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In Costa Rica, weigh stations for trucks and commercial vehicles were reinstated in 2008. Since then, a stabilizing trend in the percentage of heavy vehicles with excess loading was observed. For pavement design purposes, this resulted in reduced variability in truck equivalency factors. These were statistically validated by processing all the weight data collected at different stations located throughout the national road network between 2008 and 2011. Using linear regressions, it was verified that given a constant noncompliance percentage, the truck equivalency factor for C2, C3, and T3-S2 vehicles tended to stabilize at 0.20, 0.66, 1.19, respectively. These results were consistent with additional power regression performed on the data. Higher weight enforcement on the T3-S3 vehicles' tandem axle would result in a 0.17 decrease in the truck equivalency factor. The findings presented herein should aid countries that have yet to implement weigh stations, considering the benefits of exploring the evolution of truck factors if weigh stations were installed. This weigh station implementation case study exhibits the reality and development of pavement loading over time. Therefore, government authorities should be encouraged to control truck traffic with weigh stations to reduce pavement damage. [ABSTRACT FROM AUTHOR]

Fatigue damage prognosis for long-span steel bridges is of the utmost importance in bridge maintenance and management. In this study, a multi-scale fatigue damage prognosis algorithm is developed to calculate the trans-scale fatigue damage accumulation of newly-built long-span steel bridges under vehicle loading. The necessity and procedure of establishing a multi-scale finite element (FE) model of a newly-built long-span bridge for fatigue damage prognosis are first introduced. The future vehicle loading on the bridge is forecasted using the recorded weigh-in-motion (WIM) data and the agent-based traffic flow micro-simulation method. Then, the multi-scale fatigue damage prognosis algorithm is developed based on the multi-scale FE model and using the future vehicle loading. Finally, the proposed algorithm is applied to a newly-built long-span cable-stayed bridge for the time period from 2010 to 2020. The results show that the macro-scale fatigue damage accumulation and micro-scale short crack evolution of the critical components of the bridge can be simultaneously predicted and visualized. The proposed algorithm can be used as a numerical tool for fatigue damage prognosis of steel bridges where (or near where) WIM station is installed. [ABSTRACT FROM AUTHOR]

The article describes a method for diagnosing the accuracy of the vehicle scale without using standard weights. The novel method defines the possibility to estimate whether the scale would pass the test for error of indication in the next verification or not, only by using the results from simple tests with load of estimated weight and appropriate classifier. The method is primarily developed for users of these scales. Created classifier is based on the neural network algorithm. The neural network was trained with data from verifications, which are provided by Slovak Legal Metrology. Well trained classifier can provide not only information whether the scale will potentially pass the mentioned test or not, but reliability which is associated with this result as well. In this way, the user has valuable information about the scale in the period between the verifications. [ABSTRACT FROM AUTHOR]

Conventional bridge weigh-in-motion (BWIM) uses a bridge influence line to find the axle weights of passing vehicles that minimize the sum of squares of differences between theoretical and measured responses. An alternative approach, probabilistic bridge weigh-in-motion (pBWIM), is proposed here. The pBWIM approach uses a probabilistic influence line and seeks to find the most probable axle weights, given the measurements. The inferred axle weights are those with the greatest probability amongst all possible combinations of values. The measurement sensors used in pBWIM are similar to BWIM, containing free-of-axle detector sensors to calculate axle spacings and vehicle speed and weighing sensors to record deformations of the bridge. The pBWIM concept is tested here using a numerical model and a bridge in Slovenia. In a simulation, 200 randomly generated 2-axle trucks pass over a 6 m long simply supported beam. The bending moment at mid-span is used to find the axle weights. In the field tests, 77 pre-weighed trucks traveled over an integral slab bridge and the strain response in the soffit at mid-span was recorded. Results show that pBWIM has good potential to improve the accuracy of BWIM. [ABSTRACT FROM AUTHOR]

This paper deals with accuracy and long-term stability of bridge weigh-in-motion (B-WIM) systems. Research focused on four improvements, developed within two research projects financed by the European Commission. These improvements have increased accuracy of the results for four classes according to the European WIM specifications. The novel axle detection method recommends alternative locations to acquire strain responses under the moving vehicles, which provide reliable axle information without the need to install axle detectors in the carriageway. The new algorithm for calculating experimental influence lines combines the individual influence lines, generated from the responses of vehicles from the traffic flow, to obtain a robust solution that does not depend on the type of the vehicle. The third development adjusts the sensor factors to account for measurement errors on concrete structures, especially those resulted from hidden cracks. Finally, the effects of varying temperature and vehicle velocities on the WIM results were studied and their influences mitigated, to increase long-term stability of B-WIM results. All improvements were validated using long-term B-WIM measurements collected on four different bridges. [ABSTRACT FROM AUTHOR]

This article presents a new technical solution of fixing trailer hitch which serves as a connection between single track vehicle and cargo, mainly light trailer. They are manufactured from steel girder and nets which are constructed by point welding. They are designed to indicate the necessary solidity and the required load bearing capacity of the cargo. The application of roof racks is universal and these products are in great demand in the field of game management. There are a lot of trailer hitches which the manufacturers tailor to customers' demands. The stated technical solution is subject of published industrial utility model at the Industrial property office of the Slovak republic. [ABSTRACT FROM AUTHOR]

HL-93, the current bridge traffic load model used in the United States is examined here. Weigh-in-motion (WIM) data from 17 sites in 16 states containing 74 million truck records are used to assess the level of consistency in the characteristic load effects (LEs) implied by the HL-93 model. The LEs of positive and negative bending moments and shear force are considered on single- and two-lane same-direction slab and girder bridges with a range of spans. It is found that the ratio of WIM-implied LE to HL-93 LE varies considerably from one LE to another. An alternative model is proposed that achieves improvements in consistency in this ratio for the LEs examined, especially for the single-lane case. The proposed model consists of a uniformly distributed load whose intensity varies with bridge length. [ABSTRACT FROM AUTHOR]

This paper presents a novel weighing fusion method for a truck scale based on an optimal neural network with partial derivative constraints and a Lagrange multiplier (PD-LMNN). In this proposed method, firstly, the constraints for optimizing neural network (NN) are constructed via the truck scale’s prior knowledge that the partial derivative of the truck scale’s input–output function is positive. Secondly, the neural network’s performance index is created by using the augmented Lagrange function with a multiplier and a penalty factor. Thirdly, the detail algorithm of training the constrained-optimization NN is given. This proposed method can improve the NN’s generalization ability in case of the lacking training samples. The comparative experimental results show that the weighing errors of the truck scale with PD-LMNN are far less than those of DINN (DINN is a method for training a NN only by using the data samples, not the prior knowledge), and the PD-LMNN’s generalization ability is better than that of DINN when the training samples are lacking. [ABSTRACT FROM AUTHOR]

This paper presents a new approach of compensating truck scale's weighing errors based on prior knowledge and neural network ensembles (PKNNEs). Truck scale is a typical nonlinear system and it is fussy and labor intensive to compensate the weighing errors with the conventional method, leading to low accuracy of the weighing results. The general idea of this proposed approach consists of building individual neural networks (NNs) and designing the constraint conditions for optimizing neural network ensembles (NNEs) with the prior knowledge of the truck scale. First, three uncorrelated individual NNs are created by using the step-distribution characteristics of the truck scale's permissible maximum weighing error. Second, the constraint conditions for training the individual NNs are constructed by using the ideal weighing model and its derivatives, which can significantly improve the generalization ability of NNs, especially when the training samples are few or lacking. The detailed design procedure of this proposed method is given, the weighing principle of truck scale is discussed, and its weighing error models are found in this paper. Experimental results demonstrate the effectiveness of this method, and the testing results of a truck scale with PKNNEs in the field show that it meets the requirement for the weighing accuracy of medium-class scale defined by OIML R76 “nonautomatic weighing instruments.” [ABSTRACT FROM AUTHOR]

Abstract: The regulation of overweight trucks is of increasing importance. Quickly growing heavy vehicle volumes over-proportionally contribute to roadway damage. Raising maintenance costs and compromised road safety are also becoming a major concern to managing agencies. Minimizing pavement wear is done by regulating overloaded trucks on major highways at weigh stations. However, due to lengthy inspections and insufficient capacities, weigh stations tend to be inefficient. New practices, using Radio Frequency Identification (RFID) transponders and weigh-in-motion technologies, called preclearance programs, have been set up in a number of countries. The primary aim of this study is to investigate the current issues with regard to the implementation and operation of the preclearance program. The State of Queensland, Australia, is used as a case study. The investigation focuses on three aspects; the first emphasizes on identifying the need for improvement of the current regulation programs in Queensland. Second, the operators of existing preclearance programs are interviewed for their lessons-learned and the marketing strategies used for promoting their programs. The trucking companies in Queensland are interviewed for their experiences with the current weighing practices and attitudes toward the potential preclearance system. Finally, the estimated benefit of the preclearance program deployment in Queensland is analyzed. The penultimate part brings the former four parts together and provides the study findings and recommendations. The framework and study findings could be valuable inputs for other roadway agencies considering a similar preclearance program or looking to promote their existing ones. [Copyright &y& Elsevier]

This paper presents results based on the analysis of an extensive database of weigh-in-motion (WIM) data collected at five European highway sites in recent years. The data are used as the basis for a Monte Carlo simulation of bridge loading by two-lane traffic, both bidirectional and in the same direction. Long runs of the simulation model are used to calculate characteristic bridge load effects (bending moments and shear forces), and these characteristic values are compared with design values for bridges of different lengths as specified by the Eurocode for bridge traffic loading. Various indicators are tested as possible bases for a bridge aggressiveness index to characterize the traffic measured by the WIM data in terms of its influence on characteristic bridge load effects. WIM measurements can thus be used to determine the aggressiveness of traffic for bridges. The mean maximum weekly gross vehicle weight is proposed as the most effective of the indicators considered and is shown to be well correlated with a wide range of calculated characteristic load effects at each site. [ABSTRACT FROM AUTHOR]

The Department of Rural Roads, Thailand, is responsible for managing rural roads and their assets to ensure safe and pleasurable conditions for travelers. Annually, the department spends more than 10,000 million Baht for conducting road maintenances. It has been identified that one of the major causes of road damages is a result of the operations of overloaded trucks. This leads to the plan to establish the weigh stations to control and protect the conditions of rural roads across the country. In order to determine suitable locations for establishing weigh stations, this paper utilizes the analytic hierarchy process technique, with two sets of the main criteria under consideration, namely the engineering and economic factors, with their six associated attributes. The analysis results suggest the criterion weights of the engineering and economic factors, and their associated attributes, to be used for the calculation of the net weights of the rural roads. The roads with the highest net weights are considered feasible for permanent weigh stations establishment. [ABSTRACT FROM AUTHOR]

A new bridge weigh-in-motion (WIM) algorithm is developed which makes use of strain sensors at multiple longitudinal locations of a bridge to calculate axle weights. The optimisation procedure at the core of the proposed algorithm seeks to minimise the difference between static theory and measurement, a procedure common in the majority of bridge WIM algorithms. In contrast to the single unique value calculated for each axle weight in common Bridge WIM algorithms, the new algorithm provides a time history for each axle based on a set of equations formulated for each sensor at each scan. Studying the determinant of this system of equations, those portions of the time history of calculated axle weights for which the equations are poorly conditioned are removed from the final reckoning of results. The accuracy of the algorithm is related to the ability to remove dynamics and the use of a precise influence line. These issues are addressed through the use of a robust moving average filter and a calibration procedure based on using trucks from ambient traffic. The influence of additional longitudinal sensor locations on the determinant of the system of equations is discussed. Sensitivity analyses are carried out to analyse the effect of a misread axle spacing or velocity on the predictions, and as a result, the algorithm reveals an ability to identify potentially erroneous predictions. The improvement in accuracy of the calculated axle weights with respect to common approaches is shown, first using numerical simulations based on a vehicle-bridge interaction finite-element model, and second using experimental data from a beam-and-slab bridge in Slovenia. [ABSTRACT FROM AUTHOR]

Abstract: Weigh stations are the primary weight compliance checkpoints for commercial trucks. In the past decades, states have deployed weigh-in-motion (WIM) technology to reduce delay and increase weight violation enforcement. However, due to limitations on the accuracy and implementation of WIM technology the full potential of WIM has not been realized. To this end, this paper presents an adaptive algorithm that improves the efficiency of WIM-equipped weigh stations based on real-time weigh station queue length, truck demand, weight distribution, and static scale service time. Instead of using one fixed weight threshold value, our proposed floating-threshold control algorithm increases the threshold value based on the queue length at the weigh station to avoid station closure while still identifying the worst weight offenders: the threshold value is lowered when the queue is short to maximize the number of inspection. We develop the queueing models for both the fixed-threshold algorithm and the floating threshold algorithm and derive their mathematical formula to calculate the measures of effectiveness of a weigh system. A simulation model is developed to compare the performance of the proposed adaptive algorithm with a traditional fixed-threshold algorithm under various situations. The simulation results show that an adaptive algorithm yields higher violator capture percentage, lower station closure frequency, and less delay to non-violating trucks. [Copyright &y& Elsevier]

Abstract: Truck scale is an important weighing instrument. The truck parking cheating method is one of the truck scales cheating method and can lead to large economic losses to the enterprise. A new truck parking cheating detection method based on the voltage waveform analysis is brought out in this paper. According to the output voltage signal waveform of the weighing transducer, if the turning point number of the output voltage is different with the truck axles, the truck parking cheating method exists. Based on the principle, the truck parking cheating detection system is designed. The instrument is using 8031 as the MCU and can be transmitted the voltage signal to the control computer. Experimental data show that the detection system can on-time detects the truck parking cheating method. [Copyright &y& Elsevier]

Abstract: In this paper, a genetic algorithm (GA) is developed to solve a clustering problem for evaluating and ranking the weighing stations according to their performances. In hierarchical steps of clustering, observations with the least similarities should be merged and some of them will be lost. To improve this defect, the main concept behind the proposed algorithm is to avoid losing data in the hierarchical process of clustering, so all of the observations are randomly assigned into a predefined number of clusters by GA procedures. In this model, we consider the performance factors related to the weighing operation, such as the traffic volume of trucks, detected overloading, type of portable or fixed scales, and rate of acceding detections compared to the same duration in the previous year. The required data of 126 weighing stations are collected during two 6-month periods. Different dimensions of the collected data are standardized to uniform dimensions. The main performance of a clustering method considered as the fitness value in a genetic algorithm (GA) is to maximize the sum of deviation squares from the mean of within groups. It guaranties that the clusters have most similarities within groups and least similarities in among groups. Four different techniques of the mathematical clustering are compared with the result of the proposed GA by using the MATLAB software. The related results show that the clustering of weighing stations is more likely to other methods. [Copyright &y& Elsevier]

Electronic screening (e-screening) sorts and diverts commercial vehicles that have a high likelihood of being overweight into a weigh station using weigh-in-motion technology. E-screening is known to add significant efficiency in operating weigh stations by allowing eligible trucks to bypass the in-station inspection, hence reducing the congestion at the weigh station. The primary goal of this study was twofold: (a) to develop a simulation model for describing the e-screening operation at truck weigh stations and (b) to analyze and evaluate the weigh station operation with varying values of affecting factors including the transponder penetration rate and the weigh-in-motion weight threshold. This study focuses the e-screening operation at a small weigh station with relatively short queuing area and heavy truck volumes, which is inevitably vulnerable to truck overflows and is sensitive to the prevailing transponder penetration rate and the weigh-in-motion threshold. The simulation results reveal that an e-screening operation can substantially improve the overweight enforcement and can reduce the travel time of legal trucks passing the test weigh station. The simulation results also demonstrate that properly adjusted weigh-in-motion thresholds can effectively enhance the overweight enforcement by preventing overweight trucks from being granted a false green light as a result of the erroneous weigh-in-motion measurement error. The study results also indicate that with the transponder penetration rate equal to or less than 20%, the e-screening benefits are relatively insignificant and adjusting the weigh-in-motion threshold may further deteriorate the enforcement efficiency. [ABSTRACT FROM AUTHOR]

Abstract: The conventional compensation for eccentric error in truck scale is realized by repeatedly regulating the potentiometer in junction box to adjust gain of each channel with load cell, which is fussy and labor-intensive. In this paper, eccentric error sources are analyzed, and an error model is established. A method of adaptive compensation for eccentric error is proposed, and its model of compensation based on radial basis function neural network (RBFNN) is established, which considers the output signals of multiple load cells as its input variables. A learning algorithm of RBFNN is also presented. Experiments and verifications in field show that with adaptive compensation the eccentric error from some nonlinear factors of truck scale is greatly reduced, and it is less than the maximum permissible error of scales with medium accuracy defined by international standard OIML R76 “Nonautomatic Weighing Instruments”. [Copyright &y& Elsevier]

Weigh-in-Motion (WIM) systems can improve the capacity of weigh-station operations by screening trucks traveling at high speeds and requiring only trucks within a threshold of a maximum permissible weight or axle load to be weighed on more accurate static scales. The efficiency of a weigh station is highly dependent on the accuracy of the WIM screening system. This article examines the operations at the Stephens City weigh station in Virginia. The case study evaluates the accuracy of the WIM technology, in addition to the operations of the weigh station, in terms of service time (time that the truck is on static scale), queued delay, and system time. Specifically, the study demonstrated that the WIM systems did not conform to American Society for Testing and Materials (ASTM) standards for Type III WIM systems. The study also demonstrated that by incorporating a weight threshold of 96% only 16% of the trucks that were identified as possible violators actually violated the legal limits. Consequently, 84% of the trucks that were required to enter the static scale were forced to incur unnecessary delays and caused additional delays for violating and nonviolating trucks. [ABSTRACT FROM AUTHOR]