Statistical Properties and Prediction Models of Regional Highway Traffic Distribution

Traffic distribution data are essential basic data for highway network planning, but they are difficult and expensive to obtain. In this study, the statistical properties and prediction models of regional highway traffic distribution are investigated by a practical case of regional highway traffic distribution in Heilongjiang Province, China. The authors build a topologic graph of the highway traffic distribution and present the degree distribution of the topologic graph and the probability distribution of traffic flow between traffic zones. The two distributions show a high level of heterogeneity and follow Zipf’s law. The authors also present the distributions of production and attraction of traffic zones. The results show that production and attraction exhibit a positive linear correlation and a high level of heterogeneity, approximately satisfying a power-law decay. The authors also find that the traffic and the topology are strongly correlated. The authors present three existing models (gravity model, radiation model, and population-weighted opportunities model) and a proposed multifactor-weighted benefits model considering population, GDP, and area (named as MWB model) for the highway traffic distribution. A comparative study shows that the MWB model is more suitable for predicting the highway traffic distribution than the other three models whether predicting accuracy, cost, or efficiency.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Gao, Wei
    • Pei, Yulong
    • Hu, Baoyu
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01697418
  • Record Type: Publication
  • Report/Paper Numbers: 19-01804
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:27AM