高速公路转换区严重冲突识别与分析

doi:10.16265/j.cnki.issn1003-3033.2022.02.025

摘要/Abstract

摘要：

为深入探究高速公路改扩建转换区发生严重冲突的原因,使用高精度雷达采集单车实时状态数据,对单车区间初速度与加速度进行K-means聚类组合。基于聚类组合内的冲突率与路段事故率,采用Pearson系数法确定车辆的严重冲突阈值。融合转换区单车、交通流和道路因素建立二项Logistic模型,分析严重冲突因素的影响程度。结果表明:速度在45.50~85.68 km/h且加速度在-3.53~-1.31 m/s²区间,或速度在27.65~34.96 km/h且加速度在1.77~3.04 m/s²区间存在严重冲突;车型、交通量、平均速度、加速度、单位长度行驶转角对发生严重冲突概率有非常显著的影响;通过交通组织分流大型车、增大转换区圆曲线半径、设置合理的限速标志,能有效降低高速公路改扩建转换区的严重冲突风险。

关键词: 高速公路, 转换区, 严重冲突, K-means聚类, Logistic模型, 交通安全

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

丘积, 王红, 蒋若曦, 肖文彬, 常红光, 朱顺应. 高速公路转换区严重冲突识别与分析[J]. 中国安全科学学报, 2022, 32(2): 184-191.

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.

图/表 11

表1

图1

图2

表2

变量定义

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

表2

表3

表4

表5

自变量离散化

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

表5

表6

平均速度和加速度哑变量

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

表6

表7

车型、交通量和单位长度行驶转角哑变量

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	—	—	—	—

表7

表8

Logistic模型拟合结果

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

表8

图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