Factors affecting bus accident severity in Thailand: A multinomial logit model

Abstract

Bus accidents are a serious issue, with high rates of injury and fatality in Thailand. However, no studies have been conducted on the factors affecting bus accident severity in Thailand. A cross-sectional study was conducted by the Department of Highways, Thailand over the 2010–2019 period. A multinomial logit model was used to evaluate the factors associated with bus accident severity. This model divided accidents into three categories: non-injury, injury, and fatality. The risk factors consisted of three major categories: the bus driver, characteristics of the crash, and environmental characteristics. The results showed that characteristics of the bus driver, the crash, and the environment where the crash occurred all increased the probability of bus accidents causing injury. These three main factors included driving on sloped roads (relative risk ratio [RRR] 3.03, 95% confidence level [CI] 1.73 to 5.30), drowsy driving (RRR 2.60, 95% CI 1.71 to 3.96), and driving in the wrong direction (RRR 2.37, 95% CI 1.77 to 3.19). Moreover, the factors that increased the probability of the accidents causing fatality were drowsy driving (RRR 3.40, 95% CI 2.07 to 5.57) and drivers not obeying or following traffic rules (RRR 3.02, 95% CI 1.95 to 4.67), especially in the northern part of Thailand (RRR 3.01, 95% CI 1.98 to 4.62). The results can provide a valuable resource to help road authorities in development targeting road safety programs at sloped roads in the northern part of Thailand. Stakeholders should increase road safety efforts and implement campaigns, such as raising public awareness of the risks of not obeying or following traffic rules and drowsy driving which could possibly reduce the risk of both injury and fatality.

Analyzing of Total Number of Railway Accidents in Türkiye via Different Computational Models

“…Akalın explored the factors affecting the tram accident severity via Multinomial Logit Model (MNL) for the cities of Eskisehir (in Türkiye), Blackpool, London, Manchester, Nottingham and Sheffield (in England). The model results were almost the same for all cities; rail gauge width and dividedness of the roads were found to be significant parameters [10]. Iranitalab and Khattak investigated the factors affecting highway-rail grade crossing accidents; the location where the vehicular speeds high significantly impact the accident frequency [9].…”

“…Traditional models, such as the Multinomial logit model, have often been employed to establish associations between exploratory variables and accident frequency. [8][9][10], ordered regression model [11], spatial regression model [12], linear regression model [12], negative binomial regression model [13]. Akalın explored the factors affecting the tram accident severity via Multinomial Logit Model (MNL) for the cities of Eskisehir (in Türkiye), Blackpool, London, Manchester, Nottingham and Sheffield (in England).…”