A Novel Multi-Criteria Decision-Making Framework of Vehicle Structural Factor Evaluation for Public Transportation Safety  
Zhe-Fan Hou  
1 Centre for Advances in Reliability and Safety Limited (CAiR8), Hong Kong SAR, China; zhefan.houoconnect.polyu.hk (Z.-F.H. );  
transit operators, and citizens to ensure the safety of public transportation and to mitigate the negative consequences of road incidents. Human factors, vehicle factors, and environmental factors have been identified as three significant factors that contribute to public traffic safety [4,5]. Under such circumstances, regular safety inspections are essential for public transportation vehicles, such as transportation buses, transportation trains, and transportation metros, to maintain roadworthiness [6,7]. Modern vehicles have evolved into integrated complex systems. Any safety risk occurring in any system may cause the entire device to malfunction. In practice, regular inspection and maintenance in depots still rely heavily on the experience of engineers. Components within potentially faulty systems are inspected and replaced individually, resulting in unnecessary human labor and expenses. Therefore, enhancing the efficiency of maintenance management for public transportation vehicles has become a focus in both academic research and industrial applications. Prognostic and health management (PHM) issues related to public transportation vehicles have been solved using model-based, data-driven, and hybrid approaches [8, 9, 10, 11, 12, 13, 14, 15]. Some investigations assessed the health status by identifying failure factors using physical models or by extracting factors directly from sensor data using data-driven methods [8, 9, 10, 11, 12, 13]. Several studies proposed maintenance planning methods to optimize human and material resources [14, 15, 16]. However, there are three primary limitations in the existing research. Firstly, the research above predominantly relied on experimental and simulation data, which may not accurately reflect real-world vehicle conditions and incidents. Secondly, the research was based on specific fault scenario datasets that may not encompass all types of faults. Third, the research either took the vehicle as a whole unit or focused on specific structure areas. Therefore, this work aims to exhaustively evaluate failure factors throughout the entire structure of transportation vehicles, accounting for all potential failure types encountered in real-world conditions. Identifying and evaluating factors is a typical decision-making problem. Multi-Criteria Decision-Making (MCDM) technology is a commonly used decision-making method, which is suitable for this work. MCDM techniques have been widely applied across multiple disciplines. Particularly in the field of safety management within engineering fields, MCDM methods have been extensively adopted [17, 18, 19, 20, 21, 22, 23]. MCDM methods exhibit unique advantages as they can comprehensively evaluate and balance multiple criteria, including technical, economic, and social aspects. Additionally, MCDM methods integrate both quantitative and qualitative data to ensure the thoroughness of analyzation. Through the transparent and explainable decision-making process, MCDM methods enable decision-makers to manage critical risks more effectively and ultimately enhance the safety and robustness of systems. Nevertheless, only a handful of studies have utilized MCDM techniques to assess factors related to public transportation safety, and even fewer have focused on vehicle structure factors. Some studies have utilized MCDM techniques to analyze critical factors contributing to road crashes [24, 25, 26, 27, 28, 29, 30]. [PERSON] et al. [29] evaluated the crash risks associated with each route by combining safety factors, predictive models, and risk assessment techniques. [PERSON] et al. [30] investigated the traffic collision data to analyze factors about the occupant, vehicle, road, and environment. Chi-square tests assessed the potential influence of the factors.