Abstract
Traffic congestion is an ever-increasing issue across urban environments in the US. One potential mitigation strategy is to improve our understanding of how the geographical patterns of urban land use influence congestion. Unfortunately, there is no consensus regarding if more sprawling or dense urban morphologies help mitigate congestion issues. To potentially clarify the conflicting findings of previous studies, we used a detailed spatial metric-based approach and panel regression to quantify the relationships between urban development patterns and congestion in 98 US urban areas from 2001 to 2011. We found that the abundance and spatial configuration of urban land uses were correlated with traffic congestion. Specifically, high degrees of polycentricity for both high-intensity and low-intensity urban land uses were associated with more congestion, while contiguous residential development was correlated with less congestion. Important distinctions were also observed between different congestion measures, as urban morphology exhibited a more substantial influence on overall congestion than rush-hour congestion. Our findings can potentially inform future land use planning by clarifying which urban morphologies alleviate traffic congestion issues.
Highlights
Traffic congestion is a global phenomenon influenced by economics, population growth, transportation infrastructure, and the ever-increasing availability of ridesharing and delivery services
An extensive number of metrics are available within the FRAGSTATS software, but this study focused on spatial metrics previously used to quantify the geographical patterns of urban development (e.g., Debbage, Bereitschaft, & Shepherd, 2016; Herold et al, 2005; Kang, Ma, Tong, & Liu, 2012)
Several panel regression models were estimated to quantify the re lationships between the three congestion measures and the urban morphological characteristics evaluated via the spatial metrics (Tables 2–4)
Summary
Traffic congestion is a global phenomenon influenced by economics, population growth, transportation infrastructure, and the ever-increasing availability of ridesharing and delivery services. Larger cities generally exhibit higher congestion levels (Chang, Lee, & Choi, 2017), the negative consequences of traffic, including the loss of time, increase of urban pollution, and rise of accidents, are pervasive throughout many urban centers. Congestion enhances the price of freight movement by increasing oper ating costs and decreasing reliability. In terms of human health, congestion reduces air quality by enhancing traffic-related air pollutants such as NOx and CO (Zhang & Batterman, 2013; Zheng, de Beurs, Owsley, & Henebry, 2019), and it jeopardizes road safety by increasing the fatality and injury accident rates (Wang, Quddus, & Ison, 2013)
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