Intégration de la mobilité et des activités quotidiennes à l'aide de modèles multi-agents lors de l'évaluation de l'exposition au bruit à l'échelle métropolitaine

Environmental noise is a major problem to be confronted in urban areas due to its detrimental health outcomes, and social and economic costs. According to the World Health Organization, approximately one-third of Europeans experience environmental noise-related disturbances during the daytime with approximately one-fifth having their sleep disturbed by traffic noise alone. Noise health impacts are intensified with urbanization which is associated with an increase in the diversity of noise sources. With the objective of establishing a legal framework to address environmental noise, the European Union passed the Environmental Noise Directive and formulated a Common Noise Assessment Methods based on numerical modeling. The European method has strong limitations: (1) the location of the individuals is static as it is assumed that individuals are fixed to their homes; (2) the exposure is estimated based on long-term noise doses, usually daily or annual energetic averages, neglecting detailed noise dynamics; (3) the assessment of the socio-economic groups the most affected by noise is not promoted and the exposed population is treated as homogeneous, without intra-population variability in noise reactions. In parallel, a new generation of studies in environmental health research, inspired by the theories of time geography and spatial ecology, advocates for the integration of mobility and everyday activities in public health research to study the exposure phenomena as a complex spatio-temporal process. One solution for improving noise exposure assessments is the implementation of agent-based exposure frameworks. These frameworks simulate an everyday activity plan for each individual of a modeled population over a 24-hours of a typical working weekday. These individual-level exposure assessments allow the estimation of both agents' trajectories and the noise conditions they encounter over different activity contexts. However, it is very important to understand the relevance of these assessments within the context of models initially designed for transport studies. Then, the initial objective of this doctoral thesis is to situate the exposure estimation with agent-based models in relation to other exposure assessment methodologies, identifying its limitations, its strengths, and the avenues for its enhancement. Furthermore, there is still limited knowledge regarding the utilization and formulation of analyses based on these results. Consequently, the second objective is to develop innovative assessment frameworks, metrics, and indicators in the context of contemporary urban noise problems. To this end, two studies have been conducted: (a) a spatio-temporal assessment of the accessibility of a population to quiet areas, and (b) an assessment of critical exposure areas over the clock in the context of formulating Noise Action Plans. These studies rely on an open-source scenario applied to the Lyon Metropolitan Area composed of three main tools: EQASim, MATSim and NoiseModelling. EQASim is utilized for the modeling of the synthetic population, the assignment of activity plans to agents, and the modeling of transport infrastructure and services. MATSim is utilized for the agent-based transport simulation utilizing the synthetic population and transportation system previously modeled by EQASim. NoiseModelling is utilized to characterize noise from different transport traffic flows and environmental sources. It then calculates sound propagation and estimates the environmental noise conditions. The findings of this study underscore the imperative of conceptualizing exposure assessment as a multifaceted process encompassing four modeling dimensions: the representation of space, time, the individual, and his trajectory of activities. (...)