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Prévoir la demande de transport

Author

Listed:
  • Patrick Bonnel

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

Abstract

L'ambition de cet ouvrage est d'offrir un état des connaissances sur la prévision de la demande de déplacements de personnes en milieu urbain. Sa conception permet son utilisation comme support de formation à la modélisation. Il présente les fondements théoriques des modèles de prévision de la demande ainsi que les différents outils s'appliquant aux quatre étapes traditionnelles de la modélisation : génération de la demande, distribution des déplacements, répartition modale et affectation des déplacements. Pour chacune de ces étapes de la prévision sont détaillées les principales familles de modèles disponibles pour la traiter en mettant en évidence les concepts de base qui sous-tendent les modèles et les principales limites de ceux-ci, tenant aux hypothèses – souvent implicites – ou aux données nécessaires à leur utilisation. Au-delà de cette présentation, la particularité de cet ouvrage est d'offrir une analyse de l'ensemble du processus de prévision en incluant notamment l'identification des objectifs, la production des données et l'analyse de la demande. Enfin, il fournit des grilles de lecture des modèles permettant l'analyse de leur performance.

Suggested Citation

  • Patrick Bonnel, 2004. "Prévoir la demande de transport," Post-Print halshs-00077292, HAL.
  • Handle: RePEc:hal:journl:halshs-00077292
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    Citations

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    Cited by:

    1. Cabrera Delgado, Jorge & Bonnel, Patrick, 2016. "Level of aggregation of zoning and temporal transferability of the gravity distribution model: The case of Lyon," Journal of Transport Geography, Elsevier, vol. 51(C), pages 17-26.
    2. Ouassim Manout & Patrick Bonnel & François Pacull, 2021. "Spatial Aggregation Issues in Traffic Assignment Models," Networks and Spatial Economics, Springer, vol. 21(1), pages 1-29, March.
    3. Alain Bonnafous & Yves Crozet & Aurélie Mercier & Nicolas Ovtracht & Valérie Thiebaut, 2009. "MOSART (MOdélisation et Simulation de l'Accessibilité aux Réseaux et aux Territoires) : un prototype d'outil d'aide à la décision, individuelle et collective pour une mobilité durable. Rapport final," Working Papers halshs-01707182, HAL.
    4. Alain Bonnafous & Pablo Jensen & William Roy, 2006. "Le cofinancement usager - contribuable et le partenariat public-privé changent les termes de l'évaluation des programmes d'investissement public," Economie & Prévision, La Documentation Française, vol. 0(4), pages 15-30.
    5. Jean Patrick Mfoulou Olugu & Jean Patrick & Mfoulou Olugu, 2017. "Urban Form, Mobility Behavior And Dysfunction Of Transport Supply: The Case Of Yaoundé ," Post-Print hal-01773468, HAL.
    6. Manout, Ouassim & Bonnel, Patrick & Bouzouina, Louafi, 2018. "Transit accessibility: A new definition of transit connectors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 88-100.
    7. Abraham, Claude & Bonnafous, Alain & Ray, Jean-Baptiste, 2021. "Statistical distribution of time values and underestimation of the benefits of speed," Transport Policy, Elsevier, vol. 113(C), pages 27-36.
    8. Manel Daldoul & Sami Jarboui & Ahlem Dakhlaoui, 2016. "Public transport demand: dynamic panel model analysis," Transportation, Springer, vol. 43(3), pages 491-505, May.
    9. Mohsen Nazem & Martin Trépanier & Catherine Morency, 2015. "Revisiting the destination ranking procedure in development of an Intervening Opportunities Model for public transit trip distribution," Journal of Geographical Systems, Springer, vol. 17(1), pages 61-81, January.
    10. Mirkan Geyik & Patrick Bonnel, 2016. "Évolution de l’usage des modes de transport - Analyse des facteurs explicatifs : application à l’agglomération lyonnaise," Working Papers halshs-01685748, HAL.
    11. Mariem Fekih & Tom Bellemans & Zbigniew Smoreda & Patrick Bonnel & Angelo Furno & Stéphane Galland, 2021. "A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)," Transportation, Springer, vol. 48(4), pages 1671-1702, August.

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