Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.
Load-balancing and synchronisation for parallel agent-based road traffic simulation
