# Accident Probability Prediction and Analysis of Bus Drivers Based on Occupational Characteristics
## 2 Literature Review  
The formation of traffic accidents is caused by a multi-factor mutual influence. As a result, the integrated roles of a transportation system and people-vehicle-road-ring any side of the anomaly are very likely to contribute to the occurrence of accidents. Buses, as an essential part of urban public transportation, tend to have a greater proportion of human factors in their accident causation. When studying the probability of accidents, most scholars' primary consideration is given to the driver's demographic characteristics such as gender, age, and driving age [8; 9]. For example, [PERSON]'s [10] study showed that a specific age (60 years and above) and driving experience (2 years or less) of bus drivers were more likely to result in their involvement in at-fault accidents. [PERSON] [9] found that bus drivers older than 55 years of age had five times more accidents than drivers younger than 35 years of age. Second, the complexity of transit drivers' work environments contributes to more stressful and worse driving conditions. Many scholars have found that fatigue and work stress conditions [11; 12], mileage [13], and working hours of the day [14] all have different degrees of influence on the risk of transit drivers. For example, [PERSON] [12] found that BRT drivers' fatigue levels and stressful working conditions were closely related to drivers' risky driving through structural equations. [PERSON] [11] found that 19% of Swedish bus drivers struggled to stay awake while driving a bus 2-3 or more times per week and that the problem of drowsiness was prevalent among Swedish urban bus drivers. However, all of the above studies tended to use analysis methods such as questionnaires, which are not conducive to the timely acquisition and analysis of relevant business information. Some research scholars have also found that similar to the risk factors of private vehicle drivers, the unsafe behaviors and historical driving records of public transit drivers affect driver risk [15; 16; 17]. For example, [PERSON] [15] selected data from the Buses in Fatal Accidents (BIFA) database in the United States, used K-means clustering to analyze the intrinsic attributes of drivers involved in fatal accidents, and categorized the public transit drivers into three clusters, which were mainly distinguished by the age of the drivers, driving violation history, and so on. [PERSON] [18] found, in the process of identifying risky public transit drivers, that the number of violations and so on has a more significant impact on the risk of public transit accidents, and the probability of accidents is lower for public transit drivers who have not had any violations. In contrast, the risk of accidents is higher for drivers who have had more than one violation. In addition to this, some scholars have recently included environmental variables factors in the prediction of bus crash severity, and the results show that road congestion conditions, road moisture conditions, and so on, are closely related to driver risk behaviors [15; 19; 20]. There has been abundant research, but there are still some limitations in exploring the influence factors of bus drivers' occupational characteristics. For example, some scholars have now considered the relationship between a bus driver's driving hours and their fatigue status. Still, this type of study has been limited to the extraction of factors based on a driver's hourly characteristics on the same day or the previous day. It is important to note that driver fatigue and burnout are not sudden; they are cumulative and gradual processes. So, whether the correlation between incremental utility and fatigue over some time can lead to transit accidents has yet to be studied. In addition, due to the uncertainty in the daily scheduling pattern of transit drivers, they experience different peak hours during the course of the day. The length of time a driver runs during peak hours will have an effect on his or her work stress or fatigue level, which has been confirmed by [PERSON] [21].