Skip to main content
SpringerLink
Log in

Incorporating Dynamic Bus Stop Simulation into Static Transit Assignment Models

  • Research Paper
  • Published:
International Journal of Civil Engineering Aims and scope Submit manuscript

Abstract

This study provides a methodology to incorporate the dynamic bus stop simulation into a proposed static transit assignment model. It tries to combine the merits of the realism of dynamic models and the simplicity of static models in a single framework. An algorithm is developed to simulate any load profile of both passenger and bus arrivals. Then, the simulation results are used within the transit assignment process to allow a better line choice representation. A detailed illustrative example is given to validate the proposed assignment methodology performance. The resulted flows in some cases exceed lines capacity while conserving the static equilibrium principles. This capacity violation interprets the fact that some passengers may fail to board the first incoming bus of their desired line due to insufficient capacity. However, they wait until a vacant space is offered on the same line. In addition, a benchmark problem is solved to ease the comparison between the proposed methodology and the existing methodologies. It shows the methodology capability of incorporating different waiting time models to produce passengers’ flow on transit lines. It also indicates the importance of lines that might be neglected in other transit assignment models. This would highlight the methodology interpretation of passengers’ behavior in transit networks.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

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

Similar content being viewed by others

References

  1. Ceder A, Wilson NHM (1986) Bus network design. Transp Res 20B:331–344

    Article  Google Scholar 

  2. Ceder A (2001) Public transport scheduling. Handbooks in transport—handbook 3: transport systems and traffic control. Elsevier Ltd, Oxford

    Google Scholar 

  3. Ceder A (2002) Urban transit scheduling: framework, review, and examples. ASCE J Urban Plan Dev 128:225–244

    Article  Google Scholar 

  4. Ceder A (2007) Public transit planning and operation. Elsevier Ltd, Oxford

    Google Scholar 

  5. Ceder A, Israeli Y (2007) User and operator perspectives in transit network design. J Transp Res Board 1623:3–7

    Article  Google Scholar 

  6. Owais M, Osman MK, Moussa G (2016) Multi-objective transit route network design as set covering problem. IEEE Trans Intell Transp Syst 17:670–679

    Article  Google Scholar 

  7. Szeto WY, Wu Y (2011) A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong. Eur J Oper Res 209:141–155

    Article  MathSciNet  MATH  Google Scholar 

  8. Owais M (2015) Issues related to transit network design problem. Int J Comput Appl 120:40–45

    Google Scholar 

  9. Ibeas A, dell’Olio L, Alonso B, Sainz O (2010) Optimizing bus stop spacing in urban areas. Transp Res Part E 46:446–458

    Article  Google Scholar 

  10. dell’Olio L, Moura JL, Ibeas A (2006) Bi-level mathematical programming model for locating bus stops and optimizing frequencies. Transp Res Rec J Transp Res Board 1971:23–31

    Article  Google Scholar 

  11. dell’Olio L, Ibeas A, Díaz FR (20087)Assigning vehicles types to a bus transit network. TRB 2009 annual meeting CD-ROM

  12. Qi H, Wang DH, Bie Y (2015) Spatial development of urban road network traffic gridlock. Int J Civ Eng 13:388–399

    Google Scholar 

  13. Bosurgi G, Bongiorno N, Pellegrino O (2016) A nonlinear model to predict drivers’ track paths along a curve. Int J Civ Eng 14:271. doi:10.1007/s40999-016-0034-1

    Article  Google Scholar 

  14. Chriqui C, Robillard P (1975) Common bus lines. Hautes Eludes Commercials Montréal Québec Canada Transportation 9:115–121

    Google Scholar 

  15. Spiess H (1983) On optimal route choice strategies in transit networks. Publication 285, Centre de Recherche sur les Transports, Université de Montréal

  16. Desaulniers G, Hickman M (2007) Handbook in OR & MS, Chapter 2. Elsevier, Oxford

    Google Scholar 

  17. Nuzzolo A, Russo F, Crisalli U (2001) A doubly dynamic schedule-based assignment model for transit networks. Transp Sci 35:268–285

    Article  MATH  Google Scholar 

  18. Tong C, Wong S (1998) A stochastic transit assignment model using a dynamic schedule-based network. Transp Res Part B Methodol 33:107–121

    Article  Google Scholar 

  19. Abdelghany K, Mahmassani H (2001) Dynamic trip assignment-simulation model for intermodal transportation networks. Transp Res Rec J Transp Res Board (1771):52–60

  20. Sumalee A, Tan Z, Lam WH (2009) Dynamic stochastic transit assignment with explicit seat allocation model. Transp Res Part B Methodol 43:895–912

    Article  Google Scholar 

  21. Yuqing Z, Lam WH, Sumalee A (2009) Dynamic transit assignment model for congested transit networks with uncertainties. Transportation research board 88th annual meeting

  22. Hamdouch Y, Ho H, Sumalee A, Wang G (2011) Schedule-based transit assignment model with vehicle capacity and seat availability. Transp Res Part B Methodol 45:1805–1830

    Article  Google Scholar 

  23. Nuzzolo A, Crisalli U, Rosati L (2012) A schedule-based assignment model with explicit capacity constraints for congested transit networks. Transp Res Part C Emerg Technol 20:16–33

    Article  Google Scholar 

  24. Hamdouch Y, Szeto W, Jiang Y (2014) A new schedule-based transit assignment model with travel strategies and supply uncertainties. Transp Res Part B Methodol 67:35–67

    Article  Google Scholar 

  25. Speiss H, Florian M (1989) Optimal strategies: a new assignment model for transit networks. Transp Res Part B 23:83–102

    Article  Google Scholar 

  26. De Cea J, Fernández E (1993) Transit assignment for congested public transport system: an equilibrium model. Transp Sci 27(2):133–147

    Article  MATH  Google Scholar 

  27. Lam WH-K, Gao Z, Chan K, Yang H (1999) A stochastic user equilibrium assignment model for congested transit networks. Transp Res Part B Methodol 33:351–368

    Article  Google Scholar 

  28. Nielsen OA (2000) A stochastic transit assignment model considering differences in passengers utility functions. Transp Res Part B Methodol 34:377–402

    Article  Google Scholar 

  29. Lam WH, Zhou J, Sheng Z-H (2002) A capacity restraint transit assignment with elastic line frequency. Transp Res Part B Methodol 36:919–938

    Article  Google Scholar 

  30. Cepeda M, Cominetti R, Florian M (2006) A frequency-based assignment model for congested transit networks with strict capacity constraints: characterization and computation of equilibria. Transp Res Part B Methodol 40:437–459

    Article  Google Scholar 

  31. Sun L-J, Gao Z-Y (2007) An equilibrium model for urban transit assignment based on game theory. Eur J Oper Res 181:305–314

    Article  MATH  Google Scholar 

  32. Schmöcker J-D, Bell MG, Kurauchi F (2008) A quasi-dynamic capacity constrained frequency-based transit assignment model. Transp Res Part B Methodol 42:925–945

    Article  Google Scholar 

  33. Schmöcker J-D, Fonzone A, Shimamoto H, Kurauchi F, Bell MG (2011) Frequency-based transit assignment considering seat capacities. Transp Res Part B Methodol 45:392–408

    Article  Google Scholar 

  34. Szeto W, Solayappan M, Jiang Y (2011) Reliability-based transit assignment for congested stochastic transit networks. Comput Aided Civ Infrastruct Eng 26:311–326

    Article  Google Scholar 

  35. Li Q, Chen PW, Nie YM (2015) Finding optimal hyperpaths in large transit networks with realistic headway distributions. Eur J Oper Res 240:98–108

    Article  MathSciNet  MATH  Google Scholar 

  36. Marguier P, Ceder A (1984) Passenger waiting strategies for overlapping bus routes. Mass Inst Technol Camb Mass Transp Sci 18:207–230

    Google Scholar 

  37. Holroyd EM, Scraggs DA (1996) Waiting times for buses in central London. Printerhall, London

    Google Scholar 

  38. Bowman LA, Turnquist MA (1981) Service frequency, schedule reliability and passenger wait times at transit stops. Transp Res Part A Gen 15:465–471

    Article  Google Scholar 

  39. Gendreau M, U d. M. C. d. r. s. l. transports (1984) Étude approfondie d’un modèle d’équilibre pour l’affectation des passagers dans les réseaux de transport en commun. Montréal: Université de Montréal, Centre de recherche sur les transports

  40. Cancela H, Mauttone A, Urquhart ME (2015) Mathematical programming formulations for transit network design. Transp Res Part B Methodol 77:17–37

  41. Nguyen S, Pallottino S (1988) Equilibrium traffic assignment for large scale transit networks. Eur J Oper Res 37:176–186

    Article  MathSciNet  MATH  Google Scholar 

  42. Yu B, Yang Z-Z, Jin P-H, Wu S-H, Yao B-Z (2012) Transit route network design-maximizing direct and transfer demand density. Transp Res Part C Emerg Technol 22:58–75

    Article  Google Scholar 

  43. Gao Z, Sun H, Shan LL (2004) A continuous equilibrium network design model and algorithm for transit systems. Transp Res Part B Methodol 38:235–250

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Civil Engineering Department, Assiut University, Assiut, 71515, Egypt

    Mahmoud Owais & Taher Hassan

Authors
  1. Mahmoud Owais
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Taher Hassan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mahmoud Owais.

Appendix

Appendix

figure bfigure b

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Owais, M., Hassan, T. Incorporating Dynamic Bus Stop Simulation into Static Transit Assignment Models. Int J Civ Eng 16, 67–77 (2018). https://doi.org/10.1007/s40999-016-0064-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40999-016-0064-8

Keywords

Search

Navigation