[J].城市公共交通,2017(6):9-10.
[7]Xu H,Ying J,Wu H,et al.Public bicycle traffic flow prediction based on a hybrid model[J].Applied Mathematics&Information Sciences,2013,7(2):667-674.
[8]于文超.城市公共自行车系统智能调度优化算法研究[D].上海:上海交通大学,2015.
[9]钱大琳,黄迪,赵春龙,等.中国特大城市自行车到达的统计分布研究[J].数学的实践与认识,2005,35(9):67-70.
[10]刘珈铭.自行车在平面信号交叉口的行为特性研究[D].北京:北京交通大学,2005.
[11]汪金.城市信号交叉口自行车到达特性的负二项分布拟合分析[J].江苏交通科技,2011(6):30-31.
[12]魏丽英,吕凯.信号交叉口处自行车交通流的跟驰行为[J].吉林大学学报(工学版),2008,38(1):53-56.
[13]Leong H J W.The distribution and trend of free speeds on two-lane two-way rural highways in New South Wales[C]∥Australian Road Research Board(ARRB)Conference,4th,1968,Melbourne,1900.