Optimizing Tailored Bus Bridging Paths

Paper and extended abstract authored by Wei Gu, Jie Yu, Yuxiong Ji, Jeroen P.T. van der Gun, Adam J. Pel, H. Michael Zhang and Bart van Arem in 2018.

Conference contribution number 18-05145 presented at the 97th Transportation Research Board Annual Meeting (TRB 2018) in Washington, D.C. on 7–11 January 2018.

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Metro disruptions due to unexpected events reduce transit system reliability, resulting in significant productivity loss and long passenger delays. Bus bridging strategy is often used to connect stations affected by metro disruptions such that passengers could continue their journey. The literature usually designed bridging routes and then allocated buses to designed routes with specific frequencies. The restriction that each bus can only operate on a route greatly limits the service flexibility and decreases operation efficiency. We propose a flexible bus bridging strategy to deal with the disruptions of metro networks. The proposed strategy optimizes a tailored bridging path for each bus. The path dictates the stations that a bus should visit in sequence once it is dispatched from the depot. A two-stage model that balances the needs of transit agency and passengers is developed to optimize the tailored bridging paths based on affected metro stations, reserved buses, bus capacity, passenger demands and bus travel times. The Stage I model produces schematic bridging paths by minimizing the maximum bus bridging time. The Stage II model further details the paths by minimizing average passenger delay. The superiority of the proposed strategy to a traditional strategy is demonstrated in a case study in Rotterdam, The Netherlands.

Keywords: bus bridging, metro network disruptions, tailored bridging paths, two-stage model, integer linear programming.

Citation: Gu, W., Yu, J., Ji, Y., Van der Gun, J.P.T., Pel, A.J., Zhang, H.M., Van Arem, B. (2018). Optimizing Tailored Bus Bridging Paths. Paper and extended abstract no. 18-05145 presented at the 97th Transportation Research Board Annual Meeting (TRB 2018). Washington, D.C., 7–11 January.