Skip to main content

Part of the book series: Springer Tracts on Transportation and Traffic ((STTT))

Abstract

In this chapter, the different basic assumptions for the development of assignment models to transit networks (frequency-based, schedule-based) are presented together with the possible approaches to the simulation of the dynamic system (steady state, macroscopic flows, agent-based).

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alfa AS, Chen MY (1995) Temporal distribution of public transport demand during the peak period. Eur J Oper Res 83:137–153

    Article  MATH  Google Scholar 

  • Amin-Naseri MR, Baradaran V (2014) Accurate estimation of average waiting time in public transportation systems. Transp Sci 49:213–222

    Article  Google Scholar 

  • Andreasson I. (1976) A method for the analysis of transit networks. In: Roubens M (ed) Proceedings of the 2nd European congress on operations research, North Holland, Amsterdam

    Google Scholar 

  • Balmer M, Rieser M, Meister K, Charypar D, Lefebvre N, Nagel K (2008) MATSim-T: architecture and simulation times. In: Bazzan ALC, KlĂ¼gl F (ed) Multi-agent systems for traffic and transportation engineering. Information science reference, Hershey, pp 57–78

    Google Scholar 

  • Bellei G, Gentile G, Papola N (2005) A within-day dynamic traffic assignment model for urban road networks. Transp Res B 39:1–29

    Article  Google Scholar 

  • Bellei G, Gentile G, Meschini L, Papola N (2006) A demand model with departure time choice for within-day dynamic traffic assignment. Eur J Oper Res 175:1557–1576

    Article  MATH  Google Scholar 

  • Bellman R (1958) On a routing problem. Q Appl Math 16:87–90

    MATH  Google Scholar 

  • Bowman LA, Turnquist MA (1981) Service frequency, schedule reliability and passenger wait times at transit stops. Transportation Research A 15:465–471

    Article  Google Scholar 

  • Cantarella GE (1997) A general fixed-point approach to multimode multi-user equilibrium assignment with elastic demand. Transp Sci 31:107–128

    Article  MATH  Google Scholar 

  • Cantarella GE, Cascetta E (1995) Dynamic processes and equilibrium in transportation networks: towards a unifying theory. Transp Sci 29:305–329

    Article  MATH  Google Scholar 

  • Cats O (2013) Multi-agent transit operations and assignment model. Proc Comput Sci 19:809–814

    Article  Google Scholar 

  • Cats O, Burghout W, Toledo T, Kousopoulos HN (2010) Mesoscopic modeling of bus public transportation. Transp Res Rec 2188:9–18

    Article  Google Scholar 

  • Cats O, Kousopoulos HN, Burghout W, Toledo T (2011) Effect of real-time transit information on dynamic path choice of passengers. Transp Res Rec 2217:46–54

    Article  Google Scholar 

  • Chriqui C, Robillard P (1975) Common bus lines. Transp Sci 9:115–121

    Article  Google Scholar 

  • De Cea J, Fernandez JE (1989) Transit assignment to minimal routes: an efficient new algorithm. Traffic Eng Control 30:491–494

    Google Scholar 

  • Dial RB (1967) Transit pathfinder algorithm. Highw Res Board 205:67–85

    Google Scholar 

  • Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1:269–271

    Article  MathSciNet  MATH  Google Scholar 

  • Ettema D, Jong K, Timmermans H, Bakema A (2007) PUMA: multi-agent modelling of urban systems. In: Koomen E et al (eds) Modelling land-use change, pp 237–258

    Google Scholar 

  • Fearnside K, Draper DP (1971) Public transport assignment—a new approach. Traffic Eng Control 13:298–299

    Google Scholar 

  • Friedrich M, Hofsaess I, Wekeck S (2001) Timetable-based transit assignment using branch and bound techniques. Transp Res Rec 1752:100–107

    Article  Google Scholar 

  • Gallo G, Longo G, Nguyen S, Pallottino S (1993) Directed hypergraphs and applications. Discrete Appl Math 42:177–201

    Article  MathSciNet  MATH  Google Scholar 

  • Gao W, Balmer M, Miller EJ (2010) Comparisons between MATSim and EMME/2 on the greater Toronto and Hamilton area network. Transp Res Rec 2197:118–128

    Article  Google Scholar 

  • Gentile G (2010) The general link transmission model for dynamic network loading and a comparison with the due algorithm. In: Immers LGH, Tampere CMJ, Viti F (eds) New developments in transport planning: advances in Dynamic Traffic Assignment (selected papers from the DTA 2008 conference, Leuven). Transport economics, management and policy series. Edward Elgar Publishing, MA, pp 153–178

    Google Scholar 

  • Gentile G (2015) Using the general link transmission model in a dynamic traffic assignment to simulate congestion on urban networks. Transp Res Proc 5:66–81

    Article  Google Scholar 

  • Gentile G, Papola A (2006) An alternative approach to route choice simulation: the sequential models. In: Proceedings of the European transport conference, Strasbourg, France

    Google Scholar 

  • Gentile G, Meschini L, Papola N (2005) Spillback congestion in dynamic traffic assignment: a macroscopic flow model with time-varying bottlenecks. Transp Res B 41:1114–1138

    Article  Google Scholar 

  • Hickman MD, Bernstein DH (1997) Transit service and path choice models in stochastic and time-dependent networks. Transp Sci 31:129–146

    Article  MATH  Google Scholar 

  • Jolliffe JK, Hutchinson TP (1975) A behavioral explanation of the association between bus and passenger arrivals at a bus stop. Transp Sci 9:248–282

    Article  Google Scholar 

  • Larson RC, Odoni AR (1981) Urban operations research. Prentice-Hall, Englewoods Cliffs

    Google Scholar 

  • Last A, Leak SE (1976) Transept: a bus model. Traffic Eng Control 17:14–20

    Google Scholar 

  • Le Clercq F (1972) A public transport assignment method. Traffic Eng Control 14:91–96

    Google Scholar 

  • Meignan D, Simonin O, Koukam A (2007) Simulation and evaluation of urban bus-networks using a multiagent approach. Simul Model Pract Theory 15:659–671

    Article  Google Scholar 

  • Meschini L, Gentile G, Papola N (2007) A frequency based transit model for dynamic traffic assignment to multimodal networks. In: Allsop R, Bell MGH, Heydecker BG (eds) Proceedings of the 17th international symposium on transportation and traffic theory (ISTTT). Elsevier, London, pp 407–436

    Google Scholar 

  • Moller-Pedersen J (1999) Assignment model of timetable based systems (TPSCHEDULE). In: Proceedings of 27th European transportation forum, seminar F, Cambridge, England, pp 159–168

    Google Scholar 

  • Nguyen S, Pallottino S, Malucelli F (2001) A modeling framework for passenger assignment on a transport network with timetables. Transp Sci 35:238–249

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  • Nielsen OA (2004) A large-scale stochastic multi-class schedule-based transit model with random coefficients. In: Wilson NHM, Nuzzolo A (eds) Schedule-based dynamic transit modeling: theory and applications. Kluwer Academic Publisher, Dordrecht, pp 53–78

    Chapter  Google Scholar 

  • Nielsen OA, Jovicic G (1999) A large-scale stochastic timetable-based transit assignment model for route and sub-mode choices. Transp Plann Methods 434:169–184

    Google Scholar 

  • Nuzzolo A, Russo F (1998) A dynamic network loading model for transit services. In: Proceedings of TRAISTAN III, San Juan, Puerto Rico

    Google Scholar 

  • 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 

  • Osuna E, Newell G (1972) Control strategies for an idealized public transportation system. Transp Sci 6:52–72

    Article  Google Scholar 

  • Pallottino S, ScutellĂ  MG (1998) Shortest path algorithms in transportation models: classical and innovative aspects. In: Marcotte P, Nguyen S (eds) Equilibrium and advanced transportation modelling. Kluwer Academic Publishers, Dordrecht, pp 245–281

    Google Scholar 

  • Salvini P, Miller EJ (2005) ILUTE: an operational prototype of a comprehensive microsimulation model of urban systems. Netw Spat Econ 5:217–234

    Article  Google Scholar 

  • Sheffi Y (1984) Urban transportation networks: equilibrium analysis with mathematical programming methods. Prentice-Hall, NJ

    Google Scholar 

  • Sumi T, Matsumoto Y, Miyaki Y (1990) Departure time and route choice of commuters on mass transit systems. Transp Res B 24:247–262

    Article  Google Scholar 

  • Toledo T, Cats O, Burghout W, Koutsopoulos HN (2010) Mesoscopic simulation for transit operations. Transp Res C 18:896–908

    Article  Google Scholar 

  • Tong CO, Wong SC (1999) A stochastic transit assignment model using a dynamic schedule-based network. Transp Res B 33:107–121

    Article  Google Scholar 

  • TRB (2013) TCRP Report 165–Transit Capacity and Quality of Service Manual, 3rd Edition

    Google Scholar 

  • Wahba M, Shalaby A (2005) Multiagent learning-based approach to transit assignment problem a prototype. Transp Res Rec 1926:96–105

    Article  Google Scholar 

  • Wang J, Wahba M, Miller EJ (2010) A comparison of an agent-based transit assignment procedure (MILATRAS) with conventional approaches city of Toronto transit network. In: Proceedings of the 89th transportation research board annual meeting, Washington DC

    Google Scholar 

  • Watling D (1999) Stability of the stochastic equilibrium assignment problem: a dynamical systems approach. Transp Res B 33:281–312

    Article  Google Scholar 

  • Yperman I (2007) The link transmission model for dynamic network loading. PhD thesis, Katholieke Universiteit Leuven

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guido Gentile .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Gentile, G., Florian, M., Hamdouch, Y., Cats, O., Nuzzolo, A. (2016). The Theory of Transit Assignment: Basic Modelling Frameworks. In: Gentile, G., Noekel, K. (eds) Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems. Springer Tracts on Transportation and Traffic. Springer, Cham. https://doi.org/10.1007/978-3-319-25082-3_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25082-3_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25080-9

  • Online ISBN: 978-3-319-25082-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics