Optimizing limited-stop bus services along a public transit corridor with a differential fare structure
Abstract
Limited-stop bus services are a highly efficient way to release more potential of the public transit system to meet travel demand, especially under constraints on vehicle fleet size and transportation infrastructure. This work first proposes a visualized fare table for the design of limited-stop bus services along a public transit corridor, along which many lines of public transit carry a heavy load of demand back and forth every working day. Based on this proposed fare table, a set of fare strategies and desired aims of fare policy, a differentiated fare structure is established to improve social equity and increase revenue. The nature of the structure can help travellers understand how to be charged between their origins and destinations (e.g. flat, time-based, stop-based or quality-based pricing) and then plan their trips efficiently. Secondly, a model is formulated to minimize the total social cost in designing a fixed demand limited-stop bus service system with a differentiated fare structure. Thirdly, numerical results are carried out with sensitivity analysis within three scenarios of differentiated fare structures. It is found that a differentiated fare structure has a great effect on passenger path choice behaviour and resulting optimal design of bus services. An attractive feature of this differentiated fare structure is that it could not only enhance the operator’s revenue and social equity but also reduce passenger transfers and social cost.
Keyword : public transit, limited-stop bus service, differentiated fare structure, social cost, environmental improvement
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Chien, S. I.-J.; Tsai, C. F. M. 2007. Optimization of fare structure and service frequency for maximum profitability of transit systems, Transportation Planning and Technology 30(5): 477–500. https://doi.org/10.1080/03081060701599961
De Cea, J.; Fernández, E. 1993. Transit assignment for congested public transport systems: an equilibrium model, Transportation Science 27(2): 133–147. https://doi.org/10.1287/trsc.27.2.133
Fleishman, D.; Shaw, N.; Joshi, A.; Freeze, R.; Oram, R. 1996. Fare Policies, Structures, and Technologies. Transit Cooperative Research Program (TCRP) Report 10. Transportation Research Board, Washington, DC, US. 53 p. Available from Internet: http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_10-a.pdf
Furth, P. G.; Day, F. B. 1985. Transit routing and scheduling strategies for heavy-demand corridors, Transportation Research Record 1011: 23–26.
Leiva, C.; Muñoz, J. C.; Giesen, R.; Larrain, H. 2010. Design of limited-stop services for an urban bus corridor with capacity constraints, Transportation Research Part B: Methodological 44(10): 1186–1201. https://doi.org/10.1016/j.trb.2010.01.003
Li, Z.-C.; Lam, W. H. K.; Wong, S. C. 2009. The optimal transit fare structure under different market regimes with uncertainty in the network, Networks and Spatial Economics 9(2): 191–216. https://doi.org/10.1007/s11067-007-9058-z
Ling, J.-H. 1998. Transit fare differentials: a theoretical analysis, Journal of Advanced Transportation 32(3): 297–314. https://doi.org/10.1002/atr.5670320304
Tang, C.; Ceder, A.; Zhao, S.; Ge, Y.-E. 2016. Determining optimal strategies for single-line bus operation by means of smartphone demand data, Transportation Research Record: Journal of the Transportation Research Board 2539: 130–139. https://doi.org/10.3141/2539-15
Tirachini, A. 2007. Estrategias de Asignación de Flota en un Corredor de Transporte Público. Universidad de Chile, Santiago, Chile. (in Portugal).
Tirachini, A.; Hensher, D. A. 2011. Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors, Transportation Research Part B: Methodological 45(5): 828–844. https://doi.org/10.1016/j.trb.2011.02.006
Tsai, F.-M.; Chien, S.; Wei, C.-H. 2013. Joint optimization of temporal headway and differential fare for transit systems considering heterogeneous demand elasticity, Journal of Transportation Engineering 139(1): 30–39. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000468
Zhang, J.; Lv, B.; Tian, G.; Liu, W. 2014. Fare design in urban transit network considering elastic demand and adverse weather’s Impact, Journal of Applied Mathematics 2014: 197515. https://doi.org/10.1155/2014/197515