Software-Based Vehicle Reidentification with Existing Loop Infrastructure

• Published in: Transportation research record Vol. 2443; no. 1; pp. 56 - 62
• Main Authors: Kwon, Jaimyoung, Petty, Karl
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2014
• Subjects: Algorithms; Calibration; Estimates; Hardware; Infrastructure; Segments; Transportation; Vehicles
• ISBN: 0309295319; 9780309295314
• ISSN: 0361-1981; 2169-4052
• DOI: 10.3141/2443-07

This paper describes the development of a hybrid reidentification algorithm to estimate travel times entirely on the basis of data that are readily available from single loop detectors (60-Hz vehicle occupancy data) without the need for additional hardware in the field. The key concept is data fusion, which combines crude and potentially inaccurate spot-point estimates with a software-based signature-matching algorithm. The method was applied to real data from an urban freeway site with four locations and six segments, with Bluetooth-matched travel time as the ground truth. The method performed satisfactorily, with a relative error of 9% for a segment 1.54 mi long, among others. It removed bias and improved the baseline spot-speed method significantly. The approach requires minimum calibration with no additional hardware. The method, therefore, proves suitable for widespread deployment and provides a clear path for agencies to leverage their existing loop and controller infrastructure for accurate travel time estimation through reidentification.