Effect of Regional Characteristics on Injury Severity in Local Bus Crashes

Abstract

As the importance of public transportation increases, the management of bus-involved crashes has become a crucial issue for traffic safety. However, there are relatively few studies on crash severity for buses in South Korea. This study investigated factors that influence the severity of injuries that occur in local bus crashes. The study used commercial vehicle crash data from a 5-year period from 2010 through 2014 in South Korea. To determine unobserved regional effects on crash severity, a hierarchical ordered model was applied to the analysis. Individual crash characteristics were set to lower-level variables, and regional characteristics were adopted as upper-level variables. At the lower level, the factors affecting severity of injuries included vehicle speed, vehicle age, road alignment, surface status, road class, and traffic light installation, as found in previous studies. At the upper level, the factors included pavement, emergent medical environment, traffic rate of compliance, and ratio of elderly in the community. There was a 5.1% unobserved variation between regions from the intraclass correlation analysis. The validity of a hierarchical model for local bus crashes was verified by applying the model to other long-distance buses, and it appeared there were no regional effects. This study found a regional effect for local bus crash severity, and thus this factor is important when developing prevention plans to reduce local bus crashes. These results contribute to the study of traffic safety.

Injury Severity of Bus–Pedestrian Crashes in South Korea Considering the Effects of Regional and Company Factors

“…There is growing interest in the use of multi-level models to analyze hierarchically structured traffic crash data, and these models are often referred to as hierarchical models [1,[7][8][9][10][11][12][13][14][15]. Two research studies have summarized the use of multi-level analysis of traffic crash data and suggested further studies [14,15].…”

“…In this paper, we briefly described the specification of a two-level multi-level model. Yoon et al (2017) provided a detailed description of the model [1]. We applied a random intercept model that has been used extensively in previous studies.…”

“…Crashes that involve buses are known to result in serious injuries due in part to their physical characteristics, e.g., heavy weight, large size, and maneuvering restrictions, such as a large minimum turning radius [1]. In South Korea, according to the data on vehicle crashes in 2015, the fatalities that occurred in bus crashes represented 2.2% of the total fatalities, which was slightly more than double the number of fatalities that occurred in taxi crashes.…”

“…These factors may be affected by the safety management practices of companies. In addition, the characteristics of the region where the crash occurred also can affect bus-pedestrian crashes, and some studies have focused on the regional effects on bus-pedestrian crashes [1,7]. Therefore, bus-pedestrian crashes can be affected by the crash level factors, the characteristics of the company, and the characteristics of the region.…”

“…Some research results have indicated that traffic crash data have a hierarchical structure, usually focused on geographical or regional effects, and multi-level modeling should be used to account for group-level factors [1,[7][8][9][10][11][12][13][14][15]. Concerning the severity of the injuries in bus or pedestrian crashes, two-level models were used to account for the correlation of the crashes in a defined region [1,7]. These models set the crash level factors to a lower level (i.e., individual or level 1 factors) and the regional group factors to a higher level (i.e., group or level 2 factors).…”