Post-doc : Development of a Dynamic Modeling Methodology

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Subject : Development of a Dynamic Modeling Methodology for Urban Mobility with MATSim Using Dynamic Data

MATSim is a widely-used activity-and-agent based simulation framework designed to analyze transportation systems and urban planning.
The MATSim scenariodeveloped for the Île-de-France region utilizes open data and free software, traditionally relying on expensive survey data, which is updated every decade for mobility surveys and annually for household censuses.

However, recent significant shifts in urban mobility patterns in Ile-de-France Region such as the increase in bicycle use from a 3% modal share in 2010 to 11.2% in 2023 , the rise of remote work post-COVID-19 pandemic, and the introduction of Low Emission Zones (LEZ), challenge the model's ability to accurately capture current behaviors.
These factors make the existing MATSim model, which typically depicts a standard day from past surveys, less effective for some mobility studies such as the development of new cycle paths or new public transport lines.
The model struggles to capture both the dynamic and long-term shifts in mobility behavior. This presents a significant limitation for evaluating mobility policies.
To address these limitations, it is essential to integrate into the mobility demand generation process new and more recent sources.

The candidate will join an experienced research team in mobility analysis and traffic estimation with close connections to local and national stakeholders. He will furthermore be part of the Mob Sci-Dat Factory project, in partnership with CEREMA, IGN-ENSG, INRIA, and Université Gustave Eiffel, which aims to improve methods for collecting, processing, and analyzing heterogeneous mobility data.

Compétences techniques et aptitudes

• Experience with multi-agents simulation tools
• Proficiency in data analysis techniques and advanced programming skills, particularly in Python/SQL

Diplôme(s), niveau d'études
PhD in Computer Science, Statistics, Transport Engineering, or a closely related field.

Expérience
Proven experience in applying mobility simulation techniques to real-world case studies, with a focus on analyzing and interpreting complex mobility patterns.

For further information and to apply, please contact:

• Guoxi Feng: guoxi.feng@ifpen.fr
• Azise Oumar Diallo: azise-oumar.diallo@ifpen.fr
• Alexandre Chasse : alexandre.chasse@ifpen.fr

Department of Control, Signal and System, IFP Energies Nouvelles, France