Coordinated Operation of Fixed-Route and Demand-Responsive Feeder Transit Services in a Travel Corridor
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 2
Abstract
With the wide use of smartphone travel apps, a new hybrid transit system (HTS) that integrates fixed-route transit (FRT) and app-based demand-responsive feeder transit (DRFT) services have recently emerged in many cities over the world. App-based DRFT services are coordinated with FRT to offer fast, comfortable, and well-connected mobility services to travelers. The study investigates a new variant of HTS, termed flexible HTS (FHTS), allowing FRT to have flexible vehicle departure times and capacitated vehicle loads and DRFT to have flexible feeder stations, so as to further enhance the coordination between FRT and DRFT. The coordinated operation optimization problem of such an FHTS in a travel corridor is formulated as a mixed-integer linear programming model. A novel hybrid metaheuristic algorithm is developed to solve it. In the hybrid algorithm, a constrained compass search method is used to optimize FRT vehicle departure times, and an adaptive large neighborhood search algorithm, coupled with a tailored forward time slack algorithm, is applied to solve the DRFT routing and scheduling problems. A case study in Shucheng County, China is conducted to examine the performance of the model and solution algorithms. Sensitivity analyses on feeder station layout and vehicle size are also conducted. The results show that flexible FRT vehicle departure times and flexible DRFT feeder stations have a great potential of enhancing the coordination of FRT and DRFT services by reducing operators’ costs and passengers’ total travel time. Managerial implications are to set feeder transit stations downstream of an FRT line and to keep a reasonable station spacing.
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Data Availability Statement
The data applied to support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 2022JBMC045) and the National Natural Science Foundation of China (Grant Nos. 72271018 and 61903311).
References
Aldaihani, M., and M. M. Dessouky. 2003. “Hybrid scheduling methods for paratransit operations.” Comput. Ind. Eng. 45 (1): 75–96. https://doi.org/10.1016/S0360-8352(03)00032-9.
Alonso-González, M. J., T. Liu, O. Cats, N. Van Oort, and S. Hoogendoorn. 2018. “The potential of demand-responsive transport as a complement to public transport: An assessment framework and an empirical evaluation.” Transp. Res. Rec. 2672 (8): 879–889. https://doi.org/10.1177/0361198118790842.
Audet, C., and J. E. Dennis. 2003. “Analysis of generalized pattern searches.” SIAM J. Optim. 13 (3): 889–903. https://doi.org/10.1137/S1052623400378742.
Audet, C., and J. E. Dennis. 2006. “Mesh adaptive direct search algorithms for constrained optimization.” SIAM J. Optim. 17 (1): 188–217. https://doi.org/10.1137/040603371.
Chen, M. C., Y. H. Hsiao, R. H. Reddy, and M. K. Tiwari. 2016. “The self-learning particle swarm optimization approach for routing pickup and delivery of multiple products with material handling in multiple cross-docks.” Transp. Res. Part E Logist. Transp. Rev. 91 (Jul): 208–226. https://doi.org/10.1016/j.tre.2016.04.003.
Chen, X., Y. Wang, and X. Ma. 2021. “Integrated optimization for commuting customized bus stop planning, routing design, and timetable development with passenger spatial-temporal accessibility.” IEEE Trans. Intell. Transp. Syst. 22 (4): 2060–2075. https://doi.org/10.1109/TITS.2020.3048520.
Conn, A. R., K. Scheinberg, and L. N. Vicente. 2009. Introduction to derivative-free optimization. Philadelphia, PA: Society for Industrial and Applied Mathematics.
Dikas, G., and I. Minis. 2018. “Scheduled paratransit transport enhanced by accessible taxis.” Transp. Sci. 52 (5): 1122–1140. https://doi.org/10.1287/trsc.2017.0806.
Drexl, M. 2012. “Synchronization in vehicle routing: A survey of VRPs with multiple synchronization constraints.” Transp. Sci. 46 (3): 297–316. https://doi.org/10.1287/trsc.1110.0400.
Ghilas, V., J.-F. Cordeau, E. Demir, and T. V. Woensel. 2018. “Branch-and-price for the pickup and delivery problem with time windows and scheduled lines.” Transp. Sci. 52 (5): 1191–1210. https://doi.org/10.1287/trsc.2017.0798.
Ghilas, V., E. Demir, and T. Van Woensel. 2016a. “An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows and scheduled lines.” Comput. Oper. Res. 72 (Aug): 12–30. https://doi.org/10.1016/j.cor.2016.01.018.
Ghilas, V., E. Demir, and T. V. Woensel. 2016b. “A scenario-based planning for the pickup and delivery problem with time windows, scheduled lines and stochastic demands.” Transp. Res. Part B Methodol. 91 (Sep): 34–51. https://doi.org/10.1016/j.trb.2016.04.015.
Gkiotsalitis, K., O. Cats, and T. Liu. 2022. “A review of public transport transfer synchronisation at the real-time control phase.” Transp. Rev. (Feb): 1–20. https://doi.org/10.1080/01441647.2022.2035014.
Guo, R., W. Guan, and W. Zhang. 2018. “Route design problem of customized buses: Mixed integer programming model and case study.” J. Transp. Eng. Part A Syst. 144 (11): 04018069. https://doi.org/10.1061/JTEPBS.0000185.
Häll, C. H., H. Andersson, J. T. Lundgren, and P. Värbrand. 2009. “The integrated dial-a-ride problem.” Public Transp. 1 (1): 39–54. https://doi.org/10.1007/s12469-008-0006-1.
Ho, S. C., W. Szeto, Y.-H. Kuo, J. M. Leung, M. Petering, and T. W. Tou. 2018. “A survey of dial-a-ride problems: Literature review and recent developments.” Transp. Res. Part B Methodol. 111 (May): 395–421. https://doi.org/10.1016/j.trb.2018.02.001.
Huang, A., Z. Dou, L. Qi, and L. Wang. 2020. “Flexible route optimization for demand-responsive public transit service.” J. Transp. Eng. Part A Syst. 146 (12): 04020132. https://doi.org/10.1061/JTEPBS.0000448.
Keefer, D. L. 1973. “Simpat: Self-bounding direct search method for optimization.” Ind. Eng. Chem. Process Des. Dev. 12 (1): 92–99. https://doi.org/10.1021/i260045a018.
Kennedy, J., and R. C. Eberhart. 1995. “Particle swarm optimization.” In Proc., IEEE Int. Conf. on Neural Networks, 1942–1948. New York: IEEE.
Kolda, T. G., R. M. Lewis, and V. Torczon. 2003. “Optimization by direct search: New perspectives on some classical and modern methods.” SIAM Rev. 45 (3): 385–482. https://doi.org/10.1137/S003614450242889.
Li, X., Y. Luo, Y. Li, H. Li, and W. Fan. 2022. “A joint optimization model for designing demand responsive connectors fed by shared bikes.” Transportmetrica A: Transp. Sci. (Mar): 1–25. https://doi.org/10.1080/23249935.2022.2025949.
Li, X., and L. Quadrifoglio. 2009. “Optimal zone design for feeder transit services.” Transp. Res. Rec. 2111 (1): 100–108. https://doi.org/10.3141/2111-13.
Li, X., and L. Quadrifoglio. 2010. “Feeder transit services: Choosing between fixed and demand responsive policy.” Transp. Res. Part C Emerging Technol. 18 (5): 770–780. https://doi.org/10.1016/j.trc.2009.05.015.
Liaw, C.-F., C. C. White, and J. Bander. 1996. “A decision support system for the bimodal dial-a-ride problem.” IEEE Trans. Syst. Man Cybern. Part A Syst. Humans 26 (5): 552–565. https://doi.org/10.1109/3468.531903.
Liu, T., O. Cats, and K. Gkiotsalitis. 2021a. “A review of public transport transfer coordination at the tactical planning phase.” Transp. Res. Part C Emerging Technol. 133 (Dec): 103450. https://doi.org/10.1016/j.trc.2021.103450.
Liu, T., and A. Ceder. 2015. “Analysis of a new public-transport-service concept: Customized bus in China.” Transp. Policy 39 (Apr): 63–76. https://doi.org/10.1016/j.tranpol.2015.02.004.
Liu, T., A. Ceder, R. Bologna, and B. Cabantous. 2016. “Commuting by customized bus: A comparative analysis with private car and conventional public transport in two cities.” J. Public Transp. 19 (2): 55–74. https://doi.org/10.5038/2375-0901.19.2.4.
Liu, X., X. Qu, and X. Ma. 2021b. “Improving flex-route transit services with modular autonomous vehicles.” Transp. Res. Part E Logist. Transp. Rev. 149 (May): 102331. https://doi.org/10.1016/j.tre.2021.102331.
Ma, C., C. Wang, and X. Xu. 2020. “A multi-objective robust optimization model for customized bus routes.” IEEE Trans. Intell. Transp. Syst. 22 (4): 2359–2370. https://doi.org/10.1109/TITS.2020.3012144.
Ma, T., S. Rasulkhani, J. Y. Chow, and S. Klein. 2019. “A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers.” Transp. Res. Part E Logist. Transp. Rev. 128 (Aug): 417–442. https://doi.org/10.1016/j.tre.2019.07.002.
Molenbruch, Y., K. Braekers, P. Hirsch, and M. Oberscheider. 2021. “Analyzing the benefits of an integrated mobility system using a matheuristic routing algorithm.” Eur. J. Oper. Res. 290 (1): 81–98. https://doi.org/10.1016/j.ejor.2020.07.060.
Pisinger, D., and S. Ropke. 2007. “A general heuristic for vehicle routing problems.” Comput. Oper. Res. 34 (8): 2403–2435. https://doi.org/10.1016/j.cor.2005.09.012.
Posada, M., H. Andersson, and C. H. Häll. 2017. “The integrated dial-a-ride problem with timetabled fixed route service.” Public Transp. 9 (1–2): 217–241. https://doi.org/10.1007/s12469-016-0128-9.
Posada, M., and C. H. Häll. 2020. “A metaheuristic for evaluation of an integrated special transport service.” Int. J. Urban Sci. 24 (3): 316–338. https://doi.org/10.1080/12265934.2019.1709533.
Ronald, N., R. G. Thompson, and S. Winter. 2015. “Simulating demand-responsive transportation: A review of agent-based approaches.” Transp. Rev. 35 (4): 404–421. https://doi.org/10.1080/01441647.2015.1017749.
Ropke, S., and D. Pisinger. 2006a. “An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows.” Transp. Sci. 40 (4): 455–472. https://doi.org/10.1287/trsc.1050.0135.
Ropke, S., and D. Pisinger. 2006b. “A unified heuristic for a large class of vehicle routing problems with backhauls.” Eur. J. Oper. Res. 171 (3): 750–775. https://doi.org/10.1016/j.ejor.2004.09.004.
Savelsbergh, M. W. 1992. “The vehicle routing problem with time windows: Minimizing route duration.” ORSA J. Comput. 4 (2): 146–154. https://doi.org/10.1287/ijoc.4.2.146.
Sayarshad, H. R., and J. Y. Chow. 2017. “Non-myopic relocation of idle mobility-on-demand vehicles as a dynamic location-allocation-queueing problem.” Transp. Res. Part E Logist. Transp. Rev. 106 (Dec): 60–77. https://doi.org/10.1016/j.tre.2017.08.003.
Shaw, P. 1998. “Using constraint programming and local search methods to solve vehicle routing problems.” In Proc., Int. Conf. on Principles and Practice of Constraint Programming, 417–431. Berlin: Springer.
Shi, Y., and R. Eberhart. 1998. “A modified particle swarm optimizer.” In Proc., IEEE World Congress on Computational Intelligence: Evolutionary Computation Proc., (Cat. No. 98TH8360), 69–73. New York: IEEE.https://doi.org/10.1109/ICEC.1998.699146.
Shrivastava, P., and M. O’Mahony. 2006. “A model for development of optimized feeder routes and coordinated schedules-A genetic algorithms approach.” Transp. Policy 13 (5): 413–425. https://doi.org/10.1016/j.tranpol.2006.03.002.
Silva, D. F., A. Vinel, and B. Kirkici. 2022. “On-demand public transit: A Markovian continuous approximation model.” Transp. Sci. 56 (3): 704–724. https://doi.org/10.1287/trsc.2021.1063.
Sivakumaran, K., Y. Li, M. J. Cassidy, and S. Madanat. 2012. “Cost-saving properties of schedule coordination in a simple trunk-and-feeder transit system.” Transp. Res. Part A Policy Pract. 46 (1): 131–139. https://doi.org/10.1016/j.tra.2011.09.013.
Steiner, K., and S. Irnich. 2020. “Strategic planning for integrated mobility-on-demand and urban public bus networks.” Transp. Sci. 54 (6): 1616–1639. https://doi.org/10.1287/trsc.2020.0987.
Stiglic, M., N. Agatz, M. Savelsbergh, and M. Gradisar. 2018. “Enhancing urban mobility: Integrating ride-sharing and public transit.” Comput. Oper. Res. 90 (Feb): 12–21. https://doi.org/10.1016/j.cor.2017.08.016.
Tian, Q., Y. H. Lin, and D. Z. Wang. 2021. “Autonomous and conventional bus fleet optimization for fixed-route operations considering demand uncertainty.” Transportation 48 (5): 2735–2763. https://doi.org/10.1007/s11116-020-10146-4.
Wang, C., C. Ma, and X. D. Xu. 2020a. “Multi-objective optimization of real-time customized bus routes based on two-stage method.” Physica A 537 (Jan): 122774. https://doi.org/10.1016/j.physa.2019.122774.
Wang, C., M. Quddus, M. Enoch, T. Ryley, and L. Davison. 2014. “Multilevel modeling of demand responsive transport (DRT) trips in Greater Manchester based on area-wide socio-economic data.” Transportation 41 (3): 589–610. https://doi.org/10.1007/s11116-013-9506-1.
Wang, D. Z., A. Nayan, and W. Y. Szeto. 2018. “Optimal bus service design with limited stop services in a travel corridor.” Transp. Res. Part E Logist. Transp. Rev. 111 (Mar): 70–86. https://doi.org/10.1016/j.tre.2018.01.007.
Wang, Z., J. Yu, W. Hao, J. Tang, Q. Zeng, C. Ma, and R. Yu. 2020b. “Two-step coordinated optimization model of mixed demand responsive feeder transit.” J. Transp. Eng. Part A Syst. 146 (3): 04019082. https://doi.org/10.1061/JTEPBS.0000317.
Wardman, M. R. 2004. “Public transport values of time.” Transp. Policy 11 (4): 363–377. https://doi.org/10.1016/j.tranpol.2004.05.001.
Weinreich, D. P., S. M. Reeves, A. Sakalker, and S. Hamidi. 2020. “Transit in flex: Examining service fragmentation of app-based, on-demand transit services in Texas.” Transp. Res. Interdiscip. Perspect. 5 (May): 100060. https://doi.org/10.1016/j.trip.2019.100060.
Xiong, J., Z. He, W. Guan, and B. Ran. 2015. “Optimal timetable development for community shuttle network with metro stations.” Transp. Res. Part C Emerging Technol. 60 (Nov): 540–565. https://doi.org/10.1016/j.trc.2015.10.007.
Yang, H., Z. Zhang, W. Fan, and F. Xiao. 2021. “Optimal design for demand responsive connector service considering elastic demand.” IEEE Trans. Intell. Transp. Syst. 22 (4): 2476–2486. https://doi.org/10.1109/TITS.2021.3054678.
Yu, S., J. Puchinger, and S. Sun. 2020. “Two-echelon urban deliveries using autonomous vehicles.” Transp. Res. Part E Logist. Transp. Rev. 141 (Sep): 102018. https://doi.org/10.1016/j.tre.2020.102018.
Yu, Y., R. B. Machemehl, and C. Xie. 2015. “Demand-responsive transit circulator service network design.” Transp. Res. Part E Logist. Transp. Rev. 76 (Apr): 160–175. https://doi.org/10.1016/j.tre.2015.02.009.
Zhang, J., D. Z. Wang, and M. Meng. 2017. “Analyzing customized bus service on a multimodal travel corridor: An analytical modeling approach.” J. Transp. Eng. Part A Syst. 143 (11): 04017057. https://doi.org/10.1061/JTEPBS.0000087.
Zhang, W., D. Xia, T. Liu, Y. Fu, and J. Ma. 2021. “Optimization of single-line bus timetables considering time-dependent travel times: A case study of Beijing, China.” Comput. Ind. Eng. 158 (4): 107444. https://doi.org/10.1016/j.cie.2021.107444.
Zhao, J., S. Sun, and O. Cats. 2021. “Joint optimization of regular and demand-responsive transit services.” Transportmetrica A: Transp. Sci. (Oct): 1–24. https://doi.org/10.1080/23249935.2021.1987580.
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© 2022 American Society of Civil Engineers.
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Received: Apr 28, 2022
Accepted: Sep 28, 2022
Published online: Nov 26, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 26, 2023
ASCE Technical Topics:
- Algorithms
- Analysis (by type)
- Continuum mechanics
- Dynamic loads
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Hybrid methods
- Infrastructure
- Mathematics
- Methodology (by type)
- Models (by type)
- Optimization models
- Routing (transportation)
- Sensitivity analysis
- Solid mechanics
- Structural dynamics
- Traffic engineering
- Transportation corridors
- Transportation engineering
- Transportation management
- Travel demand
- Vehicle loads
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