Please wait a minute...
浙江大学学报(工学版)
土木工程     
基于多类跟驰行为的车头时距混合分布模型
王福建, 戴美伟, 孙凌涛, 金盛
浙江大学 建筑工程学院,浙江 杭州 310058
Mixed distribution model of vehicle headway based on multiclass car following
WANG Fu-jian, DAI Mei-wei, SUN Ling-tao, JIN Sheng
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
 全文: PDF(1022 KB)   HTML
摘要:

基于实际的驾驶行为特性,将驾驶员的驾驶状态分为强跟驰、弱跟驰和自由流3种状态,建立能够描述这3种状态的车头时距三元混合分布模型.利用北京快速路实测数据,通过最大期望(EM)算法标定了三元混合分布模型中的参数,对3种不同驾驶行为数据进行分析.通过研究对比各个车头时距分布模型的拟合精度,结果表明,提出的车头时距混合模型的拟合结果优于威布尔分布以及对数正态分布模型.

Abstract:

Based on the characteristics of drivers psychological behavior, driving behaviors were classified into strong car-following, weak car-following and free driving state. Then a ternary mixed distribution model that can describe the headway distribution of three driving states was built. The parameters of the ternary mixture distribution model were determined by expectation maximization (EM) algorithm through a case study of Beijing expressway, and the data of three different driving behavior were deep analyzed. Results show that the fitting precision of ternary mixed distribution model is the best compared with other Weibull and Lognormal models.

出版日期: 2015-09-10
:  U 491  
基金资助:

国家自然科学基金资助项目(51278455,51208462,61304191);浙江省重点科技创新团队资助项目(2013TD09)

通讯作者: 金盛,男,讲师     E-mail: jinsheng@zju.edu.cn
作者简介: 王福建(1969-),男,副教授,从事交通控制的研究. E-mail: ciewfj@zju.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

王福建, 戴美伟, 孙凌涛, 金盛. 基于多类跟驰行为的车头时距混合分布模型[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2015.07.013.

WANG Fu-jian, DAI Mei-wei, SUN Ling-tao, JIN Sheng. Mixed distribution model of vehicle headway based on multiclass car following. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2015.07.013.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2015.07.013        http://www.zjujournals.com/eng/CN/Y2015/V49/I7/1288

[1] GARTNER N H, MESSER C, RATHI A K. Monograph on traffic flow theory [M]. Washington: The Federal Highway Administration (FHWA), 1996.
[2] JIN S, QU X, XU C, et al.  Dynamic characteristics of traffic flow with consideration of pedestrians road-crossing behavior [J]. Physica A, 2013, 392(18): 3881-3890.
[3] NAGATANI T. Chaos and headway distribution of shuttle buses that pass each other freely [J]. Physica A, 2003, 323: 686-694.
[4] 姚荣涵,王殿海,李丽丽. 机动车车头时距分布的韦布尔修正模型[J]. 吉林大学学报:工学版, 2009, 39(2): 331-335.
YAO Rong-han, WANG Dian-hai, LI Li-li. Revised Weibull revision model of headway distribution for motor-vehicle [J]. Journal of Jilin University: Engineering and Technology Edition, 2009, 39(2): 331-335.
[5] 刘江, 吕津燕, 荣建, 等. 车头时距分布模型及其在山区双车道公路的应用 [J]. 交通运输工程与信息学报, 2004, 2(4): 16-22.
LIU Jiang, LV Jin-yan, RONG Jian, et al. Headway distribution models and their application on two-lane highway in mountainous areas [J]. Journal of Transportation Engineering and Information, 2004, 2(4): 16-22.
[6] DAWSON R F, CHIMINI L A. The hyperlang probability distribution: a generalized traffic headway model [J]. Highway Research Record, 1968, 244(230): 114.
[7] TOLLE J E. The lognormal headway distribution model [J]. Traffic Engineering and Control, 1971, 13(1): 22-24.
[8] COWAN R J. Useful headway models [J]. Transportation Research, 1975, 9: 371-375.
[9] 陶鹏飞, 王殿海, 金盛.车头时距混合分布模型[J].西南交通大学学报,2011, 46(4): 633-637.
TAO Peng-fei, WANG Dian-hai, JIN Sheng. Mixed distribution model of vehicle headway [J]. Journal of Southwest Jiaotong University, 2011, 46(4): 633-637.
[10] OHTA H.Distance headway behavior between vehicles from the viewpoint of proxemics [J]. IATSS Research, 1994, 18(2): 6-14.
[11] 孟凡兴, 张良, 张伟. 驾驶员车头时距研究[J]. 工业工程管理, 2013, 18(2):131-135.
MENG Fan-xing, ZHANG Liang, ZHANG Wei. A study on drivers time headway [J]. Industrial Engineering and Management, 2013, 18(2): 131-135.
[12] TAIEB-MAIMON M, SHINAR D.Minimum and comfortable driving headways: reality versus perception [J]. Human Factors, 2001,43(1):159-172.
[13] TRB, Highway capacity manual. Special Report 209, 3th ed. [C]∥Transportation Research Board. Washington: National research Council,1994.
[14] 徐程. 基于高斯混合模型的车辆自由流速度分布 [J]. 公路交通科技, 2012, 29(8): 132-135.
XU Cheng. Distribution of vehicle free flow speeds based on Gaussian mixture model [J]. Journal of Highway and Transportation Research and Development, 2012, 29(8): 132-135.
[15] 刘曙云, 关积珍, 李元左. 基于高斯混合模型的道路交通状态特征辨识方法[J]. 中南林业科技大学学报, 2009, 29(2): 151-155.
LIU Shu-yun, GUAN Ji-zhen, LI Yuan-zuo. Method for identification of roadway traffic characteristics based on Gaussian mixture models [J]. Journal of Central South University of Forestry and Technology, 2009, 29(2): 151-155.
[16] 王殿海. 交通流理论[M]. 北京: 人民交通出版社, 2002: 13-19.

[1] 倪玲霖, 张帅超, 陈喜群. 基于手机信号令数据的居民出行空间效应[J]. 浙江大学学报(工学版), 2017, 51(5): 887-895.
[2] 曲昭伟, 曹宁博, 陈永恒, 白乔文, 康萌, 陈明涛. 信号交叉口的行人信号提前建模[J]. 浙江大学学报(工学版), 2017, 51(3): 538-544.
[3] 王韩麒, 陈红, 冯微, 刘玮蔚. 基于CPT的异质通勤者多维出行决策模型[J]. 浙江大学学报(工学版), 2017, 51(2): 297-303.
[4] 王福建, 龚成宇, 马东方, 郭伟伟, 王殿海. 采用交通出行量数据的多点联动瓶颈控制方法[J]. 浙江大学学报(工学版), 2017, 51(2): 273-278.
[5] 于谦, 李铁柱, 任彦铭. 乘客载重量对柴油公交车尾气排放影响分析[J]. 浙江大学学报(工学版), 2016, 50(10): 2009-2017.
[6] 付凤杰,龚越,王殿海,马东方. 基于高清智能卡口路段行程时间的数据质量分析[J]. 浙江大学学报(工学版), 2016, 50(9): 1761-1767.
[7] 王力,张立立,潘科,李正熙. 基于状态可控性分析的交叉口信号切换控制[J]. 浙江大学学报(工学版), 2016, 50(7): 1266-1275.
[8] 李明达,隗海林,门玉琢,包翠竹. 基于实际换挡规律的卡车列队行驶起步控制[J]. 浙江大学学报(工学版), 2016, 50(5): 887-892.
[9] 楼齐峰, 马晓龙, 叶盈, 梅振宇. 基于出行成本的停车收费和供给政策影响分析[J]. 浙江大学学报(工学版), 2016, 50(2): 257-264.
[10] 王卫东,李俊杰,王京,傅庆湘,康文泓. 基于未确知测度的公路交通效率评价[J]. 浙江大学学报(工学版), 2016, 50(1): 48-54.
[11] 李清,胡志华. 基于多目标遗传算法的灾后可靠路径选择[J]. 浙江大学学报(工学版), 2016, 50(1): 33-40.
[12] 莫元富, 于德新, 宋军, 郭亚娟. 基于信道负载阈值的车联网信标消息生成策略[J]. 浙江大学学报(工学版), 2016, 50(1): 21-26.
[13] 马明辉,杨庆芳,梁士栋,邢茹茹. 高速公路主线瓶颈区域的协调控制模型[J]. 浙江大学学报(工学版), 2015, 49(9): 1700-1706.
[14] 周旦, 马晓龙, 金盛, 王殿海. 混合非机动车交通流超车次率影响因素模型[J]. 浙江大学学报(工学版), 2015, 49(9): 1672-1678.
[15] 赵伟明, 王殿海, 朱文韬, 戴美伟. 基于改进NJW算法的交通控制时段划分[J]. 浙江大学学报(工学版), 2014, 48(12): 2259-2265.