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Public Transport

, Volume 5, Issue 3, pp 193–217 | Cite as

Approaching even-load and even-headway transit timetables using different bus sizes

  • Avishai (Avi) CederEmail author
  • Stephan Hassold
  • Blanche Dano
Original Paper

Abstract

In times of climate change and scarce resources, it is essential to reduce emissions and to use fuel as economically as possible. Naturally, the transportation sector has a high-energy demand and uses a great deal of the resources, which account for high carbon dioxide emissions. Prudent use of public-transport (PT) vehicles can help make the need for travel more economical, thus saving resources. This work proposes a multi-objective methodology to create bus timetables using multiple vehicle sizes, and has two objectives carried out simultaneously: First, minimize the deviation of the determined headways from a desired even headway and second, minimize the deviation of the observed passenger loads from a desired even-load level of the vehicles at the maximum-load point. The first objective will reduce the expected waiting time of randomly arriving passengers and thus will increase the attractiveness of the PT service. The second objective will improve the reliability of operation for fluctuating demand, and will improve the utilization of the vehicles from the operator perspective. The suggested methodology uses a graphical heuristic approach to examine different strategies in the creation of the optimal timetables. The methodology developed is applied to a case study of a bus line in Auckland, New Zealand.

Keywords

Transit timetables Matching demand and supply Reliability Different bus sizes 

References

  1. Bunte S, Kliewer N (2009) An overview on vehicle scheduling models. Public Transp 1(4):299–317 CrossRefGoogle Scholar
  2. Ceder A (1984) Bus frequency determination using passenger count data. Transp Res, Part A, Policy Pract 18(5/6):439–453 Google Scholar
  3. Ceder A (1986) Methods for creating bus timetables. Transp Res, Part A, Policy Pract 21(1):59–83 Google Scholar
  4. Ceder A (2007) Public transit planning and operation: theory, modelling and practice. Butterworth-Heinemann/Elsevier, Stoneham Google Scholar
  5. Ceder A, Stern HI (1984) Optimal transit timetables for a fixed vehicle fleet. In: Volmuller J, Hammerslag R (eds) Transportation and traffic theory. UNU Science Press, Tokyo, pp 331–355 Google Scholar
  6. Currie G (2009) Setting long headways for coordination and service timing benefits: when less is more. In: 88th transportation research board annual meeting, Washington, DC, USA (CD Rom) Google Scholar
  7. De Palma A, Lindsey R (2001) Optimal timetables for public transportation. Transp Res, Part B, Methodol 35(8):789–813 CrossRefGoogle Scholar
  8. Eberlein XJ, Wilson NHM, Barnhart C, Bernstein D (1998) The real-time deadheading problem in transit operations control. Transp Res, Part B, Methodol 32(2):77–100 CrossRefGoogle Scholar
  9. Furth P, Wilson N (1981) Setting frequencies on bus routes: theory and practice. Transp Res Rec 818:1–7 Google Scholar
  10. Gallo G, Di Miele F (2001) Dispatching buses in parking depots. Transp Sci 35(3):322–330 CrossRefGoogle Scholar
  11. Gronau R (2000) Optimum diversity in the public transport market. J Transp Econ Policy 34(1):21–41 Google Scholar
  12. Hurdle V (1973) Minimum cost schedules for a public transportation route (I: Theory, II: Examples). Transp Sci 7:109–157 CrossRefGoogle Scholar
  13. Koutsopoulos H, Odoni A, Wilson NHM (1985) Determination of headways as function of time varying characteristics on a transit network. In: Rousseau JM (ed) Computer scheduling of public transport 2. Elsevier, Amsterdam, pp 391–413 Google Scholar
  14. Luethi M, Weidmann UA, Nash A (2007) Passenger arrival rates at public transport stations. In: 86th transportation research board annual meeting, Washington, DC, USA (CD Rom) Google Scholar
  15. Newell G (1971) Dispatching policies for a transportation route. Transp Sci 5(1):91–105 CrossRefGoogle Scholar
  16. Newell G (1973) Scheduling, location, transportation, and continuum mechanics; some simple approximations to optimization problems. SIAM J Appl Math 25(3):346–360 CrossRefGoogle Scholar
  17. Osuna E, Newell G (1972) Control strategies for an idealized public transportation system. Transp Sci 6(1):52–72 CrossRefGoogle Scholar
  18. Pareto V (1897) Cours d’economie politique, vols I and II. F. Rouge, Lausanne Google Scholar
  19. Peeters L, Kroon L (2001) A cycle based optimization model for the cyclic railway timetabling problem. In: Voss S, Daduna JR (eds) Computer-aided scheduling of public transport, vol 505. Springer, Berlin, pp 275–296 CrossRefGoogle Scholar
  20. Potter S (2003) Transport energy and emissions: urban public transport. In: Hensher DA, Button KJ (eds) Handbook of transport and the environment, 4. Elsevier, Amsterdam, pp 247–263 Google Scholar
  21. Van Oudheusden DL, Zhu W (1995) Trip frequency scheduling for bus route management in Bangkok. Eur J Oper Res 83(3):439–451 CrossRefGoogle Scholar
  22. Wirasinghe SC (1990) Re-examination of Newell’s dispatching policy and extension to a public bus route with many to many time-varying demand. In: The proceedings of the 11th international symposium on transportation and traffic theory (ISTTT), Yokohama-shi, Japan, pp 363–377 Google Scholar
  23. Wirasinghe SC (2003) Initial planning for urban transit systems. In: Lam WHK, Bell MGH (eds) Advanced modeling for transit operations and service planning. Emerald Group Pub Ltd, Bingley, pp 1–29 Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Avishai (Avi) Ceder
    • 1
    Email author
  • Stephan Hassold
    • 1
  • Blanche Dano
    • 1
  1. 1.Transportation Research Center, Department of Civil and Environmental EngineeringUniversity of AucklandAucklandNew Zealand

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