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Traffic Flow Variation and Network Structure

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Abstract

This study defines and detects competitive and complementary links in a complex network and constructs theories illustrating how the variation of traffic flow is interconnected with network structure. To test the hypotheses, we extract a grid-like sub-network containing 140 traffic links from the Minneapolis - St. Paul highway system. We reveal a real-world traffic network comprises both competitive and complementary links, and there is a negative network dependency between a competitive link pair and a positive network dependency between a complementary link pair. We validate a robust linear relationship between standard deviation of flow in a link and its number of competitive links, its link correlation with competitive links, and its network dependency with both competitive and complementary links. The results indicate the number of competitive links in a traffic network is negatively correlated with the variation of traffic flow in congested regimes as drivers are able to take alternative paths. The results also signify that the more the traffic flow of a link is correlated to the traffic flow of its competitive links, the more the flow variation is in the link. Considering the network dependency, however, it is corroborated that the more the network dependency between a link and its competitive links, the more the flow variation in the link. This is also true for complementary links.

Suggested Citation

  • Alireza Ermagun & David Levinson, 2017. "Traffic Flow Variation and Network Structure," Working Papers 000167, University of Minnesota: Nexus Research Group.
  • Handle: RePEc:nex:wpaper:trafficflowvariation
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    File URL: http://hdl.handle.net/11299/189879
    File Function: First version, 2017
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    References listed on IDEAS

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    1. Clark, Stephen & Watling, David, 2005. "Modelling network travel time reliability under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 119-140, February.
    2. Alireza Ermagun & Snigdhansu Chatterjee & David Levinson, 2017. "Using temporal detrending to observe the spatial correlation of traffic," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-21, May.
    3. Chang, Justin S., 2010. "Assessing travel time reliability in transport appraisal," Journal of Transport Geography, Elsevier, vol. 18(3), pages 419-425.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Traffic flow variations; Reliability; Competitive links; Weight matrix; Network structure;
    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
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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