Non-contact vehicle weighing method based on tire-road contact model and computer vision techniques. (15th July 2022)

• Record Type: Journal Article
• Authors: Kong, Xuan; Zhang, Jie; Wang, Tengyi; Deng, Lu; Cai, C.S.
• Is Part Of: Mechanical systems and signal processing. Volume 174(2022)
• Publication Date: 2022-07-15
• Subjects: Vehicle weigh-in-motion -- Computer vision -- Tire-road contact -- Image segmentation -- Character recognition; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109093
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: Vehicle overloading is a very common phenomenon. The overloaded vehicles not only cause severe damage to the road/bridge and shorten its service life, but also likely lead to traffic accidents. Therefore, the identification of vehicle load is of great importance to the management of overload vehicles and can also provide valuable information for the design and maintenance of transportation infrastructures. The commonly used vehicle weighing methods including static weighing, pavement weigh-in-motion (PWIM), and bridge weigh-in-motion (BWIM) are contact technologies with weakness such as cumbersome installation, poor durability, short service life, and high maintenance cost. It is desirable to have a non-contact vehicle weight identification method without any sensor or scales on/under the road and bridge. Thus, the present study proposed a non-contact method based on the tire-road contact model and computer vision techniques. Firstly, the tire-road contact model is theoretically derived based on the Hertz contact theory, and the relationship between the tire vertical force and the tire deformation is obtained. Then, computer vision techniques such as the image segmentation and character recognition are adopted for the identification of the tire deformation and inflation pressure that are combined with the theoretical model to determine the tire vertical force and then the vehicle weight. Finally, the field test on passenger cars and trucks are conducted to verify the proposed method. The results indicate that the proposed method has a better performance than those methods in the literature, and shows a high accuracy and robust performance in vehicle weight identification under different conditions of inflation pressure, vehicle weight, motion state, and tire type.