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Citation |
Champahom T, Jomnonkwao S, Watthanaklang D, Karoonsoontawong A, Chatpattananan V, Ratanavaraha V. Accid. Anal. Prev. 2020; 141: e105537. |
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Affiliation |
School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand. Electronic address: vatanavongs@g.sut.ac.th. |
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Copyright |
(Copyright © 2020, Elsevier Publishing) |
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DOI |
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PMID |
32298806 |
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Abstract |
A rear-end crash is a widely studied type of road accident. The road area at the crash scene is a factor that significantly affects the crash severity from rear-end collisions. These road areas may be classified as urban or rural and evince obvious differences such as speed limits, number of intersections, vehicle types, etc. However, no study comparing rear-end crashes occurring in urban and rural areas has yet been conducted. Therefore, the present investigation focused on the comparison of diverse factors affecting the likelihood of rear-end crash severities in the two types of roadways. Additionally, hierarchical logistic models grounded in a spatial basis concept were applied by determining varying parameter estimations with regard to road segments. Additionally, the study compared coefficients with multilevel correlation model and those without multilevel correlation. Four models were established as a result. The data used for the study pertained to rear-end crashes occurring on Thai highways between 2011 and 2015. The results of the data analysis revealed that the model parameters for both urban and rural areas are in the same direction with the larger number of significant parameter values present in the rural rear-end crash model. The significant variables in both the urban and rural road segment models are the seat belt use, and the time of the incident. To conclude, the present study is useful because it provides another perspective of rear-end crashes to encourage policy makers to apply decisions that favor rules that assure safety. Language: en |
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Keywords |
Mixed effect; Multilevel model; Rear-end crash; Road segments; Thai highways |