Sustainable mobility

The environmental performance of mobility systems is linked to energy consumption, emissions of pollutants and greenhouse gases and the effects of disruption and fragmentation of natural habitats due to the construction of transport infrastructure.
Le tram l'une des offres de transport analysées

The modes of transport used to access the buildings depend on their location: quality of service by public transport, facilities for walking and bicycles, facilitation of vehicle sharing and electromobility.

At the École des Ponts ParisTech, the Laboratoire Ville Mobilité Transport designs, develops and improves mobility models for urbanised areas in order to study public transport, car traffic and parking. The objective of this research effort is to predict the effects of systems that are at the origin of road congestion, the quality of service (in terms of discomfort and travel time) and user choices (the mode of travel, itinerary and schedule).

At the level of an agglomeration, the car and public transport networks have been the subject of modelling of supply, demand and uses in order to identify the characteristics of the networks and the prices which allow the collective interest to be optimised. A dynamic parking model has been designed to analyse the distribution of parking spaces and variations in demand with the aim of identifying scenarios where supply and demand strike a balance.

Regarding the local impacts of means of transport on the environment, an evaluation method has been developed to quantify the impacts generated by individual on the move according to the journeys that person has made, the speed conditions and the vehicles used (motorisation and occupancy rate). The proposed method also makes it possible to measure the impacts generated or suffered in a given place.

Scientific publications
Journal articles
Nicolas Coulombel, Virginie Boutueil, Liu Liu, Vincent Viguie et al. Substantial rebound effects in urban ridesharing: Simulating travel decisions in Paris, France
Transportation Research Part D: Transport and Environment, 2019, 71, pp. 110-126. ⟨10.1016/j.trd.2018.12.006⟩
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Journal articles
Biao Yin, Liu Liu, Nicolas Coulombel, Vincent Viguie Appraising the environmental benefits of ride-sharing: The Paris region case study
Journal of Cleaner Production, 2018, 177, pp.888-898. ⟨10.1016/j.jclepro.2017.12.186⟩
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Journal articles
Nicolas Coulombel, Laetitia Dablanc, Mathieu Gardrat, Martin Koning The environmental social cost of urban road freight: Evidence from the Paris region
Transportation Research : Part D, Transport and Environment, 2018, 63, pp 514-532. ⟨10.1016/j.trd.2018.06.002⟩
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Conference papers
Fabien Li, Sheng Badia Structural design of a hierarchical urban transit network integrating modal choice and environmental impacts
EWGT 2018, Euroworking Group on Transportation, Sep 2018, Braunschweig, Germany. pp.99-106, ⟨10.1016/j.trpro.2018.12.171⟩
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Journal articles
Nicolas Coulombel Why housing and transport costs should always be considered together: A monocentric analysis of prudential measures in housing access
Transport Policy, 2018, 65, pp.89-105. ⟨10.1016/j.tranpol.2017.04.011⟩
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Journal articles
Fabien Leurent, Virginie Boutueil L'électromobilité : Une décennie de développement
TEC Mobilité intelligente [Revue TEC : Transport Environnement Circulation], 2018
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Project
The trips generated by a neighbourhood are quantified and characterised using models for forecasting transport demand. The environmental impacts associated with these trips are then estimated using an LCA-type approach
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Researcher
Cyrille François
Postdoctoral Researcher and Teacher
École des Ponts ParisTech
LVMT
Practitioner groups
Vegetated tramway
Research work on mobility at the neighbourhood level focuses on the development of environmental impact assessment methods that make it possible to better plan the offer of mobility services in the broad sense
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Anonymous GPS data as resource to reduce transport environmental impact
L'analyse de la mobilité à partir de traces numériques permet de mieux connaître le déplacement des individus. Des nouvelles formes de données, ainsi que des méthodes d'intelligence artificielle, peuvent
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