Evaluation of Bus Operation Reliability and Analysis of Influencing Factors Based on Travel Time

Bus operation is subject to various internal and external factors. To accurately evaluate bus operation reliability and quantitatively analyze the influencing factors. this study calculated the interval travel time based on bus arrival time data. It established a bus operation reliability evaluation method that can reflect the impact of unreasonable delays and the variability of interval travel time by calculating the dynamic threshold probability and coefficient of variation and normalization processing. This method achieves horizontal and vertical comparison of bus operation reliability for different routes and different time periods, solving the problem that the bus operation reliability evaluation method based on schedule deviation is not applicable to high-frequency service bus routes. To address the limitations of existing research, which primarily focuses on single-factor considerations and qualitative analysis, eight influencing factors of bus operation reliability are constructed from perspectives such as station passenger flow, bus route and stop attributes, and road conditions. A Random Forest model is utilized to develop an impact model for bus operation reliability, and its accuracy is compared with that of support vector machine (SVM) and back propagation (BP) Neural Network model. This study used relative importance analysis with partial dependence plots to quantitatively identify key factors and reveal the impact mechanisms. The study uses multi-source bus data from 9 bus routes in Beijing from January 2019 for empirical analysis. The results show that the proposed evaluation method is effective in accurately identifying unreliable bus operations during morning and evening peak hours. The accuracy of the impact model constructed using random forest (RF) is the highest, with improvements of 20.38% and 49.88% compared to SVM and BP Neural Networks, respectively. Key factors influencing reliability include bus stop spacing, bus section speed, and the proportion of dedicated bus lanes, with relative importance values of 26.9%, 25.1%, and 24.1%, respectively. Additionally, the model reveals the nonlinear impact mechanisms of each factor and determines effective threshold intervals. When bus stop spacing is between 600 and 800 m, reliability improves by approximately 12.5% compared to 250 meters. Bus reliability is positively correlated with section speed, with a maximum improvement of around 7%. When the proportion of dedicated bus lanes exceeds 60%, reliability significantly improves, with an increase of about 6.5% when the proportion reaches 95%. Conversely, when the number of signalized intersections along a route increases from 1 to 3, reliability decreases by approximately 4%. To maintain stable reliability, no more than three bus routes should serve the same bus stop.