Kim, K.; Hong, J. Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model. Sustainability2023, 15, 13131.
Kim, K.; Hong, J. Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model. Sustainability 2023, 15, 13131.
Kim, K.; Hong, J. Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model. Sustainability2023, 15, 13131.
Kim, K.; Hong, J. Severity Predictions for Intercity Bus Crashes on Highway Using a Random Parameter Ordered Probit Model. Sustainability 2023, 15, 13131.
Abstract
As intercity buses are a mode that moves large scaled occupancy between regions, it accounts for the mode share-means for mid to long-distance movement in South Korea. However, the study on intercity bus safety needs to be more extensive, and safety policies are carried out based on traditional probability models without considering the data characteristics of bus accidents. Therefore, in this study, the Random Parameter Ordered Logit model was applied to derive fixed parameter factors that have the same effect on the severity of intercity bus accidents and random parameters that consider the heterogeneity of unique attributes by accident. It also analyzed the marginal effect of intercity bus accident severity. As a result of the study discovered that the influencing factors that reflect heterogeneity with Random Parameters were driver’s condition: drowsiness, vehicle size: medium, crash type: vehicle-pedestrian accident, road condition: wet pavement, and log form of AADT. The random parameter ordered logit model was traditionally found to be more suitable than the ordinal logit model, which only reflects fixed factors and more reliable predictions considering the heterogeneity of accident characteristics for each observation.
Keywords
intercity bus; accident; severity; probability model; random parameter; ordered logit; heterogeneity
Subject
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
