## 5 Conclusions and Discussion  
This paper proposes a new method for calculating the travel time reliability after the earthquake based on the analysis and feature processing of the traffic data collected by the floating vehicle. Firstly, this paper defines the relevant intermediate parameters to help convert the travel trajectory of the floating vehicle into the travel time of the target path. Secondly, the impact factors of road earthquake damage are obtained after the image  
Figure 12: Probability density of path travel time before and after earthquake. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Tc (s)**} & \multicolumn{2}{c}{**Before the Earthquake (\%)**} & \multirow{2}{*}{_Ind = 0.1 (\%)_} & \multirow{2}{*}{_ind = 0.5 (\%)_} & \multirow{2}{*}{_ind = 0.9 (\%)_} \\ \hline
1800 & 44 & 25 & 16 & 11 \\
3000 & 92 & 63 & 51 & 47 \\
6000 & 98 & 97 & 82 & 58 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Path Travel Time Reliability under Different Threshold. recognition. Besides, Bayesian average adaptive kernel density estimation method are taken many measured trajectories generated by the floating vehicle segments as the data set. Finally, the kernel density estimation method is used to weight the observed values, and the calculation formula of travel time reliability is obtained. Especially, the influence formula of the earthquake on the path travel time distribution is given. The disaster factors which is first applicated in the estimation of the travel time distribution in the research. A complete reliability calculation model of the path travel time after the earthquake is established, which can be used for relevant departments to judge the reliability of road networks and provide effective basis for improving the speed of material transportation and emergency rescue. (1) According to the track data (time stamp, crossing ratio, coverage area, etc.) of rescue vehicles and the field data analysis, the image recognition technology was used to estimate the earthquake damage condition of the field road, and the calculation formula of the travel time reliability was established based on the estimation of the post-earthquake road travel time distribution. The results show that the Bayesian mean adaptive kernel density estimation method can better estimate the post-earthquake traffic travel time. As for the earthquake damage factor, a new calculation formula is given to judge the influence degree of the earthquake damage factor on the road capacity under different earthquake damage index of 0.9, the travel time reliability of this section is only 11%. (2) After testing, the authors found that, when the threshold was determined, before the path travel time reliability reached the highest, when the threshold was 6000, the road travel time reliability reached 98%, and with the increase in the earthquake damage index, the road travel time became more and more unreliable. When the threshold was 1800, the earthquake damage. (3) Earthquake disaster factors are included in the estimation of travel time distribution in this paper, but other factors, such as the improvement of road network traffic conditions brought by road repair and temporary traffic control, also affect the accuracy of the estimation of travel time distribution after earthquake, which need further analysis and research. (4) The travel time reliability is calculated by using the floating vehicle data and VISSIM simulation data to evaluate the road travel time reliability after the earthquake. However, there is no measured value to compare and explain, to highlight the advantages of this method. Therefore, we will consider the comparison and analysis with other recent methods in the follow-up research to verify the results of the proposed mechanism. Data curation, S.W. ; Funding acquisition, Y.L. ; Investigation, M.L. ; Methodology, Y.L. and S.W. ; Supervision, M.L. ; Validation, X.Z. ; Writing--original draft, Y.L. ; Writing--review and editing, X.Z. All authors have read and agreed to the published version of the manuscript.