LEARNING TO PREDICT THE DURATION OF AN AUTOMOBILE TRIP

In this paper, the authors investigate the use of machine learning and data mining to improve travel time prediction for automobiles. Focus is on a technique which uses direct prediction of transit time. This technique is then applied to data collected from the San Diego freeway system.

Media Info

  • Pagination: p. 219-223

Subject/Index Terms

Filing Info

  • Accession Number: 00777593
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: PATH
  • Created Date: Nov 17 1999 12:00AM