Vehicle reidentification as method for deriving travel time and travel time distributions: Investigation

Carlos Sun, Glenn Arr, Ravi Ramachandran

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Vehicle reidentification was investigated as a method for deriving travel time and travel time distributions with loop and video detectors. Vehicle reidentification is the process of tracking vehicles anonymously from site to site to produce individual vehicle travel times and overall travel time distribution. Travel time and travel time distribution are measures of the performance and reliability of the transportation system and are useful in many transportation applications such as planning, operations, and control. Findings from the investigation included (a) results from a platoon reidentification algorithm that improved upon a previous individual vehicle reidentification algorithm, (b) sensitivity analysis on the effect of time windows in deriving travel times, and (c) derivation and goodness of fit of travel time distributions using vehicle reidentification. Arterial data from Southern California were used in testing the algorithm's performance. Test results showed that the algorithm can reidentify vehicles with an accuracy of greater than 95.9% with 92.4% of total vehicles; can calculate individual travel times with approximately 1% mean error with the most effective time window; and can derive travel time distributions that fit actual distributions at a 9% confidence level.

Original languageEnglish (US)
Pages (from-to)25-31
Number of pages7
JournalTransportation Research Record
Issue number1826
StatePublished - Oct 21 2003

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Vehicle reidentification as method for deriving travel time and travel time distributions: Investigation'. Together they form a unique fingerprint.

Cite this