The defense will take place at "Maison des Sciences de l’Homme de Dijon" (6 esplanade Erasme, 21000 DIJON). This work was co-directed by Thomas Thévenin and Nadège Martiny.

Defense jury

BADARIOTTI Dominique, Professor at the University of Strasbourg

JOSSELIN Didier, Research Director at the CNRS, ESPACE

MARILLEAU Nicolas, Research Engineer at the IRD-UMMISCO, UPMC

MARTINY Nadège, Associate Professor at the University of Bourgogne-Franche-Comté

SANDERS Lena, Research Director at the CNRS, Géographie-Cités

THEVENIN Thomas, Professor at the University of Bourgogne-Franche-Comté

Abstract

Based on surveys, traffic is constructed from assumptions about the relationship between origins and destinations. In order to rebuild a road traffic wich would be closer to observation and on a wider set of road sections, it appears interesting to use counting data from urban sensors : this is our starting point of view. The insertion of these in-situ dataset in the road traffic measurement provides the opportunity to experience the potential of sensors to estimate Traffic Air Pollution (TAP) levels at the intraurban scale. However, this requires to change the nature of these estimation, here through the construction of a model of multi-agents simulation, in order to extract more information on the road traffic. More generally, this work can be seen as a a knowledge building approach on TAP emisssions which is discussed throughout this work.

The implementation of the SCAUP (multi-agent simulation from Urban sensors for traffic air pollution) approach was developped in three stages: 1. Focusing on the quantification of road traffic devices through urban sensors; 2. Proposing a modeling approach for road traffic data simulation ; 3. Using as a reference the national framework used by AASQA to calculate RTA emissions. All is integrated within a technical matrix that forms the spine of the manuscript through three interrelated systems: quantification, modeling and evaluation. This work is part of an experimental approach dedicated to the calculation of TAP emissions based on traffic simulations. Sponsored by the ATMOSF’AIR BOURGOGNE local AASQA, this work could also be used in an operational mode for these organizations in charge of the air quality monitoring. At a time when the big data enters into new questions about the ability of researchers to extract knowledge, we propose a geographical approach that enables to replace the data in the center of an original road traffic simulation approach (data- driven).