Overweight Vehicles Research Articles

A non‐contact identification method of overweight vehicles based on computer vision and deep learning

AbstractThe phenomenon of overweight vehicles severely threatens traffic safety and the service life of transportation infrastructure. Rapid and effective identification of overweight vehicles is of significant importance for maintaining the healthy operation of highways and bridges and ensuring the safety of people's lives and property. With the problems of high cost and low efficiency, the traditional vehicle weighing systems can only meet some of the requirements of different scenarios. The development of artificial intelligence technologies, especially deep learning, has greatly enhanced the accuracy and efficiency of computer vision. To this end, the paper proposes a method using computer vision and deep learning for the non‐contact identification of overweight vehicles. By constructing two deep learning models and combining them with the vehicle vibration model and relevant specifications, the weight and maximum allowable weight of the vehicle are obtained to make a comparison for determining overweight. Experimental verification was performed using a two‐axle vehicle as an illustrative example, and the results demonstrate that the proposed method exhibits excellent feasibility and effectiveness. It shows significant potential in real‐world scenarios, laying a research foundation for practical engineering applications. Additionally, it provides a reference for the governance and decision‐making of overweight issues for relevant authorities.

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

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.

Impact of Heavy Vehicle Axle Overload and Axle Configuration on Road Damage in Afghanistan

Aim: This study aimed to determine the percentage of heavy vehicles, overloaded vehicles, and heaviest vehicle that leads to deterioration of asphalt roads. Furthermore, the study aimed to assess the impact of ESALs and axle configuration on asphalt thickness and subgrade.
 Methods: This research used quantitative truck traffic data collected for three months in the Laghman WIM (Weigh in Motion) station located on the Kabul Torkham National Highway. Observed axle loads and GVW (Gross Vehicle Weight) data collected from April/ 10/2022, up to June/7/2022 average daily truck traffic of 73895 was estimated axle loads converted to the standard axle ESALs (Equivalent Single Axle Loads).
 Results: The percentage of heavy overweight vehicles is 13% while the heaviest vehicle is T2-Bedford truck vehicles at 20.17%. The T2 Bedford truck percentage was 42.17% in overall volume; this truck was overloaded 20.17%, compared to the general trend of Ministry of Public Works (MoPW), the T3 Hino truck contribution was 1.24% in total volume and 18.64% was overloaded, the ST112 semi-trailer contributed 3.02% in total volume, and 8.52% were overloaded. The ST113 5-axle and TT123 6-axle trailers percentile in entire volume was 9.6 % and 40.85% whereas, the overloading degree for these heavy vehicles was 2.29% and 6.72% respectively.
 Conclusion: Overloading percentage is 13% while, T2 Truck is the heaviest vehicle The variation of ESALs and axle configuration on asphalt thickness and subgrade modulus illustrates the higher thickness of asphalt decreases the damage to asphalt roads.
 Recommendations: Afghanistan Weigh-in-Motion stations need professional employees, internet facilities, electricity, and proper databases to record the data. By applying tight legislation and fines overloading will be minimized. Researchers may also research heavy vehicle tires' impact on road damage. Furthermore, it needs to determine the level of fatigue cracking and rutting failures by overloading.

Monitoring vehicles with permits and that are illegally overweight on bridges using Weigh-In-Motion (WIM) devices: A case study from Brescia

Bridges are amongst the most vulnerable elements of road networks. Since vehicles with permits and that are illegally overweight can pose a threat to bridge safety, implementation of monitoring systems for these vehicles has become mandatory. Weigh-In-Motion (WIM) systems are an efficient weight-enforcement solution because they collect data on vehicular mass and other parameters in real time. However, installation and maintenance costs frequently hinder a widespread operational use of WIM systems. Thus, while WIM devices are widespread in America and Asia, they have not yet been applied broadly in Europe. Additionally, the relationships among Gross Vehicle Mass (GVM) and other vehicular characteristics have only been investigated in a fragmentary manner. This real-world case study adopted a data set of 14,800+ overweight vehicles in heavily industrialised northern Italy based on two-months of raw data from WIM devices to: (i) investigate the probability density function on the main characteristics of overweight vehicles, and (ii) to provide Road Authorities (RAs) with a Multiple Linear Regression (MLR) model to predict overweight vehicles’ GVM in a more cost-effective way than placing WIM systems on each road segment with bridges. Probability density functions revealed the existence of different vehicle typologies, including lorries with permits and that are illegally overweight, whereas inferential analysis showed MLR’s high performance in predicting vehicles’ GVM. Minimum axle distance and total axle number were factors that had greater positive effects on the predicted GVM respectively. Conversely, by increasing vehicles’ width and length, a reduction in GVM was predicted. These findings could help support practitioners, RAs, and governments to implement rational and less resource consuming administration policies for their bridge assets.

Evaluating the impact of overweight trucks on rigid pavement performance using AASHTOWare pavement ME design

ABSTRACT The purpose of this study is to evaluate the impact of overweight vehicles on pavement performance over its design life, with Jointed Plain Concrete Pavements (JPCPs) particularly considered for analysis. The Long-Term Pavement Performance database was used to provide information on pavement construction, age, overall structure, specific traffic inputs, and recorded historical pavement performance. AASHTOWare Pavement ME Design (PMED) was used to analyze data extracted from LTPP based on legislation by the Federal Highway Administration (FHWA) regulating gross vehicle weight (GVW) and single and tandem axle weights of overweight trucks (OWTs) to estimate pavement performance and service life. The overall findings indicated that although increasing overweight by 20% on single or tandem axles could considerably reduce pavement service life by up to 20% in the various scenarios examined in this study, OWT exceeding the GVW limit legally-allowed by FHWA could damage pavement more than OWT exceeding axle weight limits.

Age-dependent failure probabilities of corroding concrete sewer pipes under traffic loads

Concrete pipes are frequently used in the wastewater infrastructure. These buried structures are prone to ageing and deterioration, as well as damage under excessive stresses from traffic. This study presents the first set of temporal fragility models for underground concrete sewer pipes under the compounding effects of corrosion and truck loads. To address the high computational costs of fragility modeling, Bayesian Additive Regression Trees (BART) – a machine-learning based meta-model – are trained using a high-fidelity computational model of buried concrete pipes. The BART models are subsequently applied to develop age-dependent fragility models for serviceability and collapse of pipes conditional on truck loads. Considered uncertainties include statistically significant concrete and soil properties, truck load, and environmental factors that affect the corrosion of concrete sewer pipes. Results indicate that the direction of traffic stream, the degree of loss of wall thickness due to corrosion, and the maximum allowed truck load are critical factors that must be considered when planning inspection, rehabilitation, and retrofit of this underground infrastructure. According to the results, concrete sewer pipes buried in perpendicular to the direction of traffic flow are more vulnerable than those that are parallel to the direction of traffic flow. The results highlight that the probability of collapse is insignificant when it comes to vehicles weighing less than the design truck weight; however, the probability of collapse significantly increases for the moderate and severe corroded sewer pipes when it comes to the overweight vehicles. The age-dependent fragility models indicate that for sewer pipes buried perpendicular to the direction of traffic stream with service life of less than 25 years, the probability of the first major structural defect is less than 5%. This is also true for sewer pipes that have been in service for less than 45 years if the traffic stream is parallel to the buried pipe. The developed fragility models also constitute a key component of quantitative risk assessment of underground wastewater collection systems.

Load Estimation of Moving Passenger Cars Using Inductive-Loop Technology.

Due to their lack of driving controllability, overweight vehicles are a big threat to road safety. The proposed method for a moving passenger car load estimation is capable of detecting an overweight vehicle, and thus it finds its application in road safety improvement. The weight of a car's load entering or leaving a considered zone, e.g., industrial facility, a state, etc., is also of concern in many applications, e.g., surveillance. Dedicated vehicle weight-in-motion measurement systems generally use expensive load sensors that also require deep intervention in the road while being installed and also are calibrated only for heavy trucks. In this paper, a vehicle magnetic profile (VMP) is used for defining a load parameter proportional to the passenger vehicle load. The usefulness of the proposed load parameter is experimentally demonstrated in field tests. The sensitivity of the VMP to the load change results from the fact that the higher load decreases the vehicle clearance value which in turn increases the VMP. It is also shown that a slim inductive-loop sensors allows the building of a load estimation system, with a maximum error around 30 kg, which allows approximate determination of the number of passengers in the car. The presented proof of concept extends the functionality of inductive loops, already installed in the road, for acquiring other traffic parameters, e.g., moving vehicle axle-to-axle distance measurement, to road safety and surveillance related applications.

Utilizing Kriging Metamodeling to Provide Practical and Effective Bridge Weigh-in-Motion

Emerging technologies are a strategic ally in the efficient management and preservation of pavements and bridges. Toward this end, different methodologies, such as weigh-in-motion (WIM), have been developed for the detection of overweight vehicles and traffic monitoring. Bridge weigh-in-motion (BWIM) systems can be installed and serviced without interrupting traffic flow. This paper presents a new approach for processing traditional strain response data. This proposal extends the BWIM concept of influence area from response time-histories. The dimensionality of the strain response waves is reduced by the calculation of the centroid and the area under the curve. Subsequently, these two dimensions are used as inputs to an ordinary Kriging (OK) metamodel to predict the gross vehicle weight (GVW) of the passing traffic. The OK methodology allows for the strategic selection of vehicles to train the BWIM metamodel. An example of the application of Kriging metamodeling (KM) to BWIM through the instrumentation of an in-service highway bridge located in Costa Rica is presented. Experimental horizontal strain data along with corresponding weight measurements from a static permanent weigh station were available for 90 trucks to validate the proposed enhanced BWIM methodology.

The effect of overweight vehicles on road pavements and safety

The Overweight vehicles impact on road infrastructure and safety was a project funded by PIARC (World Road Association). This report compiled the available information on overweight road freight vehicles around the world, the impacts they have on road infrastructure, road safety and the economic position of road infrastructure managers and collected global best practices to prevent and mitigate overloading.This paper focuses on the impact of overweight vehicles on road pavements and on road safety. Several relevant factors, either responsible for pavements distress or for road safety reduction, were analyzed. The relevance of this information is suitable for road administrations, freight, and enforcement practitioners around the world to help them design appropriate interventions.

FEM analysis of the influence of reinforcing mesh on concrete pavement performance

Reinforcement of concrete pavement slabs with steel reinforcing mesh (KARI mesh) has been regularly used in the Czech Republic. Reinforcing mesh is used for atypical shapes and non-standard (larger) dimensions of pavement slabs (intersections, runways, transhipment areas, etc.). The placement of mesh across the thickness of the slab varies in designs (top, bottom or both surfaces, eventually in centre). The mesh has a positive effect on cracking occurrence during concrete hardening. It is assumed that the reinforcing meshes also contribute to the reduction of tensile stresses caused by cyclic loading from traffic and temperature. The amount of the reduction in concrete depends on the mesh positioning, but also on the specific loading conditions. In this paper, the FEM analysis of concrete pavements with steel reinforcing mesh is carried out. The reduction of maximal value of tensile stress induced by overweight vehicles, temperature and their combination is inspected while using different mesh positioning. The slab dimensions used in the simulation are larger than the usual highway slabs, the dimensions are based on the real transhipment area pavement. The contribution of the reinforcement to limitation of the maximum tensile stress in the pavement due to different reinforcing mesh positioning was determined.

Pothole Detection System

One of the primary issues faced by emerging countries is the maintenance of road condition. Traffic infrastructure for the society is highly significant because majority of road accidents takes place owing to bad condition of road like potholes. Potholes are caused due to poor quality and improperly maintained roadways. The constant movement of the overweight vehicles like trucks is also responsible for these ill roads. These ill quality roads will cause severe damage to the vehicles in terms of tire and most important thing is the accidents which are caused due to this. To track the state of the roads and conduct analyses for upcoming work, an ideal system should be created. We suggest a new technique to stop these dangers by leveraging an advanced sensor system. The sensors will be fitted to vehicles and from vehicles the data’s collected from sensors and the location gained by the GPS are communicated to road transport authority through IOT where officials take necessary actions. Using the data’s obtained more damaged area can be prioritized and damage control can be reduced. Keywords: IOT, Sensors, Prioritization, Analysis, Road safety

Weigh-in-Motion Sensors and Traffic Monitoring Systems. State of the Art and Perspectives

Abstract Weigh-in-motion (WIM) sensors allow the control of vehicle weights without disruption of traffic. By monitoring traffic and by reducing the number of overweight vehicles, the WIM sensors bring very important savings. This paper discusses the present status and developmental trends of weigh-in-motion (WIM) technologies. Both commercial and new types of WIM sensors are presented. Strengths and weaknesses of different type of WIM sensors are discussed. It is also presented the tendency to equip the WIM systems with different types of sensors, in order to evaluate other effects: reducing the fuel consumption, emission of pollutants, noise and vibrations, etc. Possible trends for the further development of WIM sensors are anticipated.

Dynamic Property Analysis of Orthotropic Bridge Deck with Local Fatigue Crack

With the increase in traffic volume and overweight vehicles, fatigue problems are highlighted. Especially for the orthotropic steel deck, the premature cracks seriously affect the service performance, operation, and service quality of the bridge. In this paper, the steel box‐girder segment model and deck substructure model considering several typical fatigue cracks were established to reveal the variation law of fatigue cracks on vibration frequency and deflection under vehicle traveling load. A natural frequency analysis was performed to evaluate the change in the vibration characteristics due to localized damage, together with a dynamic analysis that considered a vehicle traveling on the bridge. The results show that the initiation and propagation of several typical cracks have little influence on the lower modes of the overall structure and great influence on the high‐order modes of the substructure. The dynamic deflection response of the bridge changed under vehicle load as damage progressed. Therefore, it was possible to identify cracks of the orthotropic steel bridge deck and to provide guidance for fatigue crack detection and repair.

Preserving Infrastructure with WIM Technology

The latest weigh-in-motion solutions are being used to collect data for applications such as calculating tolls and the removal of overweight vehicles from roads

Analysis of overweight vehicles on asphalt pavement performance using accelerated failure time models

ABSTRACT Vehicle overweighting has been one of the key driving forces of deteriorated pavements. The overweighting characteristics that dominate the pavement performance deterioration have been inadequately investigated. This study filled such a gap by analyzing the survival time of pavement under different overweighting scenarios. The survival model was based on the accelerated failure time (AFT) formulation. For improved predictivity, an implementation of the AFT using the gradient boosting tree method was employed. All data concerned were collected from the Long-Term Pavement Performance (LTPP) program. Fatigue cracking and rutting were selected as the pavement performance indicators. Each indicator had three levels of failure thresholds to investigate the impact of overweighting on short-term, mid-term, and long-term pavement performance. The predictive performance of AFT models showed that long-term pavement performance was more dependent on overweighting than short-term pavement performance. Compared with the volume and weight of overweight vehicles, the overweighting percentage described the overweighting situation the best. Fatigue cracking was more sensitive to the overweighting percentage than rutting. Without overweighting, the average pavement fatigue life and rutting life would be extended by about 43% and 29%, respectively.

Simplified Comparison of Oversize and Overweight Vehicles Permit Fee Structure in the U.S. Western States

This paper provides a simplified comparative assessment of oversize/overweight (OS/OW) vehicle permits and fees in the U.S. western states and includes a review of current permitting practices, fee structures, fines, and available information on revenue generation. The study was motivated by an urgent need to revise permit structures in the State of New Mexico because of escalating demand for OS/OW vehicle permits. The research team surveyed the Departments of Transportation, Motor Vehicle Divisions, and Offices of Public Safety in 14 states: Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, North Dakota, Oklahoma, Oregon, Texas, Utah, Washington, and Wyoming. In addition, the state regulations related to OS/OW vehicles were reviewed. Comparison of the OS/OW permit structures revealed significant differences in the fees and fines charged in the western states. It is recommended that the current permit structure should be overhauled to accommodate the demand for higher maximum permitted weights and to generate the funds necessary to maintain and rebuild the affected transportation infrastructure including pavements and bridges. A scientific study is needed in each state to quantify the costs associated with the operation of OS/OW vehicles and to develop a revenue-neutral fee structure. In particular, the determination of permit fees requires a comprehensive study to evaluate the damage to bridges and pavements caused by OS/OW vehicles. Findings from this research provide a contextual framework to compare current permitting structures and their implications on the revenues generated from OS/OW permits across the U.S. western states.

Strengthening Hollow Core Concrete Bridges with Deficient Transverse Hinge Joints with a Steel and Concrete Composite Anchorage System

Hollow core concrete bridges have been widely constructed in China during the last two decades. The most simple span bridges, with standard lengths of 13 m, 16 m and 20 m, are hollow core concrete bridges. For this type of bridge, the hollow core slabs are precast and simply lifted into place. After the prefabricated hollow core slabs are put in place, the embedded rebars extending from the prefabricated slabs are bound together and the concrete is poured into the space between the slabs, forming a lateral hinge joints between the slabs. A lot of hollow core concrete bridges built early in the 1990s have small hinge joints and very few rebars embedded to form strong lateral connections between the slabs. With an increase of overweight vehicles and the continuous aging of the structures, structural deficiencies such as intensive cracks running through the mid-span and severe deflection progress rapidly resulting in loss of structural capacity and even collapse. The failure of hollow core concrete bridges usually initiates from the failure of the hinge joints, which are the weakest links of the system. When the hinge joints start to lose their ability to hold the adjacent slabs securely, more and more vehicle loads are shifted onto the slabs with deficient hinge joints, which worsens the condition of the slabs and eventually results in systematic failure. To save the hollow core concrete bridges from failure, the authors propose an effective strengthening method to stop the progress of the deficiencies and improve the capacity of the structure.

Rare-Class Extraction Using Cascaded Pretrained Networks Applied to Crane Classification

Overweight vehicles are a common source of pavement and bridge damage. Especially mobile crane vehicles are often beyond legal per-axle weight limits, carrying their lifting blocks and ballast on the vehicle instead of on a separate trailer. To prevent road deterioration, the detection of overweight cranes is desirable for law enforcement. As the source of crane weight is visible, we propose a camera-based detection system based on convolutional neural networks. We iteratively label our dataset to vastly reduce labeling and extensively investigate the impact of image resolution, network depth and dataset size to choose optimal parameters during iterative labeling. We show that iterative labeling with intelligently chosen image resolutions and network depths can vastly improve (up to 70×) the speed at which data can be labeled, to train classification systems for practical surveillance applications. The experiments provide an estimate of the optimal amount of data required to train an effective classification system, which is valuable for classification problems in general. The proposed system achieves an AUC score of 0.985 for distinguishing cranes from other vehicles and an AUC of 0.92 and 0.77 on lifting block and ballast classification, respectively. The proposed classification system enables effective road monitoring for semi-automatic law enforcement and is attractive for rare-class extraction in general surveillance classification problems.

Development of an overweight vehicle permit fee structure for Illinois

Permits are one of the most effective and common tools for state agencies to regulate the operation of overweight and oversize trucks to ensure the safety of passenger and freight traffic and to minimize damage to pavements and bridges. Although the State of Illinois uses a relatively comprehensive permit system, many of its parts have not been revised for more than 30 years. Therefore, the objective of this study was to evaluate up-to-date impacts of overweight (OW) trucks and develop an equitable permit system. In this study, impacts of OW trucks on bridges, pavements, and traffic safety were evaluated; and individual fees were developed for each. The most recent databases on infrastructure condition and state-of-the-art prediction algorithms were employed to produce realistic and up-to-date assessment of OW trucks’ impact. Finally, two approaches were recommended to combine individual fees. The first approach requires developed frameworks for calculating individual fees to be integrated with existing geographic information system-based online permit tools that are currently used by many departments of transportations (DOTs). These tools compute the fee for each vehicle by reporting a route based on user-input origin/destination. The information specific to each OW vehicle (e.g., mile, axle spacing, weight, bridge inventory rating) can be extracted from the reported routes and injected into the developed frameworks. Thereby, the fee can be computed in an equitable and more accurate way. The second approach is converting the frameworks into a formula to conform to the conventional permit fee calculation schemes (e.g., table format).

Evaluating Impacts of Overweight in Road Freight Transportation: A Case Study in Brazil with System Dynamics

Overweight vehicles in ornamental stone transportation reduce the lifespan of the pavement and increase accidents on Brazilian highways. This paper evaluates the relationship between different policies for the loading of ornamental stone vehicles and its externalities, such as the impact on costs with transportation, pavement maintenance and road accidents, using the System Dynamics (SD) method. The results confirm the advantages of reducing operational costs with the practice of overweight. However, as the overweight increases, the pavement maintenance and road accidents costs also increase. Therefore, the best vehicle loading policy depends on the relative importance of the economic and social costs involved.