Investigating Optimal Aggregation Interval Sizes of Loop Detector Data for Travel Time Estimation and Prediction

With recent increases in the deployment of ITS technologies, traffic management centers have the ability to obtain and archive large amounts of data regarding the traffic system. This data can then be employed in estimations of current conditions and the prediction of future conditions on the roadway network. In this paper, we propose a general solution methodology for the identification of the optimal aggregation interval sizes of loop detector data for four scenarios: i) link travel time estimation, ii) corridor/route travel time estimation, iii) link travel time forecasting, and iv) corridor/route travel time forecasting. This study applied Cross Validated Mean Square Error (CVMSE) model for the link and route travel time estimations, and a Forecasting Mean Square Error (FMSE) model for the link and corridor/route travel time forecasting. These models were applied to loop detector data obtained from the Kyeongbu expressway in Korea. It was found that the optimal aggregation sizes for the travel time estimation and forecasting were three to five minutes and 10 to 20 minutes, respectively.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; References;
  • Pagination: 29p
  • Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

Filing Info

  • Accession Number: 01043554
  • Record Type: Publication
  • Report/Paper Numbers: 07-0611
  • Files: TRIS, TRB
  • Created Date: Feb 8 2007 5:12PM