Comparing Location-Based and Home Address–Based Approaches in Evaluating the Cost to Society of Crashes and Congestion

Abstract

Traffic congestion and safety pose two of the largest challenges for transportation planners and engineers worldwide, placing significant economic, environmental, and social burdens on the public. In the United States crashes were estimated to have cost the American public $340 billion in 2019, with congestion costs estimated to be over $166 billion in 2017. With funding from the Infrastructure Investment and Jobs Act (IIJA) becoming available to transportation agencies around the country, it is vital that agencies identify the most impactful infrastructure projects on which to prioritize funding to address these costs. At the same time, the United States is seeking to address the lack of infrastructure spending in disadvantaged communities in previous decades. To guide this infrastructure spending, data are required to properly identify the locations most in need of funding. This study assesses the trade-off between data accuracy and data availability in two methodologies to estimate the cost to society of crashes and congestion, focusing on the comparison between county-level location-based aggregation and home address–based approaches. The study assessed crash data in the state of Massachusetts and used the results of the Boston Region Metropolitan Planning Organization’s TDM23 travel demand model to evaluate these trade-offs. The study found that the county-level location-based aggregation acceptably mitigated for the unknown home addresses of those involved when creating a metric for the cost to society of crashes. By contrast, it did not mitigate well for the costs of congestion.