Current limitations and opportunities for improvements of agent-based transport models for noise exposure assessment.

Agent-based models represent a promising approach for simulating transport systems and assessing their environmental noise impact, potentially enhancing standard noise exposure assessments. However, it is very important to understand the relevance of these assessments within the context of models initially designed for transport studies. Then, this research investigates the utilization of agent-based transport models when coupled with environmental models to assess individual exposure to transport-related noise. This is achieved by proposing a method to evaluate this approach across four dimensions: spatial, temporal, individual, and activity patterns. This evaluation is demonstrated and discussed with an exemplification model applied in the Lyon Metropolitan Area using open-source tools (MATSim, EQASim, NoiseModelling), which is a representative framework of the current literature. The findings encompass a range of issues, including the conceptualization of exposure contexts and activity spaces, the resolution of the acoustic content, the disaggregation of data at the individual level, the variability in noise reactions, and the correlation structures between social and exposure profiles. The study contributes to the advancement of exposure assessment with insights for future improvements in the field. Further, it underscores the need for more quantitative analyses and scientific research into momentary noise exposure and social epidemiology.