# Research on the Optimization Method of Bus Travel Safety Considering Drivers' Risk Characteristics
## 5 Results
### Enhancing Safety Through Driver Scheduling Optimization  
Using Formula (2) to calculate the quantitative indicators of driving safety for each bus driver and analyzing the assessment values of driving safety before and after scheduling optimization, the results are shown in Figure 5. It can be seen that the safety scores of all 24 drivers have been improved to varying degrees after optimization. Especially for drivers with lower safety scores, the improvement is more significant. For drivers with original safety scores below 75, the average safety has increased by 11.08 after scheduling optimization. However, for drivers with original safety scores exceeding 80, the safety indicators have only increased by 1 to 3 after optimization. This indicates that the model prioritizes matching drivers with lower safety scores to driving conditions that suit them, thereby reducing the occurrence of extreme safety accidents. For further analysis of the optimization results, Table 6 shows the main indicators of overall driver safety. After optimization, the overall safety of bus operations has increased by 7.22%. The minimum safety value has risen from 38.80 to 62.07, and the standard deviation of safety assessment values has decreased by 33.76%. Overall, the safety of the bus scheduling plan has been effectively improved and significantly enhanced. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline
**UID** & **W1P1** & **W1P2** & **W1P3** & **W2P1** & **W2P2** & **W2P3** & **W3P1** & **W3P2** & **W3P3** & **W4P1** & **W4P2** & **W4P3** \\ \hline
01 & 81.82 & 75.77 & 81.96 & 86.57 & 78.09 & 86.34 & 85.59 & 75.46 & 85.42 & 83.07 & 76.82 & 83.14 \\
02 & 71.14 & 72.63 & 79.52 & 72.00 & 73.91 & 83.08 & 67.63 & 70.41 & 81.49 & 72.16 & 73.62 & 80.64 \\
03 & 73.57 & 69.61 & 74.44 & 81.93 & 75.91 & 82.34 & 79.88 & 72.83 & 80.59 & 82.02 & 77.41 & 82.33 \\
04 & 84.26 & 85.86 & 88.47 & 83.68 & 85.86 & 89.34 & 82.04 & 84.85 & 89.05 & 93.27 & 94.27 & 96.94 \\
05 & 34.08 & 30.06 & 35.92 & 72.55 & 63.72 & 71.56 & 68.31 & 58.12 & 67.58 & 84.16 & 76.6 & 82.61 \\
06 & 65.16 & 65.06 & 70.89 & 67.04 & 66.73 & 74.5 & 61.52 & 61.74 & 71.13 & 66.36 & 66.16 & 72.12 \\ \hline \end{tabular}
\end{table} 
Table 5: Safety database for each driver under different driving environments. It is evident that after optimization, the overall safety of bus operations has improved by 7.22%, which translates to a reduction of approximately 264 instances of abnormal speed changes per hour across the entire route, resulting in a total reduction of 44,352 instances per week. The standard deviation of the scores decreased by 6 points, indicating a more balanced overall safety level among drivers and a more reasonable scheduling scheme. The increase in the maximum score is relatively small at 1.43%, which may be due to the limited optimization scope caused by the presence of high scores in the original schedule. The minimum score has increased from 38.80 to 62.07, indicating a significant improvement in the safety of low-scored chains, thereby reducing bus safety incidents. Table 7 presents the drivers' working sequences before and after the shift scheduling optimization on 7 December 2020. This scheduling result can fulfill all the constraint conditions mentioned previously and can automatically generate a shift scheduling plan oriented towards bus operation safety. Figure 6 displays the changes in safety for each shift chain before and after the scheduling. It can be observed from the figure that the overall safety has increased from 75.5 to 86.1 after the optimization, with a significant improvement in the safety of low-safety shift chains; however, there is also a slight decrease in the safety corresponding to some shift chains. This indicates that due to the limited number of available drivers, it is not possible to ensure an increase in safety for all shift chains. Nevertheless, to guarantee the individual safety and risk balance among drivers, it is necessary to control the damage caused by individual safety reductions through penalty terms.