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基于生存分析方法的非机动车闯红灯行为研究
引用本文:环梅,杨小宝,贾斌. 基于生存分析方法的非机动车闯红灯行为研究[J]. 北京理工大学学报, 2013, 33(8): 815-819
作者姓名:环梅  杨小宝  贾斌
作者单位:北京交通大学 城市交通复杂系统理论与技术教育部重点实验室,北京,100044;北京交通大学 城市交通复杂系统理论与技术教育部重点实验室,北京,100044;北京交通大学 城市交通复杂系统理论与技术教育部重点实验室,北京,100044
基金项目:国家重点基础研究发展计划(2012CB725400);国家自然科学基金资助项目(71131001,70901005,71071013);北京交通大学基本科研业务费资助课题(2012YJS067)
摘    要:研究非机动车在信号交叉口的闯红灯行为及其重要影响因素. 通过录像拍摄获取非机动车的等待忍耐时间及其影响因素数据,采用生存分析中的非参数方法建立等待时间的生存函数模型. 结果表明,等待时间越长违规率越高;约32%的非机动车几乎不等待就闯红灯,约15%的非机动车愿意等待很长时间也不闯红灯;电动车的等待忍耐时间比自行车更短;当正在等待的非机动车数越少或正在违规的越多时,非机动车的违规率越高. 

关 键 词:闯红灯  非机动车  信号交叉口  生存分析
收稿时间:2012-05-01

Red-Light Running Behavior of Non-Motor Vehicles Based on Survival Analysis
HUAN Mei,YANG Xiao-bao and JIA Bin. Red-Light Running Behavior of Non-Motor Vehicles Based on Survival Analysis[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2013, 33(8): 815-819
Authors:HUAN Mei  YANG Xiao-bao  JIA Bin
Affiliation:MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China
Abstract:The red-light running behavior of non-motor vehicles and its influential factors were presented. The waiting times of non-motor vehicles and the data of the influential variables were collected by video. Non-parameter method of survival analysis theory was used to model the waiting time. The results show that the violation inclination of most riders increases with the increasing waiting duration. About 32% of riders are at high risk of violation and low waiting time to cross the intersections. About 15% of riders are generally non-risk takers who can obey the traffic rules after waiting for 95 seconds. In addition, electric bikes may wait shorter time than common bicycles. The waiting time of riders would decrease with the smaller number of other riders that are waiting for a green when arrives, as well as the larger number of other riders that are crossing against the red light when arrives.
Keywords:crossing at a red light  non-motor vehicle  signalized intersection  survival analysis
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