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Network Structure and Spatial Separation

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Abstract

The objective of this research is to identify the role of network architecture in influencing individual travel behavior using travel survey data from two urban areas in Florida: Fort Lauderdale and Miami. Various measures of network structure, compiled from existing sources, are used to quantify roadway networks, capture the arrangement and connectivity of nodes and links in the networks and the temporal and spatial variations that exist among and within networks. The results from the regression models estimated show that network design influences how people travel and make decisions. Results from this analysis can be used to understand how changes in network can be used to bring about desired changes in travel behavior.

Suggested Citation

  • Pavithra Parthasarathi & Hartwig Hochmair & David Levinson, 2009. "Network Structure and Spatial Separation," Working Papers 000069, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:networkstructuretraveldistance
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    File URL: http://hdl.handle.net/11299/180021
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    Cited by:

    1. Parthasarathi, Pavithra & Levinson, David, 2018. "Network structure and the journey to work: An intra-metropolitan analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 292-304.
    2. Mengying Cui & David Levinson, 2018. "Accessibility analysis of risk severity," Transportation, Springer, vol. 45(4), pages 1029-1050, July.
    3. David Giacomin & Luke James & David Levinson, 2012. "Trends in Metropolitan Network Circuity," Working Papers 000106, University of Minnesota: Nexus Research Group.
    4. Mengying Cui & David Levinson, 2015. "Accessibility and the Ring of Unreliability," Working Papers 000133, University of Minnesota: Nexus Research Group.
    5. Janson, Michael & Levinson, David, 2014. "HOT or not," Research in Transportation Economics, Elsevier, vol. 44(C), pages 21-32.
    6. Huang, Arthur & Levinson, David, 2017. "A model of two-destination choice in trip chains with GPS data," Journal of choice modelling, Elsevier, vol. 24(C), pages 51-62.
    7. Pavithra Parthasarathi & Hartwig Hochmair & David Levinson, 2015. "Street network structure and household activity spaces," Urban Studies, Urban Studies Journal Limited, vol. 52(6), pages 1090-1112, May.
    8. Tsou, Ko-Wan & Cheng, Hao-Teng & Tseng, Fu-Yi, 2015. "Exploring the relationship between multilevel highway networks and local development patterns—a case study of Taiwan," Journal of Transport Geography, Elsevier, vol. 43(C), pages 160-170.
    9. Pavithra Parthasarathi & David Levinson & Hartwig Hochmair, 2013. "Network Structure and Travel Time Perception," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-13, October.
    10. Katrien Ramaekers & Sofie Reumers & Geert Wets & Mario Cools, 2013. "Modelling Route Choice Decisions of Car Travellers Using Combined GPS and Diary Data," Networks and Spatial Economics, Springer, vol. 13(3), pages 351-372, September.
    11. Hochmair, Hartwig H. & Bardin, Eric & Ahmouda, Ahmed, 2019. "Estimating bicycle trip volume for Miami-Dade county from Strava tracking data," Journal of Transport Geography, Elsevier, vol. 75(C), pages 58-69.
    12. Carlos Carrion & David Levinson, 2019. "Overestimation and underestimation of travel time on commute trips: GPS vs. self- reporting," Working Papers 2019-05, University of Minnesota: Nexus Research Group.
    13. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.
    14. Lei Kang & Chao Yang & Jeffrey C Peters & Peng Zeng, 2016. "Empirical analysis of road networks evolution patterns in a government-oriented development area," Environment and Planning B, , vol. 43(4), pages 698-715, July.
    15. Xiubin B. Wang & Xiaowei Cao & Kai Yin & Teresa M. Adams, 2017. "Modeling Vehicle Miles Traveled on Local Roads Using Classification Roadway Spatial Structure," Networks and Spatial Economics, Springer, vol. 17(3), pages 713-735, September.

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    More about this item

    Keywords

    Network structure; travel behavior; transport geography; commuting; circuity;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations

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