# Research on the Optimization Method of Bus Travel Safety Considering Drivers' Risk Characteristics
## 5 Results  
The bus company aims to enhance driver safety by assessing driving risks under different extreme weather and driving periods. This is to prevent bus accidents caused by scheduling factors, so three performance measures were utilized in this study, as follows:  
1. Calculation of bus driver risk indicators: assessing driving risks for each bus driver under different conditions, particularly focusing on extreme weather situations and driving periods that warrant attention.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Symbol** & **Meaning** & **Value Range** & **Calibration Value** \\ \hline \(\theta\) & fairness tolerance/shift & \([0,5/\text{T}]\) & 1 \\ \(\varphi\) & balance tolerance/1 & \([0.18,0.22]\) & 0.2 \\ \(p_{1}\) & row exchange probability/1 & \([0,1)\) & 0.4 \\ \(p_{2}\) & column exchange probability/1 & \([0,1)\) & 0.4 \\ \(p_{3}\) & mutation probability/1 & \([0,1)\) & 0.2 \\ U & number of rows in scheduling table/shift & \(-\) & 96 \\ L & minimum sequential shifts/shift & \(-\) & 4 \\ \(T_{0}\) & initial temperature/degree & \(-\) & 1000 \\ \(\alpha\) & temperature decay coefficient/1 & \([0.9,1)\) & 0.98 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Calibration of model parameters.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Time** & **Lo** & **Lat** & **Driver ID** & **Vehicle ID** & **Line ID** & **Alarm Type** \\ \hline
7:00:10 & 119.55196 & 32.182868 & 3791 & 37006 & 31 & Forward collision \\
7:17:50 & 119.480024 & 32.18325 & 3664 & 37015 & 31 & Forward collision \\
7:40:09 & 119.541976 & 32.185138 & 3688 & 35504 & 31 & Lane Departure \\
8:24:13 & 119.488928 & 32.185848 & 3664 & 37015 & 31 & Lane Departure \\
9:07:52 & 119.472816 & 32.185544 & 3069 & 35515 & 31 & Lane Departure \\
9:37:27 & 119.461704 & 32.195846 & 3772 & 35516 & 31 & Forward collision \\ \hline \hline \end{tabular}
\end{table}
Table 3: Alarm data from bus vehicle onboard warning equipment.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Time** & **Weather** & **Temperature** & **Wind Force** & **Wind Speed** & **Humidity** & **Rainfall** & **Visibility** \\  & & (\({}^{\circ}\)**C)** & **(Scale)** & **(m/s)** & **(\%)** & **(mm)** & **(km)** \\ \hline
12:00:30 & Rain & 6 & 5 & 30 & 93 & 1.6 & 8 \\
13:00:28 & Rain & 5 & 5 & 29 & 93 & 1.2 & 12 \\
14:00:26 & Rain & 4 & 5 & 35 & 90 & 0.5 & 12 \\
15:00:27 & Snow & 3 & 5 & 31 & 93 & 0.8 & 3 \\
16:00:28 & Snow & 3 & 7 & 61 & 94 & 1.1 & 4 \\
17:00:30 & Snow & 1 & 7 & 53 & 93 & 0.8 & 3 \\
18:00:30 & Snow & 3 & 4 & 27 & 75 & 8.4 & 2 \\
19:00:30 & Snow & \(-1\) & 5 & 30 & 93 & 0.6 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Weather data.  
2. Individual safety variation of drivers: comparing the safety levels of individual bus drivers between the original scheduling plan and the optimized scheduling plan to measure the extent of improvement in individual safety values.
3. Overall change in bus operation safety: comparing the overall safety levels between the original scheduling plan and the optimized scheduling plan to evaluate the extent of improvement in system safety values.