考虑等待忍耐时间的电动自行车违规行为研判

doi:10.13229/j.cnki.jdxbgxb.20221516

Abstract

Abstract:

By introducing the survival analysis， the waiting tolerance time of non-violation and violation electric bicycle riders was taken as deleted and complete data respectively. The violation rate function of electric bicycles was developed to estimate the violation rate under the influence of single factor. Secondly， part of the waiting time was assumed with a distributed form， and a Cox proportional risk regression model was proposed that integrated the characteristics of parametric and non-parametric methods to describe the violations of electric bicycle under the influence of multiple factors. The waiting behavior data of 1 335 non-motor vehicles were extracted， and by using the product limit estimation method， the violation rate function of electric vehicles under the influence of gender， age and non-motor vehicle type was obtained. The results showed that the violation rate of middle-aged and elderly riders is higher than that of young riders； the violation rate of female riders is higher with the waiting time is less than 25 s； the violation rate of electric bicycles is higher than that of traditional bikes and e-tricycles when the waiting time is less than 44 s or between 88 s and 100 s. Unlike the "bandwagon" effect of traditional bicycle violations， when the non-motorized lanes are narrow or the group size is large enough， electric bicycle violations can be suppressed. The escort and dedicated left turn phase can effectively reduce the violation rate of electric bicycles.

Key words: urban traffic, electric bicycle, waiting tolerance time, violation behavior, proportional risk regression model

CLC Number:

U491.1

Chun-jiao DONG,Yu-xiao LU,She-qiang MA,Peng-hui LI. Identification of E⁃bike violation behaviors by considering waiting tolerance time[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(9): 2540-2546.

Figures/Tables 5

Table 1

Fig.1

Table 2

Table 3

Fig.2

References 12

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类型	最大值/s	平均值/s	标准差
电动自行车	99.00	10.14	21.02
传统自行车	104.00	14.92	28.83
电动三轮车	72.00	22.44	24.12

类别	影响因素	等待忍耐时间分位数值/s
类别	影响因素	50%分位数	75%分位数
性别	男	－	28
性别	女	－	14
年龄	青年（＜30岁）	－	45
年龄	中老年（≥30岁）	－	16
非机动车类别	电动自行车	－	23
	传统自行车	104	68
	电动三轮车	72	45

影响因素	系数估计	显著性	Exp（B）	95%置信区间
影响因素	系数估计	显著性	Exp（B）	下限	上限
红灯时长/s	0.019	0.000	1.019	1.010	1.029
协管员（有/无）	-0.467	0.036	0.627	0.405	0.971
左转相位（有/无）	-1.103	0.000	0.332	0.212	0.519
非机动车道宽度/m	0.467	0.000	1.596	1.262	2.019
组群规模（5~10/<5）	-0.620	0.000	0.538	0.393	0.737
组群规模（>10/<5）	-0.809	0.000	0.445	0.308	0.643
机动车交通量（pcu/进口道/h）	-0.001	0.033	0.999	0.999	1.000

Identification of E⁃bike violation behaviors by considering waiting tolerance time

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