Application of Computer Vision for Estimation of Moving Vehicle Weight

Heavy vehicle weights need to be closely monitored for preventing fatigue-induced deterioration and critical fractures to highway infrastructure, among many other purposes, but development of a cost-effective weigh-in-motion (WIM) system remains challenging. This paper describes the creation and exp...

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Bibliographic Details
Published in:IEEE sensors journal 2021-05, Vol.21 (10), p.11588-11597
Main Authors: Feng, Maria Q., Leung, Ryan Y.
Format: Article
Language:English
Subjects:
Area measurement
Cameras
Computer vision
Contact pressure
Deformation
Edge detection
Fractures
Heavy vehicles
Image edge detection
non-contact measurement
Object recognition
Optical character recognition
Parameters
Roads
Sensors
Strain
tire
Tires
Vision systems
weigh-in-motion
Weighing in motion
weight measurement
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Summary:Heavy vehicle weights need to be closely monitored for preventing fatigue-induced deterioration and critical fractures to highway infrastructure, among many other purposes, but development of a cost-effective weigh-in-motion (WIM) system remains challenging. This paper describes the creation and experimental validations of a computer vision-based non-contact WIM system. The underlining physics is that the force exerted by each tire onto the road is the product of the tire-road contact pressure and contact area. Computer vision is applied (1) to measure the tire deformation parameters so that the tire-roadway contact area can be accurately estimated; and (2) to recognize the marking texts on the tire sidewall so that the manufacturer-recommended tire inflation pressure can be found. In this research, a computer vision system is developed, which is comprised of a camera and computer vision software for measuring tire deformation parameters and recognizing the tire sidewall markings from images of individual tires of a moving vehicle. Computer vision techniques such as edge detection and optical character recognition are applied to enhance the measurement and recognition accuracy. Field experiments were conducted on fully loaded or empty concrete trucks and the truck weights estimated by this novel computer vision-based non-contact WIM system agreed well with the curb weights verified by static weighing. This research has demonstrated a novel application of the computer vision technology to solve a challenging vehicle WIM problem. Requiring no sensor installation on the roadway or the vehicle, this cost-effective non-contact computer vision system has demonstrated a great potential to be implemented.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2020.3038186