An automatic real-time bus schedule redesign method based on bus arrival time prediction. (April 2021)

• Record Type: Journal Article
• Authors: Zhang, Xinming; Yan, Min; Xie, Binglei; Yang, Haiqiang; Ma, Hang
• Is Part Of: Advanced engineering informatics. Volume 48(2021)
• Publication Date: 2021-04
• Subjects: Bus dispatching -- Real-time schedule redesign -- Bus arrival time prediction -- Support vector regression -- Circle search algorithm; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2021.101295
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: Bus travel time often fluctuates greatly due to disturbance factors such as traffic conditions and passenger flow, which causes a reduction in the transit service as it cannot be provided as planned. Bus dispatching is necessary to handle this problem. Two crucial factors for real-time bus dispatching have been analysed in this study namely the bus arrival time prediction and timetable redesign. First, a bus arrival time prediction model combining Support Vector Regression (SVR) and Kalman Filter (K-SVR) was proposed. The headway is selected as an intermediate variable to improve the prediction accuracy by limiting the disturbance factors between two adjacent bus stops. Besides, by adjusting the parameters of the Kalman Filter, the predictive results are more suitable for practice to avoid the frequency of unnecessary timetable adjustment. Furthermore, an automatic timetable redesign method is given based on the proposed circle search algorithm, which can minimise the impact on the initial schedule by finding the minimum adjustment range in consideration of the normal working order. A case study in Shenzhen, China was conducted and the results verify that the K-SVR method could improve the prediction accuracy especially in peak hours. On this basis, in comparison with the traditional method, the timetable redesign algorithm could allocate the transit resources appropriately and perform well on indicators such as the headway fluctuation, compliance rate of headways, and schedule completeness. Moreover, it is more operable and valuable as a result of sending the departure instructions appropriately and maintaining the normal working order of drivers realistically.