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A review of models for the temporal distribution of peak traffic demand

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  • Alfa, Attahiru Sule

Abstract

The existing models for predicting the temporal distribution of peak traffic demand are reviewed in this paper. Based on their assumptions and concepts, the models are classified into three groups as follows: deterministic user equilibrium (DUE), stochastic user equilibrium (SUE) and system optimum (SO). The merits and weaknesses of each group are discussed with regards to the validity of their assumptions and computational problems associated with them. Most of the models were developed for the single origin-destination pair with simple network system which is an oversimplification of a practical problem involving multiple origin-destination pairs with complex network systems. This is a major limitation when considering the application of the existing models to real life problems. Directions for future research are then proposed.

Suggested Citation

  • Alfa, Attahiru Sule, 1986. "A review of models for the temporal distribution of peak traffic demand," Transportation Research Part B: Methodological, Elsevier, vol. 20(6), pages 491-499, December.
  • Handle: RePEc:eee:transb:v:20:y:1986:i:6:p:491-499
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    Cited by:

    1. Alfa, Attahiru Sule & Chen, Mingyuan, 1995. "Temporal distribution of public transport demand during the peak period," European Journal of Operational Research, Elsevier, vol. 83(1), pages 137-153, May.
    2. Watling, David, 1996. "Asymmetric problems and stochastic process models of traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 30(5), pages 339-357, October.
    3. Sang Nguyen & Stefano Pallottino & Federico Malucelli, 2001. "A Modeling Framework for Passenger Assignment on a Transport Network with Timetables," Transportation Science, INFORMS, vol. 35(3), pages 238-249, August.
    4. Doan, Kien & Ukkusuri, Satish & Han, Lanshan, 2011. "On the existence of pricing strategies in the discrete time heterogeneous single bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1483-1500.
    5. Bao, Yue & Gao, Ziyou & Xu, Meng & Sun, Huijun & Yang, Hai, 2015. "Travel mental budgeting under road toll: An investigation based on user equilibrium," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 1-17.
    6. David Levinson & Ajay Kumar, 1995. "Activity, Travel, and the Allocation of Time," Working Papers 199505, University of Minnesota: Nexus Research Group.
    7. Spišák, Daniel, 1994. "Two-dimensional diffusion of particles with dipolar-like interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 209(1), pages 42-50.
    8. van Ackere, Ann & Larsen, Erik R., 2004. "Self-organising behaviour in the presence of negative externalities: A conceptual model of commuter choice," European Journal of Operational Research, Elsevier, vol. 157(2), pages 501-513, September.
    9. Watling, David, 2006. "User equilibrium traffic network assignment with stochastic travel times and late arrival penalty," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1539-1556, December.
    10. Chen, Mu-Chen & Wei, Yu, 2011. "Exploring time variants for short-term passenger flow," Journal of Transport Geography, Elsevier, vol. 19(4), pages 488-498.
    11. Wong, Jinn-Tsai, 1997. "Basic concepts for a system for advance booking for highway use," Transport Policy, Elsevier, vol. 4(2), pages 109-114, April.

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