Skip to main content
SpringerLink
Log in

Agent-based optimisation of public transport supply and pricing: impacts of activity scheduling decisions and simulation randomness

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

The optimal setting of public transport pricing and supply levels has been traditionally analysed with analytical models that combine the objectives of users, service providers and decision makers in optimisation problems. In this paper, public transport fare and headway are jointly optimised using an activity-based simulation framework. Unlike traditional analytical models that find single optimal values for headway, fare and other optimisation variables, we obtain a range of values for the optimal fare and headway, due to the randomness in user behaviour that is inherent to an agent-based approach. Waiting times and implications of an active bus capacity constraint are obtained on an agent-by-agent basis. The maximisation of operator profit or social welfare result in different combinations of the most likely optimal headway and fare. We show that the gap between welfare and profit optimal solutions is smaller when users can adjust their departure time according to their activities, timetabling and convenience of the public transport service.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price includes VAT (Finland)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. Multi-Agent Transport Simulation, see www.matsim.org.

  2. Estimated parameters are in this paper flagged by a hat.

  3. Relative car travel time delays are measured as the ratio between car travel time delay (actual travel time minus free-flow travel time) and total car travel time (average of all car trips and average of all random seeds).

  4. If not otherwise specified, welfare optimal or welfare maximum refer to the unconstraint situation which also allows for the operator to make losses.

References

  • Ahn, K.: Road pricing and bus service policies. J. Transp. Econ. Policy 43, 25–53 (2009)

    Google Scholar 

  • Arnott, R., Yan, A.: The two-mode problem: second-best pricing and capacity. Rev. Urban Reg. Dev. Stud. 12, 170–199 (2000)

    Article  Google Scholar 

  • ATC: National guidelines for transport system management in Australia. Technical Report. Australian Transport Council (2006)

  • Baskaran, R., Krishnaiah, K.: Simulation model to determine frequency of a single bus route with single and multiple headways. Int. J. Bus. Perform. Supply Chain Model. 4, 40–59 (2012)

    Article  Google Scholar 

  • Basso, L.J., Silva, H.E.: Efficiency and substitutability of transit subsidies and other urban transport policies. Am. Econ. J. Econ. Policy (2014), forthcoming

  • Basso, L., Guevara, C.A., Gschwender, A., Fuster, M.: Congestion pricing, transit subsidies and dedicated bus lanes: efficient and practical solutions to congestion. Transp. Policy 18, 676–684 (2011)

    Article  Google Scholar 

  • Cetin, N., Burri, A., Nagel, K.: A large-scale agent-based traffic microsimulation based on queue model. In: Proceedings of the Swiss Transport Research Conference (STRC), Monte Verita, CH. See www.strc.ch. Earlier version, with inferior performance values: Transportation Research Board Annual Meeting 2003 paper number 03-4272 (2003)

  • Chang, S.K., Schonfeld, P.M.: Multiple period optimization of bus transit systems. Transp. Res. B 25, 453–478 (1991). doi:10.1016/0191-2615(91)90038-K

    Article  Google Scholar 

  • Charypar, D., Nagel, K.: Generating complete all-day activity plans with genetic algorithms. Transportation 32, 369–397 (2005)

    Article  Google Scholar 

  • de Borger, B., Wouters, S.: Transport externalities and optimal pricing and supply decisions in urban transportation: a simulation analysis for Belgium. Reg. Sci. Urban Econ. 28, 163–197 (1998)

    Article  Google Scholar 

  • Dodgson, J.S., Topham, N.: Benefit–cost rules for urban transit subsidies: an integration of allocational, distributional and public finance issues. J. Transp. Econ. Policy 21, 57–71 (1987)

    Google Scholar 

  • Fernández, R.: Modelling public transport stops by microscopic simulation. Transp. Res. C 18, 856–868 (2010)

    Article  Google Scholar 

  • Fernández, R., Tyler, N.: Effect of passenger–bus–traffic interactions on bus stop operations. Transp. Plan. Technol. 28, 273–292 (2005)

    Article  Google Scholar 

  • Gawron, C.: An iterative algorithm to determine the dynamic user equilibrium in a traffic simulation model. Int. J. Mod. Phys. C 9, 393–407 (1998)

    Article  Google Scholar 

  • Horni, A., Charypar, D., Axhausen, K.W.: Variability in transport microsimulations investigated for MATSim: preliminary results. In: Proceedings of the 11th Swiss Transport Research Conference (STRC) (2011)

  • Horni, A., Nagel, K., Axhausen, K.: High-resolution destination choice in agent-based demand models. In: Annual Meeting Preprint 12-1989. Transportation Research Board, Washington, DC. Also VSP WP 11-17, see www.vsp.tu-berlin.de/publications (2012)

  • Jansson, J.O.: A simple bus line model for optimisation of service frequency and bus size. J. Transp. Econ. Policy 14, 53–80 (1980)

    Google Scholar 

  • Jansson, K.: Public transport policy with and without road pricing. In: 5th Kuhmo-Nectar Conference on Transport Economics (2010)

  • Jara-Díaz, S.R., Gschwender, A.: Towards a general microeconomic model for the operation of public transport. Transp. Rev. 23, 453–469 (2003). doi:10.1080/0144164032000048922

    Article  Google Scholar 

  • Jara-Díaz, S.R., Gschwender, A.: The effect of financial constraints on the optimal design of public transport services. Transportation 36, 65–75 (2009)

    Article  Google Scholar 

  • Kaddoura, I., Kickhöfer, B., Neumann, A., Tirachini, A.: Public transport supply optimization in an activity-based model: impacts of activity scheduling decisions and dynamic congestion. In: Latsis Symposium 2012—1st European Symposium on Quantitative Methods in Transportation Systems, Lausanne, Switzerland. Also VSP WP 12-17, see www.vsp.tu-berlin.de/publications (2012)

  • Kickhöfer, B., Grether, D., Nagel, K.: Income-contingent user preferences in policy evaluation: application and discussion based on multi-agent transport simulations. Transportation 38, 849–870 (2011). doi:10.1007/s11116-011-9357-6

    Article  Google Scholar 

  • Kickhöfer, B., Kaddoura, I., Neumann, A., Tirachini, A.: Optimal public transport supply in an agent-based model: the influence of departure time choice on operator’s profit and social welfare. In: Proceedings of the Kuhmo Nectar Conference on Transportation Economics. Also VSP WP 12-05, see www.vsp.tu-berlin.de/publications (2012)

  • Kickhöfer, B., Hülsmann, F., Gerike, R., Nagel, K.: Rising car user costs: comparing aggregated and geo-spatial impacts on travel demand and air pollutant emissions. In: Vanoutrive, T., Verhetsel, A. (eds.) Smart Transport Networks: Decision Making, Sustainability and Market structure. NECTAR Series on Transportation and Communications Networks Research, pp. 180–207. Edward Elgar Publishing Ltd. (2013)

  • Kraus, M.: Discomfort externalities and marginal cost transit fares. J. Urban Econ. 29, 249–259 (1991)

    Article  Google Scholar 

  • Kraus, M.: A new look at the two-mode problem. J. Urban Econ. 54, 511–530 (2003)

    Article  Google Scholar 

  • Kraus, M., Yoshida, Y.: The commuter’s time-of-use decision and optimal pricing and service in urban mass transit. J. Urban Econ. 51, 170–195 (2002)

    Article  Google Scholar 

  • Mohring, H.: Optimization and scale economics in urban bus transportation. Am. Econ. Rev. 62, 591–604 (1972)

    Google Scholar 

  • Nelson, P., Baglino, A., Harrington, W., Safirova, E.: Transit in Washington, DC: current benefits and optimal level of provision. J. Urban Econ. Lett. 62, 231–251 (2007)

    Article  Google Scholar 

  • Neumann, A.: A paratransit-inspired evolutionary process for public transit network design. PhD thesis, TU Berlin. Also VSP WP 14-13, see www.vsp.tu-berlin.de/publications (2014)

  • Neumann, A., Nagel, K.: Avoiding bus bunching phenomena from spreading: a dynamic approach using a multi-agent simulation framework. VSP Working Paper, 10-08. TU Berlin, Transport Systems Planning and Transport Telematics. See www.vsp.tu-berlin.de/publications (2010)

  • Neumann, A., Balmer, M., Rieser, M.: Converting a static trip-based model into a dynamic activity-based model to analyze public transport demand in Berlin. In: Roorda, M.J., Miller, E.J. (eds.) Travel Behaviour Research: Current Foundations, Future Prospects, chap. 7, pp. 151–176. International Association for Travel Behaviour Research (IATBR) (2014)

  • Oldfield, R.H., Bly, P.H.: An analytic investigation of optimal bus size. Transp. Res. B 22, 319–337 (1988). doi:10.1016/0191-2615(88)90038-0

    Article  Google Scholar 

  • Parry, I.W.H., Small, K.A.: Should urban transit subsidies be reduced? Am. Econ. Rev. 99, 700–724 (2009)

    Article  Google Scholar 

  • Pels, E., Verhoef, E.T.: Infrastructure pricing and competition between modes in urban transport. Environ. Plan. A 39, 2119–2138 (2007)

    Article  Google Scholar 

  • Raney, B., Nagel, K.: An improved framework for large-scale multi-agent simulations of travel behaviour. In: Rietveld, P., Jourquin, B., Westin, K. (eds.) Towards Better Performing European Transportation Systems, pp. 305–347. Routledge, London (2006)

    Google Scholar 

  • Rieser, M.: Adding transit to an agent-based transportation simulation concepts and implementation. PhD Thesis, TU Berlin. Also VSP WP 10-05, see www.vsp.tu-berlin.de/publications (2010)

  • Tabuchi, T.: Bottleneck congestion and modal split. J. Urban Econ. 34, 414–431 (1993)

    Article  Google Scholar 

  • Tirachini, A., Hensher, D.A.: Bus congestion, optimal infrastructure investment and the choice of a fare collection system in dedicated bus corridors. Transp. Res. B 45, 828–844 (2011). doi:10.1016/j.trb.2011.02.006

    Article  Google Scholar 

  • Tirachini, A., Hensher, D.A.: Multimodal transport pricing: first best, second best and extensions to non-motorized transport. Transp. Rev. 32, 181–202 (2012)

    Article  Google Scholar 

  • Tirachini, A., Hensher, D.A., Rose, J.M.: Multimodal pricing and optimal design of urban public transport: the interplay between traffic congestion and bus crowding. Transp. Res. B 61, 33–54 (2014)

    Article  Google Scholar 

  • Vickrey, W.: Congestion theory and transport investment. Am. Econ. Rev. 59, 251–260 (1969)

    Google Scholar 

  • Wright, L., Hook, W.: Bus Rapid Transit Planning Guide. Technical Report. ITDP, Institute for Transportation and Development Policy, New York (2007)

Download references

Acknowledgments

We are indebted to Kai Nagel for his helpful comments and support to the development of this project and to three anonymous reviewers for their constructive comments and suggestions. Alejandro Tirachini acknowledges support from Fondecyt, Chile (Grant 11130227) and the Complex Engineering Systems Institute (Grants ICM P-05-004-F, CONICYT FBO16). Previous versions of this paper were presented at the Kuhmo-Nectar Conference on Transportation Economics in Berlin, July 2012 (Kickhöfer et al. 2012) and the Latsis Symposium in Lausanne, September 2012 (Kaddoura et al. 2012).

Author information

Authors and Affiliations

  1. Transport Systems Planning and Transport Telematics, Technische Universität Berlin, Sekretariat SG 12, Salzufer 17–19, 10587, Berlin, Germany

    Ihab Kaddoura, Benjamin Kickhöfer & Andreas Neumann

  2. Transport Engineering Division, Civil Engineering Department, Universidad de Chile, Santiago, Chile

    Alejandro Tirachini

Authors
  1. Ihab Kaddoura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Benjamin Kickhöfer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andreas Neumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alejandro Tirachini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ihab Kaddoura.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kaddoura, I., Kickhöfer, B., Neumann, A. et al. Agent-based optimisation of public transport supply and pricing: impacts of activity scheduling decisions and simulation randomness. Transportation 42, 1039–1061 (2015). https://doi.org/10.1007/s11116-014-9533-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-014-9533-6

Keywords

Search

Navigation