基于方差异质性随机参数模型的汇合行为分析

doi:10.13229/j.cnki.jdxbgxb.20220614

Abstract

Abstract:

In order to study the merging behavior of vehicles in the interweaving area of a freeway， a random parameter model with heterogeneity in variances was used to build a vehicle lane-changing model. Seven explanatory variables that had a significant effect on lane-changing behavior statistically， extracted from NGSIM dataset， was introduced to random parameter model with heterogeneity in variances. The potential heterogeneity was explored by the model. The average margin effects were calculated to quantify the effects of explanatory variables on lane-changing behavior， and individual sample accuracy was established to compare the model accuracy. The results of the study indicate that the space headway between the merging vehicle and the putative leading vehicle， the width of the putative leading vehicle and the speed of the leading vehicle in the auxiliary lane have significant effects on lane-changing behavior， and the longitudinal position of the merging vehicle affects significantly the space headway between the merging vehicle and the putative leading vehicle. Compared with random parameter model that don't consider the variance heterogeneity and binary logit model， random parameter model with heterogeneity in variances has the highest goodness of fit and model accuracy， and can better explain the unobserved heterogeneity during the lane-changing. The results of this paper can be applied to the autonomous driving assistance system and traffic flow simulation software and can shed light on the mechanism of lane-changing behavior.

Key words: transportation safety engineering, random parameter model with heterogeneity in variance, merging behavior, freeway, interweaving area

CLC Number:

U491.2

Lan WU,Le ZHAO,Gen LI. Analysis of merging behavior based on random parameter model with heterogeneity in variances[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 883-889.

Figures/Tables 9

Fig.1

Table 1

Descriptive of candidate explanatory variables"

变量名称	变量解释
$V$ /（m·s^-1）	M车车速
$V 1$ /（m·s^-1）	PL车车速
$V 2$ /（m·s^-1）	PF车车速
$V 3$ /（m·s^-1）	L车在辅助车道上的速度
$Δ V 1$ /（m·s^-1）	M车和PL车速度差
$Δ V 2$ /（m·s^-1）	M车和PF车速度差
$Δ V 3$ /（m·s^-1）	M车和L车速度差
$Δ D$ /m	PL车与PF车纵向距离差
$Δ D 1$ /m	M车与L车车头间距
$Δ D 2$ /m	M车与PL车头间距
$Δ X 1$ /m	M车与PL车横向距离差
$Δ X 2$ /m	M车与PF车横向距离差
$L 1$ /m	PL车长度
$L 2$ /m	PF车长度
$W 1$ /m	PL车宽度
$W 2$ /m	PF车宽度
$Y$ /m	M车辅助车道上纵向位置

Table 1

Table 2

Comparison of distribution forms of random parameters"

分布形式	威布尔分布	正态分布	对数正态分布
含随机参数的变量	$Δ D 2$ ， $V 3$	$Δ D 2$ ， $V 3$ ， $W 1$	$Δ D 2$
AIC	592.4	586.2	591.7
McFadden Pseudo R²	0.551	0.558	0.550
对数似然函数值	-286.21	-282.11	-286.87

Table 2

Table 3

Table 4

Model parameter estimation results"

解释变量	二元Logit模型		随机参数模型		方差异质性随机参数模型
解释变量	系数	P值	系数	P值	系数		P值
$Δ V 1$	-0.602	0.00	-0.923	0.00	-1.033	0.00
$Δ X 2$	-1.063	0.00	-1.564	0.00	-1.672	0.00
$V 3$	-0.094	0.00	-0.108（0.080）	0.00 （0.03）	-0.125 （0.089）	0.01（0.07）
$Δ D 1$	0.016	0.00	0.021	0.00	0.021	0.03
$Y$	0.011	0.00	0.025	0.00	0.020	0.02
$Δ D 2$	0.127	0.00	0.220（0.076）	0.000 （0.00）	0.274（0.200）	0.00（0.00）
方差 $Δ D 2 : Y$	/		/		-0.018	0.01
$W 1$	-1.112	0.00	-1.590（0.562）	0.01 （0.06）	-1.964（0.631）	0.01（0.10）
常数项	5.569	0.00	7.605	0.00	8.803	0.00

Table 4

Table 5

Marginal effects of variables of random parameter model with heterogeneity in variances"

变量	边际效应/%	变量	边际效应/%
$Δ V 1$	-21.5	$Y$	6.14
$Δ X 2$	-32.18	$Δ D 2$	22.4
$V 3$ $/ Δ D 1$	-7.05/4.3	$W 1$	-21

Table 5

Fig.2

Fig.3

Fig.4

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	二元Logit 模型	随机参数模型	方差异质性随机参数模型
AIC	599.9	586.2	569.5
BIC	638.5	639.29	627.35
McFadden Pseudo R²	0.530	0.558	0.572
对数似然函数值	-291.93	-282.11	-272.73
样本精度	86.41%	87.28%	87.39%
个体样本精度	71.58%	73.99%	75.07%

Analysis of merging behavior based on random parameter model with heterogeneity in variances

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