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Assessment of Large Trucks Crash Severity on a Rural Interstate Road in Wyoming Using Decision Trees and Structural Equation Model
| 题名： | Assessment of Large Trucks Crash Severity on a Rural Interstate Road in Wyoming Using Decision Trees and Structural Equation Model |
| 正文语种： | eng |
| 作者： | Sherif M. Gaweesh;Irfan U. Ahmed;Mohamed M. Ahmed |
| 作者单位： | Dept. of Civil Engineering Univ. of North Dakota (UND) Grand Forks ND 58201||Research Center for Energy Systems Research (CESR) Tennessee Tech Univ. Cookeville TN 38505;Henningson Durham & Richardson (HRD) Engineering Inc. 10450 Holmes Rd. Kansas City MO 64131;Dept. of Civil and Architectural Engineering and Construction Management Transportation Center Univ. of Cincinnati Cincinnati OH 45221 |
| 关键词： | Truck-related crashes; Crash severity analysis; Structural equation model (SEM); Exploratory factor analysis; Confirmatory factor analysis; Latent variables; Decision trees |
| 摘要： | Promoting the safety of commercial trucks by identifying countermeasures that eliminate/reduce the effect of factors that increase the severity of truck-related crashes is crucial. Crash causal factors for rural interstate roads, located within the mountain plains, are inherently unique compared to urban interstate roads. This is due to the presence of challenging road geometry coupled with severe weather conditions and high truck traffic volumes. This study investigated Interstate 80 in Wyoming using decision trees, as a data mining approach, and structural equation model (SEM) as a latent factor modeling approach. SEM was employed to clarify the direct and indirect relationships between endogenous and exogenous variables while accounting for the variation and covariation within and between the constructed measurement models. Crash severity data were processed to account for factors affecting single vehicles and multivehicle trucks. The results showed that the interaction with surrounding traffic was the most significant latent variable affecting the crash severity of multivehicle truck crashes, while adverse weather conditions were the most significant latent variable affecting the crash severity of single-truck crashes. The results of this study highlighted the importance of increasing the situational awareness of commercial truck drivers with upcoming hazardous events. This could be performed by communicating information using variable message signs, the 511 application, the commercial vehicle operator portal (CVOP), or the connected vehicle (CV) technologies. |
| 出版年： | 2024 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 150 |
| 期： | 1 |
| 页码： | 05023008.1-05023008.15 |
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