Abstract
Traditional bus service in low-demand areas is usually designed with a low frequency planning strategy, where buses have to visit all fixed bus stops even though some do not have any passenger requests. To improve its efficiency and reduce the negative impacts on the environment, a user-centered service can be conceived by integrating the bus service as a feeder to transit. We study this problem considering also the use of electric vehicles, which are currently being widely introduced for such services. However, most studies neglect the synchronization issues of the feeder service and timetabled transit to minimize customers’ waiting time at transit stations. Moreover, existing studies on electric vehicle routing problems assume charging stations to be uncapacitated. To address these issues, this study proposes an on-demand first-mile feeder service to coordinate its service with timetabled transit using electric buses/shuttles. The problem is modeled on a departure-expanded (layered) graph and formulated as a mixed-integer linear programming problem. Several new contributions are proposed in this study: considering flexible bus stops based on meeting points (within a walking distance) of customers’ origins, coordinating bus arrival times at transit stations to minimize customers’ waiting time, and coordinating electric bus charging scheduling to ensure charging station capacity constraints. We conduct numerical studies on a set of instances to validate the proposed methodology.
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References
Li, X., Quadrifoglio, L.: Feeder transit services: choosing between fixed and demand responsive policy. Transp. Res. Part C Emerg. Technol. 18, 770–780 (2010)
Wang, Y., Bi, J., Guan, W., Zhao, X.: Optimising route choices for the travelling and charging of battery electric vehicles by considering multiple objectives. Transp. Res. Part D Transp. Environ. 64, 246–261 (2018)
Ma, T.Y., Rasulkhani, S., Chow, J.Y.J., Klein, S.: A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers. Transp. Res. Part E Logist. Transp. Rev. 128, 417–442 (2019)
Chen, S., Wang, H., Meng, Q.: Solving the first-mile ridesharing problem using autonomous vehicles. Comput. Civ. Infrastruct. Eng. 35, 45–60 (2020)
Galarza Montenegro, B.D., Sörensen, K., Vansteenwegen, P.: A large neighborhood search algorithm to optimize a demand-responsive feeder service. Transp. Res. Part C Emerg. Technol. 127, 103102 (2021)
Keskin, M., Çatay, B.: Partial recharge strategies for the electric vehicle routing problem with time windows. Transp. Res. Part C Emerg. Technol. 65, 111–127 (2016)
Bongiovanni, C., Kaspi, M., Geroliminis, N.: The electric autonomous dial-a-ride problem. Transp. Res. Part B Methodol. 122, 436–456 (2019)
Cordeau, J.F., Laporte, G.: The dial-a-ride problem: models and algorithms. Ann. Oper. Res. 153, 29–46 (2007)
Häll, C.H., Andersson, H., Lundgren, J.T., Värbrand, P.: The integrated dial-a-ride problem. Public Transp. 11(1), 39–54 (2008)
Posada, M., Andersson, H., Häll, C.H.: The integrated dial-a-ride problem with timetabled fixed route service. Public Transp. 91(9), 217–241 (2016)
Wang, H.: Routing and scheduling for a last-mile transportation system. Transp. Sci. 53, 131–147 (2017). https://doi.org/10.1287/trsc20170753
Shen, Z.J.M., Feng, B., Mao, C., Ran, L.: Optimization models for electric vehicle service operations: a literature review. Transp. Res. Part B Methodol. 128, 462–477 (2019)
Erdelic, T., Carić, T., Lalla-Ruiz, E.: A survey on the electric vehicle routing problem: variants and solution approaches. J. Adv. Transp. 2019 (2019)
Felipe, Á., Ortuño, M.T., Righini, G., Tirado, G.: A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges. Transp. Res. Part E Logist. Transp. Rev. 71, 111–128 (2014)
Schneider, M., Stenger, A., Goeke, D.: The electric vehicle-routing problem with time windows and recharging stations. Transp. Sci. 48, 500–520 (2014)
Czioska, P., Kutadinata, R., Trifunović, A., Winter, S., Sester, M., Friedrich, B.: Real-world meeting points for shared demand-responsive transportation systems. Public Transp. 11(2), 341–377 (2019). https://doi.org/10.1007/s12469-019-00207-y
Ma, T.Y., Chow, J.Y.J., Klein, S., Ma, Z.: A user-operator assignment game with heterogeneous user groups for empirical evaluation of a microtransit service in Luxembourg. Transp. A Transp. Sci. 17, 946–973 (2021)
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This work was supported by the Luxembourg National Research Fund (C20/SC/14703944).
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Fang, Y., Ma, TY. (2023). Demand Responsive Feeder Bus Service Using Electric Vehicles with Timetabled Transit Coordination. In: Nathanail, E.G., Gavanas, N., Adamos, G. (eds) Smart Energy for Smart Transport. CSUM 2022. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-031-23721-8_7
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DOI: https://doi.org/10.1007/978-3-031-23721-8_7
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