Development of a Comprehensive Safety Evaluation Mechanism for the Highway Bus Industry

Abstract

A suitable mechanism for evaluating the safety of the highway bus industry is crucial for ensuring public transportation safety in a country. In this study, we have combined indices from the Compliance Safety Accountability (CSA) program of the Federal Motor Carrier Safety Administration (FMCSA) in the US, the safety evaluation of renting buses in Japan, and some existing safety evaluation methods in Taiwan to develop a new safety evaluation mechanism for the highway bus industry. This paper introduces a two-stage decision making approach that includes the use of fuzzy analytic hierarchy process (Fuzzy AHP) and machine learning techniques such as decision trees, support vector machines, and random forests to develop this mechanism. The data used in this research were collected from the internet and directly from highway bus transportation companies. We calculated the safety performance of each company and assigned them different safety ranks. Compared with the causes of accidents in Taiwan, the results of this study showed that work hours, driver fitness, and administrative penalties are the three most important sub-attributes that affect the safety rank of the company.