In many countries, work is being conducted to introduce Weigh-In-Motion (WIM) systems intended for continuous and automatic control of gross vehicle weight. Such systems are also called WIM systems for direct enforcement (e-WIM). The achievement of introducing e-WIM systems is conditional on ensuring constant, known, and high-accuracy dynamic weighing of vehicles. WIM systems weigh moving vehicles, and on this basis, they estimate static parameters, i.e., static axle load and gross vehicle weight. The design and principle of operation of WIM systems result in their high sensitivity to many disturbing factors, including climatic factors. As a result, weighing accuracy fluctuates during system operation, even in the short term. The article presents practical aspects related to the identification of factors disturbing measurement in WIM systems as well as methods of controlling, improving and stabilizing the accuracy of weighing results. Achieving constant high accuracy in weighing vehicles in WIM systems is a prerequisite for their use in the direct enforcement mode. The research results presented in this paper are a step towards this goal.

The paper provides analysis of the influence of temperature on the error of weigh-in-motion (WIM) systems utilizing piezoelectric polymer load sensors. Results of tests of these sensors in a climatic chamber, as well as results of long-term tests at the WIM site, are presented. Different methods for correction of the influence of changes in temperature were assessed for their effectiveness and compared.

The use of Weigh-in-Motion (WIM) systems for vehicle's direct enforcement depends, first of all, on their high and constant accuracy under variable measurement conditions. This work concerns improving accuracy of weighing results obtained in WIM systems. The method commonly employed for achieving this goal is to increase the number of axle load sensors at the weighing site. The objective of this study is to compare the accuracy of Weigh-in-Motion systems equipped with different numbers of axle load sensors. The paper presents the results of in situ tests and simulations. Experiments were carried out on 16-sensors system and were supplemented by results obtained by simulations using multibody dynamic software. For accuracy assessment of weighing systems, two criteria were used: the 95%-percent relative error and the reliability characteristic. Quantitative relationship between the number of axle load sensors and weighing accuracy was estimated. Optimal number of sensors was evaluated for multi-sensor systems which is a step forward in implementation of WIM systems for direct enforcement of overloading.

In every country, road networks are one of the largest and highly expensive investment. Equally expensive are the consequences of not ensuring adequate road safety. This creates the need for an efficient and automatic system for the detection of overloaded vehicles [17]. One of the tools designed to measure the weight and individual axle loads of vehicles are the systems weighing vehicles in motion (WIM). Due to their measurement imprecision, WIM systems composed of two lines of sensors are only used as pre-selection systems. At present, the only viable option for reducing measurement uncertainty in dynamic weighing is to increase number of load sensors (Multi-Sensor systems; MS-WIM). The paper presents the results of research on a MS-WIM system equipped with 16 lines of load sensors. The conceptual objectives, system design, results of experimental evaluation of the system's accuracy, and the final conclusions based on a 6-year operating period, during which the system has been used under normal traffic conditions have been presented.