EVALUATING SYSTEM ATMIS TECHNOLOGIES VIA RAPID ESTIMATION OF NETWORK FLOW

This research focuses on the relevance of rapid flow prediction models to the bridge retrofit criteria used by the California Department of Transportation (Caltrans). The objective is to provide dependable estimates of network flows given changes in link configuration, and to attach these changes to the decision-making procedures Caltrans uses to make bridge retrofit decisions.

• Supplemental Notes:
  • Publication Date: 1995 Published By: California PATH Program, Institute of Transportation Studies, University of California, Berkeley CA Remarks: Confidential; for internal use only
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  University of Southern California, Los Angeles

  School of Urban and Regional Planning, University Park
  Los Angeles, CA  United States  90007

  California Department of Transportation

  1120 N Street
  Sacramento, CA  United States  95814
• Authors:
  • Moore, James E
• Publication Date: 1995

Language

• English

Media Info

• Pagination: 213 p.
• Serial:
  • California PATH reports to Caltrans ; 95-C10
  • Publisher: University of California, Berkeley

Subject/Index Terms

• TRT Terms: Artificial intelligence; Highway capacity; Traffic estimation
• Subject Areas: Data and Information Technology; Highways;

Filing Info

• Accession Number: 00774637
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH, STATEDOT
• Created Date: Nov 17 1999 12:00AM