Abstract
Intermodality refers to the combination of multiple transportation modes during a single trip. It can help reduce carbon emissions, especially in rural and peri-urban areas where public transit can be hard to reach by walking. Yet, since only about 1% of trips in France are intermodal, studying this behavior is difficult. This study introduces MobiSurvStd, an open-source tool that standardizes French mobility survey data. With this tool, I combine data from 68 surveys conducted between 2008 and 2022 to build a detailed dataset representing travel patterns across France. The analysis shows that most intermodal trips combine car use with public transit. In these trips, the public-transit segment is more than 3 times longer than the car segment. Trips that start by car and continue with public transit often link outer areas to city centers, with trains and coaches being the most common transit mode used to access the network. The final part of this study links survey data with the actual locations of public-transit stops to test whether travelers choose the closest train station to their departure point. The results offer insights for transportation planners aiming to design multimodal hubs that make sustainable intermodal travel more convenient.
Keywords
Intermodalité; Enquête mobilité; Standardisation d'enquêtes; Park-and-RideBibtex (click to select)
@unpublished{Javaudin2025,
author = "Lucas Javaudin",
title = {{Aggregating Mobility Surveys to Understand Intermodality: Evidence from 68 French Surveys}},
year = 2025,
month = 11,
}