Title :
Tracking Heavy Vehicles Based on Weigh-In-Motion and Inductive Loop Signature Technologies
Author :
Shin-Ting Jeng ; Lianyu Chu
Author_Institution :
CLR Analytics Inc., Irvine, CA, USA
Abstract :
Weigh-in-motion (WIM) has been employed as a major technology to collect heavy vehicles´ data on the freeways. Because WIM is one of the most costly and sophisticated data collection systems, how to effectively utilize the valuable WIM data and monitor the performance of WIM stations are particularly important. In this paper, we proposed an innovative and yet practical approach for heavy vehicle tracking that combines the use of both WIM data and the inductive loop signature data. The proposed multilevel vehicle reidentification approach was able to generate promising tracking performance with both inductive loop signatures and WIM data applied.
Keywords :
object tracking; traffic engineering computing; WIM stations; data collection systems; heavy vehicle tracking; inductive loop signature technologies; inductive loop signatures; multilevel vehicle reidentification approach; performance monitoring; weigh-in-motion; Axles; Data collection; Detectors; Feature extraction; Licenses; Tracking loops; Vehicles; Inductive loop signature; travel time estimation; truck tracking; vehicle reidentification; weigh-in-motion (WIM);
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2014.2333003