Allocation of Railroad Capacity Under Competition: A Game Theoretic Approach to Track time Pricing

  • A. Bassanini
  • A. La Bella
  • A. Nastasi
Part of the Applied Optimization book series (APOP, volume 63)

Abstract

The reorganization of the European railway sector following the application of Directive 440 requires devising an infrastructure access mechanism for competing transport operators. This paper proposes a market-based approach to railroad track allocation and capacity pricing, formulating a three-stage game-theoretic model where transport operators request their preferred schedules to the infrastructure manager and set the final prices for the transport services on the basis of actual schedules and access tariffs. The latter are simultaneously computed by a non discriminatory mechanism which maximizes the value of the timetable of each operator. Access tariffs are based on the congestion degree each train imposes on the system.

The model is validated by numerical simulations showing the impact of congestion externalities on access tariffs, final service prices and operators’ profits.

Keywords

Subgame Perfect Equilibrium Quasi Variational Inequality Slack Time Transport Operator Rail Transport 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ben Akiva, M. and S. Lerman. (1985). Discrete Choice Analysis: Theory and Applicati on to Predict Travel Demand, MIT Press, Cambridge, MA.Google Scholar
  2. Bowers, P.H. (1996). Railway Reform in Germany. Journal of Transport Economics and Policy, 30: 95 - 102.Google Scholar
  3. Brooks, M. and K. Button. (1995). Separating Transport Track from Operations: a Typology of International Experiences. International Journal of Transport Economics, 22: 235 - 260.Google Scholar
  4. Carey, M. (1994). A Model and Strategy for Train Pathing with Choice of Lines, Platforms and Routes. Transportation Research, 28B: 333 - 353.CrossRefGoogle Scholar
  5. Crew, M.A. and P.R. Kleindorfer. (1987). The Economics of Public Utility Regulation. The MIT Press, Cambridge, MA.Google Scholar
  6. Dobson, G. and P.J. Lederer. (1993). Airline Scheduling and Routing in a Hub-andSpoke System. Transportation Science, 27: 281 - 297.CrossRefGoogle Scholar
  7. Harker, P.T. (1991). Generalized Nash Games and Quasi-Variational Inequalities. European Journal of Operations Research, 54: 81 - 94.CrossRefGoogle Scholar
  8. Harker, P.T. and S. Hong. (1990). Two Moments Estimation of the Delay on a Partially Double-Track Rail Line with Scheduled Traffic. Journal of Transportation Research Forum, 31: 38 - 49.Google Scholar
  9. Harker, P.T. and S. Hong. (1994). Pricing of Track Time in Railroad Operations: an Internal Market Approach. Transportation Research, 28B: 197 - 212.CrossRefGoogle Scholar
  10. Kraay, D.R. and P.T. Harker. (1995). Real-Time Scheduling of Freight Railroads. Transportation Research, 29B: 213 - 229.CrossRefGoogle Scholar
  11. Levin, R.C. (1981). Railroad Rates, Profitability, and Welfare under Deregulation. Bell Journal of Economics, 12: 1 - 26.CrossRefGoogle Scholar
  12. McFadden, D. (1981). Econometric Models of Probabilistic Choice, in C. Manski and D. McFadden (eds.) Structural Analysis of Discrete Data with Econometric Applications, MIT Press, Cambridge, MA.Google Scholar
  13. Morrison, S.A. (1983). Prices and Investment Level for Airport Runways. In T.E. Keeler (ed.) Research in Transportation Economics, pp. 103 - 130.Google Scholar
  14. Nash, C. (1993). Rail Privatisation in Britain. Journal of Transport Economics and Policy, 27: 317 - 322.Google Scholar
  15. Odijk, M.A. (1996). A Constraint Generation Algorithm for the Construction of Periodic Railway Timetables. Transportation Research, 30B: 455 - 464.CrossRefGoogle Scholar
  16. Selten, R. (1975). Re-Examination of the Perfectness Concept for Equilibrium Points in Extensive Games. International Journal of Game Theory, 4: 25 - 55.CrossRefGoogle Scholar
  17. Vickrey, W. (1969). Congestion Theory and Transportation Investment. American Economic Review, 59: 251 - 260.Google Scholar
  18. Winston, C. (1983). The Demand for Freight Transportation: Models and Applications. Transportation Research 17A: 419 - 427.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • A. Bassanini
  • A. La Bella
  • A. Nastasi

There are no affiliations available

Personalised recommendations