An Investigation in the Use of Vehicle Reidentification for Deriving Travel Time and Travel Time Distributions

This paper presents the results from an investigation in the use of vehicle reidentification for deriving travel time and travel time distributions using loop and video detectors. Vehicle reidentification is the process of tracking vehicles anonymously from site to site thus yielding 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. This paper will present the following findings: 1) the results from a platoon reidentification algorithm that improved upon a previous individual vehicle reidentification algorithm, 2) sensitivity analysis on the effect of time windows in deriving travel times, and 3) the derivation and goodness-of-fit of travel time distributions using vehicle reidentification. Arterial data from Southern California are used in testing the algorithm performance. The test results show that the algorithm can reidentify vehicles with an accuracy of over 95.9% when using 92.4% of total vehicles, calculate individual travel times with approximately 1% mean error using the most effective time window and derive travel time distributions that fit actual distributions at a 99% confidence level.