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How do graph properties of road networks influence vehicle miles traveled? A study of 486 urban areas in the United States

Author

Listed:
  • Zhang, Zihe
  • Liu, Jun
  • Fu, Xing
  • Yang, Chenxuan
  • Nie, Qifan
  • Jones, Steven

Abstract

This study delivers a comprehensive investigation of the road networks of 486 urbanized areas in the United States. This study considers a region-to-region macroscopic perspective to discuss the role of road networks in passenger vehicle miles traveled (VMT). The main goal of this study is to quantify the relationship between VMT and region-level road network characteristics as measured by 25 graph-theoretical metrics. Principal Component Analysis (PCA) was performed to reduce the dimensionality of graph metrics and to combine highly correlated measures (e.g., node density and edge density) into uncorrelated principal components. PCA generated five graph-related principal components to describe five aspects of road networks: network size, density, connectivity, complexity, and vulnerability. Random-parameter models were built to relate road network graph properties to VMT per capita and VMT per household. All models showed a significant relationship between passenger VMT and road network variables, including original graph metrics and graph-based principal components. Results implied residents in large urban areas travel more than people in small urban areas; a denser road network could reduce VMT; and more dead ends or 3-way intersections can lead to increased VMT in a region. The findings quantify the impact of roadway characteristics on the VMT variation of US urban areas. This study advances the state-of-the-art by conducting a comprehensive regional-level VMT analysis across all urban areas in the U.S. and identifying key roadway network features associated with high or low VMT per capita and per household. The findings provide valuable policy insights for roadway development, including new regional expansions and improvements to existing road networks (e.g., transportation improvement plans), to support urban planning that fosters a low-carbon transportation system.

Suggested Citation

  • Zhang, Zihe & Liu, Jun & Fu, Xing & Yang, Chenxuan & Nie, Qifan & Jones, Steven, 2025. "How do graph properties of road networks influence vehicle miles traveled? A study of 486 urban areas in the United States," Transport Policy, Elsevier, vol. 171(C), pages 344-358.
  • Handle: RePEc:eee:trapol:v:171:y:2025:i:c:p:344-358
    DOI: 10.1016/j.tranpol.2025.06.018
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    References listed on IDEAS

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    1. LEE, Sungwon & LEE, Bumsoo, 2020. "Comparing the impacts of local land use and urban spatial structure on household VMT and GHG emissions," Journal of Transport Geography, Elsevier, vol. 84(C).
    2. Wong, Yale Z. & Hensher, David A. & Mulley, Corinne, 2020. "Mobility as a service (MaaS): Charting a future context," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 5-19.
    3. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    4. Rentziou, Aikaterini & Gkritza, Konstantina & Souleyrette, Reginald R., 2012. "VMT, energy consumption, and GHG emissions forecasting for passenger transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 487-500.
    5. Su, Qing, 2011. "The effect of population density, road network density, and congestion on household gasoline consumption in U.S. urban areas," Energy Economics, Elsevier, vol. 33(3), pages 445-452, May.
    6. Schaller, Bruce, 2021. "Can sharing a ride make for less traffic? Evidence from Uber and Lyft and implications for cities," Transport Policy, Elsevier, vol. 102(C), pages 1-10.
    7. Tingting Wang & Cynthia Chen, 2014. "Impact of fuel price on vehicle miles traveled (VMT): do the poor respond in the same way as the rich?," Transportation, Springer, vol. 41(1), pages 91-105, January.
    8. Zhao, Chunxue & Fu, Baibai & Wang, Tianming, 2014. "Braess paradox and robustness of traffic networks under stochastic user equilibrium," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 135-141.
    9. repec:osf:socarx:q86sd_v1 is not listed on IDEAS
    10. Greene, David L. & Khattak, Asad J. & Liu, Jun & Wang, Xin & Hopson, Janet L. & Goeltz, Richard, 2017. "What is the evidence concerning the gap between on-road and Environmental Protection Agency fuel economy ratings?," Transport Policy, Elsevier, vol. 53(C), pages 146-160.
    11. Andersson, Öivind & Börjesson, Pål, 2021. "The greenhouse gas emissions of an electrified vehicle combined with renewable fuels: Life cycle assessment and policy implications," Applied Energy, Elsevier, vol. 289(C).
    12. Zhang, Zihe & Liu, Jun & Qian, Xinwu & Guo, Shuocheng & Yang, Chenxuan & Jones, Steven, 2025. "Envisioning shared autonomous vehicles (SAVs) for 374 small and medium-sized urban areas in the United States: The roles of road network and travel demand," Journal of Transport Geography, Elsevier, vol. 127(C).
    13. Jun Liu & Kara M. Kockelman & Patrick M. Boesch & Francesco Ciari, 2017. "Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation," Transportation, Springer, vol. 44(6), pages 1261-1278, November.
    14. Melinda Matyas & Maria Kamargianni, 2019. "The potential of mobility as a service bundles as a mobility management tool," Transportation, Springer, vol. 46(5), pages 1951-1968, October.
    15. Nasri, Arefeh & Zhang, Lei, 2014. "The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas," Transport Policy, Elsevier, vol. 32(C), pages 172-179.
    16. Geoff Boeing, 2020. "A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood," Environment and Planning B, , vol. 47(4), pages 590-608, May.
    17. Lei Zhang & Jin Hyun Hong & Arefeh Nasri & Qing Shen, 2012. "How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 40-52.
    18. Zhang, Zihe & Liu, Jun & Bastidas, Javier Pena & Jones, Steven, 2024. "Charging infrastructure assessment for shared autonomous electric vehicles in 374 small and medium-sized urban areas: An agent-based simulation approach," Transport Policy, Elsevier, vol. 155(C), pages 58-78.
    19. M i Diao & Joseph Ferreira Jr, 2014. "Vehicle Miles Traveled and the Built Environment: Evidence from Vehicle Safety Inspection Data," Environment and Planning A, , vol. 46(12), pages 2991-3009, December.
    20. Alejandro Henao & Wesley E. Marshall, 2019. "The impact of ride-hailing on vehicle miles traveled," Transportation, Springer, vol. 46(6), pages 2173-2194, December.
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