Identification and analysis of serious conflicts in expressway transition areas

doi:10.16265/j.cnki.issn1003-3033.2022.02.025

Abstract

Abstract:

In order to further explore causes of serious conflicts in transition areas of expressway reconstruction and expansion, a high-precision radar was used to collect real-time status data of vehicles, and k-means clustering was carried out on initial velocity and acceleration of a single vehicle. Then, based on conflict rate and road accident rate in cluster combination, Pearson coefficient method was adopted to determine serious conflicts threshold, and a binomial Logistic model was established integrating factors of vehicles, traffic flow and roads in transition areas to analyze influence degree of serious conflict factors. The results show that there are serious conflicts when velocity ranges from 45.50 to 85.68 km/h, and acceleration ranges from -3.53 to -1.31 m/s² or velocity ranges from 27.65 and 34.96 km/h, and acceleration from 1.77 and 3.04 m/s². The vehicle type, traffic volume, average speed, acceleration and driving angle per unit length have significant influence on probability of conflicts, and by diverting large vehicles through traffic organization, increasing radius of circle curves in transition areas and setting reasonable speed limit signs, the probability can be effectively reduced.

Key words: expressway, transition area, serious conflict, K-means clustering, Logistic model, traffic safety

QIU Ji, WANG Hong, JIANG Ruoxi, XIAO Wenbin, CHANG Hongguang, ZHU Shunying. Identification and analysis of serious conflicts in expressway transition areas[J]. China Safety Science Journal, 2022, 32(2): 184-191.

Figures/Tables 11

Tab.1

Fig.1

Fig.2

Tab.2

Definition of variables

因素	自变量	定义
单车	$T (i)$	车型
	$v - (i)$ /(km·h^-1)	车辆i行驶的平均速度
	$v - σ (i)$ /(km·h^-1)	车辆i连续行驶时的速度标准差
	$a (i)$ /(m·s^-2)	车辆i行驶加速度
交通流	Q/(pcu·h^-1)	转换区的交通量
	$V -$ /(km·h^-1)	所有车辆的平均车速
	$V - σ$ /(km·h^-1)	所有车辆的速度标准差
	$A σ (i)$ /(m·s^-2)	车辆行驶加速度的标准差
道路	r/m	转换区圆曲线半径
道路	$φ$ /((°)·m^-1)	单位长度累计行驶转角,反映车道转弯的曲率变化
因变量	$y i$	是否存在严重冲突

Tab.2

Tab.3

Tab.4

Tab.5

Discretization of independent variables

类别	自变量	离散取值	离散判别
单车因素	$T (i)$	1	中小型车
	$T (i)$	2	大型车
	单车平均速度 $v - (i)$ /(km·h^-1)	1	[18.50,29.23)
		2	[29.23,40.5)
		3	[40.5,69.73)
		4	[69.73,86.69]
	单车平均速度标准差 $v - σ (i)$ /(km·h^-1)	1	[0.58,2.56)
		2	[2.56,6.05)
		3	[6.05,12.02)
		4	[12.02,30.67]
	加速度 $a (i)$ /(m· $s - 2$ )	1	[-3.67,-1.04)
		2	[-1.04, -0.19)
		3	[-0.19,1.81)
		4	[1.81,3.23]
类别	自变量	离散取值	离散判别
交通流因素	交通量 Q/(pcu·h^-1)	1	[380,450)
		2	[450,570)
		3	[570,652)
		4	[652,910]
	交通流平均速度 $V -$ /(km·h^-1)	1	[19.01,30.67)
		2	[30.67,45.25)
		3	[45.25,72.9)
		4	[72.9,86.11]
	交通流速度标准差 $V - σ$ /(km·h^-1)	1	[6.52,9.54)
		2	[9.54,13.03)
		3	[13.03,16.96)
		4	[16.96,19.19]
	转换区内车辆行驶加速度的标准差 $A σ (i)$ /(m· $s - 2$ )	1	[0.94,2.29)
		2	[2.29,3.14)
		3	[3.14,3.94)
		4	[3.94,5.12]
道路因素	转换区圆曲线半径 r/m	1	小
		2	中
		3	大
	单位长度累计行驶转角 φ/((°)·m^-1)	1	小
		2	中
		3	大
因变量	是否存在严重冲突 $y i$	0	不存在严重冲突
因变量	是否存在严重冲突 $y i$	1	存在严重冲突

Tab.5

Tab.6

Dummy variables of mean velocity and acceleration

平均速度哑变量	$v - (i) = 2$	$v - (i) = 3$	$v - (i) = 4$	加速度哑变量	$a (i) = 2$	$a (i) = 3$	$a (i) = 4$
X₂₁	1	0	0	X₃₁	1	0	0
X₂₂	0	1	0	X₃₂	0	1	0
X₂₃	0	0	1	X₃₃	0	0	1

Tab.6

Tab.7

Dummy variables of vehicle type, traffic volume and driving angle per unit length

车型哑变量	$T (i) = 1$	$T (i) = 2$	交通量哑变量	$Q = 2$	$Q = 3$	$Q = 4$	单位长度行驶转角哑变量	$φ = 1$	$φ = 2$	$φ = 3$
X₁₁	1	0	X₄₁	1	0	0	X₅₁	0	1	0
			X₄₂	0	1	0	X₅₂	0	0	1
			X₄₃	0	0	1	—	—	—	—

Tab.7

Tab.8

Fitting results of Logistic model

变量	β	标准差	Wald检验	自由度	显著性	优势比
$T (i) = 1$	—	—	—	1	0.000	—
$T (i) = 2$	1.354	0.675	4.021	1	0.000	3.871
$v - (i) = 1$	—	—	—	3	0.032	—
变量	β	标准差	Wald检验	自由度	显著性	优势比
$v - (i) = 2$	-0.191	0.873	0.048	1	0.000	0.826
$v - (i) = 3$	0.634	0.881	0.518	1	0.000	1.885
$v - (i) = 4$	1.152	0.910	1.602	1	0.841	3.164
$a (i) = 1$	—	—	—	3	0.000	—
$a (i) = 2$	-1.160	0.782	2.218	1	0.000	0.312
$a (i) = 3$	-1.061	0.713	2.216	1	0.000	0.346
$a (i) = 4$	0.563	3.457	0.027	1	0.879	1.756
$Q = 1$	—	—	—	3	0.000	—
$Q = 2$	0.303	0.213	2.024	1	0.000	1.354
$Q = 3$	0.516	0.165	9.795	1	0.000	1.676
$Q = 4$	-0.209	0.246	0.725	1	0.025	0.811
$φ = 1$	—	—	—	2	0.000	—
$φ = 2$	-0.268	0.022	148.263	1	0.000	0.765
$φ = 3$	-0.652	0.361	3.262	1	0.000	0.521
常量	-3.442	0.441	60.919	1	0.000	0.032

Tab.8

Fig.3

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采集工具	高精度雷达
采集时段	早高峰8—9点,晚高峰16—17点以及平峰10—11点、15—16点
采集地点	K245+844、K257+500、K277+300、 K283+500、K287+700
数据类型及数量	1 708辆车的单车长度、位置(X、Y方向)、单车速度(X、Y方向)

聚类	初速度/(km·h^-1)	加速度/(m·s^-2)
1	[18.11,27.65)	[-3.53,-1.31)
2	[27.65,34.96)	[-1.31,-0.24)
3	[34.96,45.50)	[-0.24,0.40)
4	[45.50,72.11)	[0.40,1.77)
5	[72.11,85.68]	[1.77,3.04]

初速度/(km·h^-1)	加速度/(m·s^-2)	Pearson系数	初速度/(km·h^-1)	加速度/(m·s^-2)	Pearson系数
[18.11,27.65)	[-3.53,-1.31)	0.306	[27.65,34.96)	[-3.53,-1.31)	0.412
[18.11,27.65)	[-1.31,-0.24)	0.103	[27.65,34.96)	[1.31,0.24)	0.018
[18.11,27.65)	[-0.24,0.4)	0.158	[27.65,34.96)	[0.24,-0.4)	0.149
[18.11,27.65)	[0.4,1.77)	0.133	[27.65,34.96)	[-0.4,1.77)	0.121
[18.11,27.65)	[1.77,3.04]	0.295	[27.65,34.96)	[1.77,3.04]	0.824
[34.96,45.50)	[-3.53,-1.31)	0.543	[45.50,72.11)	[-3.53,-1.31)	0.843
[34.96,45.50)	[-1.31,0.24)	0.216	[45.50,72.11)	[-1.31,-0.24)	0.690
[34.96,45.50)	[-0.24,0.4)	0.077	[45.50,72.11)	[-0.24,0.4)	0.243
[34.96,45.50)	[-0.4,1.77)	0.150	[45.50,72.11)	[0.4,1.77)	0.417
[9.71,12.64)	[1.77,3.04]	0.527	[45.50,72.11)	[1.77,3.04]	0.542
[72.11,85.68]	[-3.53,-1.31)	0.823	[72.11,85.68]	[0.4,1.77)	0.550
[72.11,85.68]	[-1.31,0.24)	0.562	[72.11,85.68]	[1.77,3.04]	0.621
[72.11,85.68]	[0.24,0.4)	0.364