Real-time estimation of travel time using low frequency GPS data from moving sensors

This research is based on the development and application of a methodology which uses GPS data to reliably estimate travel time in real-time while considering the factors including vehicle fleet sample size, data sampling frequency and time window length in the estimation process. Specifically, the purpose of this thesis was to first determine the accurate location of a vehicle travelling on a road link by applying a map-matching algorithm at a range of sampling frequencies to reduce the potential errors associated with GPS and digital road maps, for example where vehicles are sometimes assigned to the wrong road links. Secondly, four different methods have been developed to estimate link travel time based on map-matched GPS positions and speed data from low frequency data sets in three time windows lengths (i.e. 5, 10 and 15 minutes). These are based on vehicle speeds, speed limits, link distances and average speeds; initially only within the given link but subsequently in the adjacent links too. The results were then validated against reference travel time data collected from 4,126 vehicles by high resolution video cameras, and these indicate that factors such as vehicle sample size, data sampling frequency, vehicle coverage on the links and time window length all influence the accuracy of link travel time estimation.

Language

  • English

Media Info

  • Pagination: 1 file

Subject/Index Terms

Filing Info

  • Accession Number: 01489873
  • Record Type: Publication
  • Source Agency: ARRB
  • Files: ATRI
  • Created Date: Aug 15 2013 9:49AM