Analysis of Freeway Crash Severity Based on Spatial Generalized Ordered Probit Model

doi:10.12141/j.issn.1000-565X.210758

Abstract

Abstract:

To provide a deep insight into the significant factors that affect the severity of freeway crashes, this study took the crash data from the Dongguan section of the Guang-Shen Yanjiang Freeway in China from 2014 to 2019 as the research object. Crash severity levels were divided into three categories (i.e., no injury crash, minor injury crash, severe injury or fatality crash). Accounting for spatial correlation among adjacent crashes via conditional autoregressive priors, spatial generalized ordered Probit models with different correlation distance thresholds were developed, where the crash severity was used as the dependent variable and 13 potential influencing factors were used as independent variables. The research results show that there is significant spatial correlation among crashes; the spatial generalized ordered Probit models outperform the generalized ordered Probit model and multinomial Logit model; and the spatial model with 250-meters correlation distance threshold achieves the best performance. The results of model parameter estimation reveal that the type and registered province of vehicles, the time of crash occurrence, curvature of crash location, bridge section, and crash type have significant effects on freeway crash severity. The marginal effects of these factors indicate that: as compared with crashes with cars involved only, the involvement of bus, truck and other type vehicles will increase the probability of severe injury or fatality by 3.27%, 1.53%, and 4.11%, respectively; the involvement of vehicles from other provinces will increase the probability of severe injury or fatality by 1.02%; as compared with those occurring on weekend, spring, and bridge, crashes occurring on weekdays, summer, and non-bridge sections would increase the probability of severe injury or fatality by 0.87%, 2.38%, and 0.08%, respectively; the probability of heavy casualties caused by bicycle accidents is 1.64% lower than that of multi-vehicle accidents; the probability of severe injury or fatality will decrease by 1.54% for per 1 km^-1 increase in horizontal curvature of crash location.

Key words: traffic engineering, freeway safety, spatial generalized ordered Probit model, crash severity, spatial correlation distance

CLC Number:

U491.31

HU Yucong, WEI Hu, ZENG Qiang . Analysis of Freeway Crash Severity Based on Spatial Generalized Ordered Probit Model[J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(1): 114-122.

Figures/Tables 5

Fig.1

Table 1

Table 2

Comparison of model results"

参数	估计值
参数	多项Logit模型	广义有序 Probit模型	空间广义有序 Probit模型（200 m）	空间广义有序 Probit模型（250 m）	空间广义有序 Probit模型（300 m）
$σ ?$	—	—	4.60（0.66）^1）	8.58（0.83）	5.62（0.40）
$D ˉ$	1 340	1 339	918	658	899
n_pD	34	36	323	357	334
C_DI	1 374	1 375	1 241	1 015	1 232
A_C1/%	100	100	100	100	100
A_C2/%	0.53	0.53	36.7	76.06	32.98
A_C3/%	0	0	27.59	55.17	24.14
A_{C_}_t /%	85.5	85.5	90.6	96.11	90.07

Table 2

Table 3

Table 4

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因素	变量名称	变量解释及取值	均值	标准差
车辆类型	小汽车^*1）	涉事车辆全部为小汽车时取1，否则取0	0.611	0.487
	客车	涉事车辆包含客车时取1，否则取0	0.107	0.309
	货车	涉事车辆包含货车时取1，否则取0	0.221	0.415
	其他类型车辆	涉事车辆包含其他类型车辆时取1，否则取0	0.098	0.297
发生时间	凌晨	事故发生在0：00—6：00时取1，否则取0	0.078	0.268
	上午^*	事故发生在6：00—12：00时取1，否则取0	0.271	0.445
	下午	事故发生在12：00—18：00时取1，否则取0	0.400	0.490
	晚上	事故发生在18：00—24：00时取1，否则取0	0.251	0.434
发生季节	春季^*	事故发生在2?4月取1，否则取0	0.189	0.392
	夏季	事故发生在5?7月取1，否则取0	0.311	0.463
	秋季	事故发生在8?10月取1，否则取0	0.309	0.462
	冬季	事故发生在11?1月取1，否则取0	0.191	0.393
天气情况	阴	事故发生在阴天取1，否则取0	0.060	0.237
	晴^*	事故发生在晴天取1，否则取0	0.501	0.500
	雨	事故发生在雨天取1，否则取0	0.439	0.496
其他	本省车	涉事车辆全部是本省车时取1，否则取0	0.772	0.420
	周末	事故发生在周末时取1，否则取0	0.283	0.451
	单车事故	仅1辆涉事车辆时取1，否则取0	0.520	0.500
	曲率/km^-1	事故发生地点的曲率	0.410	0.410
	坡度/%	事故发生地点的坡度	0.936	0.602
	桥梁	事故发生在桥梁上时取1，否则取0	0.863	0.344

变量	潜在伤亡倾向			轻伤与重伤亡间的阈值
变量	均值	90% BCI^2）	95% BCI	均值	90% BCI	95% BCI
单车事故	-0.80	（-1.12，-0.46）	（-1.18，-0.39）	—	—	—
本省车	-0.45	（-0.78，-0.13）	（-0.84，-0.07）	—	—	—
客车	1.09	（0.58，1.58）	（0.47，1.67）	—	—	—
货车	0.64	（0.28，1.04）	（0.21，1.13）	—	—	—
其他类型车辆	—	—	—	-0.86	（-1.35，-0.41）	（-1.45，-0.33）
周末	-0.47	（-0.87，-0.06）	（-0.96，0.02）	—	—	—
夏天	—	—	—	-0.58	（-0.98，-0.18）	（-1.08，-0.09）
曲率	-0.74	（-1.19，-0.31）	（-1.28，-0.23）	—	—	—
桥梁	1.16	（0.56，1.69）	（0.46，1.82）	0.75	（0.25，1.25）	（0.13，1.34）

变量	边际效用值/%
变量	无伤亡	轻伤	重伤或死亡
单车事故	7.58	-5.94	-1.64
本省车	4.56	-3.54	-1.02
客车	-12.33	9.06	3.27
货车	-6.69	5.16	1.53
其他类型车辆	0	-4.11	4.11
周末	4.18	-3.31	-0.87
夏天	0	-2.38	2.38
曲率	6.99	-5.45	-1.54
桥梁	-8.77	8.85	-0.08

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