Non-Contact vehicle Weigh-in-Motion using computer vision

Feng, Maria Q.; Leung, Ryan Y.; Eckersley, Casey M.

doi:10.1016/j.measurement.2019.107415

Cited by 38 publications

(9 citation statements)

References 20 publications

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“…In the available studies devoted to the elements of a weight control system, such as automatic weight control stations, attention is focused on the analysis of HGV weighing equipment and procedures. In the literature, mobile weighing stations are mainly considered to be tools for collecting data on traffic flow parameters, including weight parameters for calculations in the design and operation of bridges and roadbeds [6,7,9,12]. The objectives of the above studies are to calculate the carrying capacity of bridge crossings and roadbeds on the basis of the data on the weight parameters of traffic flow obtained by mobile weighing stations as well as analyze the relevance of the problem of overloaded vehicles and damage to road infrastructure in various regions.…”

Section: Discussionmentioning

confidence: 99%

“…These studies also provide new ways of measuring the weight parameters of heavy vehicles [10,11]. The objectives of the above studies are to calculate the carrying capacity of bridge crossings and roadbeds on the basis of the data on the weight parameters of traffic flow obtained by weight-in-motion stations, as well as analyze the relevance of the problem of overloaded vehicles and damage to road infrastructure in different regions of the world [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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The Design and Evaluation of a Telematic Automated System of Weight Control for Heavy Vehicles

Belikova

Safiullin

2022

Infrastructures

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In this article, the authors reviewed the existing system of weight control of heavy vehicles in the Russian Federation. In this research, the main shortcomings of the system, which prevent its effective functioning in relation to the use of road infrastructure, were determined. To solve these problems, we developed a model of the functionality of a telematic automated system of weight control of heavy vehicles, as well as defining the optimization tasks of the transportation process. Mathematical modeling of the operational factors that influence the system of weight control of heavy vehicles on roads was carried out. As a result of the research, the most significant parameters that have the greatest impact on the efficiency of the road were determined. By means of these parameters, it is feasible to choose suitable hardware and equipment for a weight control system. The methodology of developing automatic points for the weight control of heavy loads during road transportation was formulated. As a result of the study, it was concluded that the introduction of a telematic automated system of weight control of heavy vehicles would increase the efficiency of road transport on the highway by positively affecting its basic transport and performance indicators.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Design and Evaluation of a Telematic Automated System of Weight Control for Heavy Vehicles

Belikova

Safiullin

2022

Infrastructures

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“…Obviously, this method was not comprehensive, as vehicle weight information was not included. In order to obtain data on loading, Kong and Feng proposed a noncontact weighing method that involved capturing vehicle tire images [26,27]. Zhu reconstructed a 3D bounding box for each vehicle using YOLOv5 and simulated the traffic data with historical records [28].…”

Section: Introductionmentioning

confidence: 99%

Computer Vision-Based Real-Time Identification of Vehicle Loads for Structural Health Monitoring of Bridges

Yang,

Bao,

Sun

et al. 2024

Sustainability

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Coupling effects of various loading conditions can cause deflections, settlements and even failure of in-service bridges. Although it is one of the most critical loads, unfortunately, loading conditions of moving vehicles are difficult to capture in real time by bridge monitoring systems currently in place for sustainable operation. To fully understand the status of a bridge, it is essential to obtain instantaneous vehicle load distributions in a dynamic traffic environment. Although there are some methods that can identify overweight vehicles, the captured vehicle-related information is scattered and incomplete and thus cannot support effective bridge structural health monitoring (BSHM). This study proposes a noncontact, vision-based approach to identification of vehicle loads for real-time monitoring of bridge structural health. The proposed method consists of four major steps: (1) establish a dual-object detection model for vehicles using YOLOv7, (2) develop a hybrid coordinate transformation model on a bridge desk, (3) develop a multiobject tracking model for real-time trajectory monitoring of moving vehicles, and (4) establish a decision-level fusion model for fusing data on vehicle loads and positions. The proposed method effectively visualizes the 3D spatiotemporal vehicular-load distribution with low delay at a speed of over 30FPS. The results show that the hybrid coordinate transformation ensures that the vehicle position error is within 1 m, a 5-fold reduction compared with the traditional method. Wheelbase is calculated through dual-object detection and transformation and is as the primary reference for vehicle position correction. The trajectory and real-time speed of vehicles are preserved, and the smoothed speed error is under 5.7%, compared with the speed measured by sensors. The authors envision that the proposed method could constitute a new approach for conducting real-time SHM of in-service bridges.

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“…Multi-vision sensor measurement technology has been widely used for some special occasions or large-scale measurement scenes; for example, in industrial fields such as the aerospace industry, intelligent manufacturing and automotive production. Among them, corresponding vision inspection methods have been explored in the field of special-purpose vehicle manufacturing [1]. However, most methods are limited to the measurement of regular-sized cars.…”

Section: Introductionmentioning

confidence: 99%

Research on global calibration method of large-scene multi-vision sensors in wheel alignment

Song¹,

Wang²,

Chen³

et al. 2022

Meas. Sci. Technol.

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Wheel measurement and positioning technology is an important technology in vehicle production, and is of great importance for the safety of vehicles. At present, visual measurement and other methods are widely used in automotive production and inspection, but these methods are limited to the measurement of regular-sized vehicles. There is no effective solution to the problem of wheel alignment for large special-purpose vehicles with multiple tires. In order to solve the wheel positioning problem of large-size special-purpose vehicles, this paper designs a vision measurement system for wheel parameters in large scenes by combining vision sensors with linear motion guides to extend the vision measurement range and complete the global calibration of multiple-vision sensors with the help of laser trackers and self-researched stereo targets. This paper proposes an Elementary–Advance global calibration algorithm to improve the accuracy of coordinate system conversion during global calibration. This paper establishes a correction model for the measurement errors that exist in the initial global calibration process, and iterates the objective function to optimize the coordinate system conversion parameters between multiple vision sensors to improve the measurement accuracy of the system. The experimental results show that the goodness of fit and the accuracy of fit for the feature cylinder are 98.31% and 99.03% based on the global calibration method of this paper. The standard deviation of measurements for the standard ruler of the Inva alloy is less than 0.391 mm in the large dimensional range of 6050 mm × 3500 mm × 800 mm. Finally, by comparing the measurement results with the TrukCam four-wheel alignment instrument, the feasibility of the visual measurement system designed in this paper for large scenarios of wheel parameters is verified, and the measurement accuracy requirements for four-wheel alignment of special-purpose vehicles are met.

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Non-Contact vehicle Weigh-in-Motion using computer vision

Cited by 38 publications

References 20 publications

The Design and Evaluation of a Telematic Automated System of Weight Control for Heavy Vehicles

The Design and Evaluation of a Telematic Automated System of Weight Control for Heavy Vehicles

Computer Vision-Based Real-Time Identification of Vehicle Loads for Structural Health Monitoring of Bridges

Research on global calibration method of large-scene multi-vision sensors in wheel alignment

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