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Investigating the Efficiency of a Gradient Approximation Approach for the Solution of Dynamic Demand Estimation Problems

In: New Developments in Transport Planning

Author

Listed:
  • Ernesto Cipriani
  • Michael Florian
  • Michael Mahut
  • Marialisa Nigro

Abstract

Traffic assignment is a set of criteria through which the demand for mobility is distributed over the links of a transport network. Over the last 30 years, Dynamic Traffic Assignment (DTA) models have been developed to support time-dependent analyses in nascent fields that need to take into account the temporal distribution of demand and supply. In this book, leading international experts in the field provide a state-of-the-art overview of fundamental DTA research and practice, identifying weaknesses and major challenges for future research.

Suggested Citation

  • Ernesto Cipriani & Michael Florian & Michael Mahut & Marialisa Nigro, 2010. "Investigating the Efficiency of a Gradient Approximation Approach for the Solution of Dynamic Demand Estimation Problems," Chapters, in: Chris M.J. Tampere & Francesco Viti & Lambertus H. (Ben) Immers (ed.), New Developments in Transport Planning, chapter 18, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:13831_18
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    References listed on IDEAS

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    1. Jin, Wen-Long, 2007. "A dynamical system model of the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 32-48, January.
    2. Han, Sangjin, 2003. "Dynamic traffic modelling and dynamic stochastic user equilibrium assignment for general road networks," Transportation Research Part B: Methodological, Elsevier, vol. 37(3), pages 225-249, March.
    3. Nie, Yu & Zhang, H. M. & Lee, Der-Horng, 2004. "Models and algorithms for the traffic assignment problem with link capacity constraints," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 285-312, May.
    4. Hoogendoorn, Serge P. & Bovy, Piet H. L., 2004. "Dynamic user-optimal assignment in continuous time and space," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 571-592, August.
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