Road Sectional Characteristic Cluster Model for Urban Expressways

In order to select highly-correlated sectional samples in building the relationship models between physical characteristic parameters and traffic flow characteristic parameters the road sectional characteristic cluster model is developed for urban expressways. An improved SAGA-K-Means cluster algorithm is proposed to optimize both number of clusters and the cluster results for physical and traffic flow characteristic matrixes. A cluster matching model for expressways is developed by considering the physical characteristic data and traffic flow characteristic data as two sources of data. The intersection samples of matched physical and traffic flow characteristic clusters are considered as the highly-correlated sectional samples. The proposed road sectional characteristic cluster model is tested using data from 200 expressway sections in Beijing. The result indicates that the proposed model could increase the correlation coefficient values of physical and traffic flow characteristic parameters of road sectional samples.

• Record URL:
  • https://doi.org/10.1061/41186(421)63
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411865
• Supplemental Notes:
  • Copyright © 2011 ASCE
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zhao, Nale
  • Yu, Lei
  • Li, Changcheng
  • Li, Feng
• Conference:
  • 11th International Conference of Chinese Transportation Professionals (ICCTP)
  • Location: Nanjing , China
  • Date: 2011-8-14 to 2011-8-17
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: References;
• Pagination: pp 647-658
• Monograph Title: ICCTP 2011: Towards Sustainable Transportation Systems

Subject/Index Terms

• TRT Terms: Algorithms; Cluster analysis; Expressways; Intersections; Traffic flow; Urban areas
• Geographic Terms: Beijing (China)
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01453819
• Record Type: Publication
• ISBN: 9780784411865
• Files: TRIS, ASCE
• Created Date: Nov 15 2012 12:32PM