# Accident Probability Prediction and Analysis of Bus Drivers Based on Occupational Characteristics
## 6 Results
### SHAP Analysis
For bus drivers above 45 years with driving experience exceeding 15 years, their SHAP values remain negative and stable, indicating a relatively low accident risk in the bus drivers. Figure 11: SHAP dependency graphs. this category. Regarding the \"Education\" feature, most bus drivers have an educational level of 1 or 2, corresponding to primary or high school education. The risk level was the lowest when the educational level was at 1. For the \"Rainfall\" feature, many samples are clustered around 0. This is related to the weather in June in Chongqing Municipality, where there was no rainfall or less rainfall for most of the time. When the rainfall was less than 0.3 mm/h, its SHAP value was mostly less than 0, and the driver's risk level was relatively low and safer. When the \"Rainfall\" was less than 0.5 mm/h (i.e., light rain or less), the driver's risk level was low. Then, as rainfall exceeded, the SHAP value increased, meaning a positive relationship between rainfall and the accident risk of bus drivers. For the \"Azimuthal Change\" feature, when the azimuthal change was less than 20, most of the SHAP values were negative, clearly showing that more minor azimuthal changes were associated with lower accident risk for bus drivers. After that, the more significant the change in azimuth, the higher the accident risk. For PDP, the plot shows that when the proportion of driving time during peak hours was less than 0.3, the SHAP values fluctuated around 0, but were mostly greater than 0, showing a positive effect on the impact of accidents. Yet, when the proportion exceeded 0.3, the SHAP values decreased. For TLV, as the value of the horizontal coordinate increased, the longer the bus driver was from the last violation. As can be seen from the figure, there was a dampening effect on bus driver risk the shorter the length of time since the previous offense (within one week). As the length of time increased, the risk of bus drivers gradually increased. However, the probability of accidents for bus drivers who had not had a violation within six months was also low. For SDEE, when the value of the entry and exit speed discrepancy was around 8, its SHAP value was less than 0, indicating that it has a particular inhibitory effect on accident risk. As the discrepancy increases and decreases, the accident risk shows an upward trend. For ADW and PDW, the cumulative driving time of bus drivers in the last week was mostly around 30 h, and their driving time per day did not vary much, with their SHAP values more centrally distributed around zero. For PDW, most of the surveyed bus drivers had some non-working days in their driving experience. The SHAP values also fluctuated around 0 and remained relatively stable. In addition, four feature combinations with significant interactions were selected to explore the interaction between bus driver accident features, as shown in Figure 12. Compared with the SHAP dependency graphs, the feature interaction graphs have a colored bar on the right side, which indicates the value of another feature interacting with the current feature. In Figure 12a, it can be seen that the higher the \"Age\" of the bus driver, the higher his or her \"Driving Experience\". In the red section on the right, higher aged drivers have negative SHAP values with high driving experience, showing a negative influence effect. Meanwhile, the blue scatter on the left shows that low driving experience has a positive SHAP for low age, showing a positive influence effect. In Figure 12b, at one month or more from the last violation (taking the values of 2, 3, and 4), the increment of PDP increased the SHAP value of the TLV, showing its positive influencing effect. Instead, when the length of time since the last violation was more than six months, the increment of PDP decreased the SHAP value of the TLV. Similarly, in Figure 12c, the increase in age increased the SHAP value of education when the education level was 2, while it had a negative effect when the education level was elementary school.