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https://nap.nationalacademies.org/catalog/27432/critical-issues-in-transportation-for-2024-and-beyond

Association between Transportation Infrastructure, and its environmental health exposures : Developing a Comprehensive Machine Learning Algorithm

Transportation infrastructure plays a vital role in urban life by providing mobility and accessibility for people and goods, but also bring externalities such as air pollution. Research has been devoted to study negative health outcomes and environmental injustice due to transportation externalities. New methods, however, are still required to overcome the data scarcity and improve the accuracy of existing data which are mostly based on estimations rather than actual exposure effects. Furthermore, while different transportation-related factors are commonly considered individually in estimating exposure impacts, new and innovative approaches are critically needed to predict collective exposures to correlated factors in urban environments. With such more comprehensive and interdisciplinary understanding of the complexity of transportation-related exposures, we also need to move beyond top-down planning approaches, to ones that incorporate the involvement and behavioral reactions of stakeholders to changes in their living environments. This research proposal aims to develop a new exposure modeling based on artificial intelligence. The deep learning algorithm estimates exposure to different aspects of the transportation system by detecting the features in publicly available data such as Google Street View and aerial images. The air quality, active transportation infrastructure, and green spaces are a transportation system aspects that this proposal will estimate population exposure to cover a long range of exposure indices. The research team will implement their modeling framework in two case studies in Dallas Texas and Washington DC with different urban forms and transportation system patterns so the team can compare the outcomes under different conditions. The exposure modeling platform then will be used to launch a user interface that will enable the public user to evaluate their exposure to the transportation system.