Weigh-in-motion systems (WIM) serve as valuable sources of traffic load data. The determination of axle load spectra using WIM data is pivotal for calculating load equivalency factors and predicting pavement distresses through M-EPDG. Among various factors affecting WIM accuracy, temperature changes stand out as particularly influential. This paper examines the influence of temperature on WIM-collected data, utilizing the steering axle load spectrum. Data was gathered from 77 WIM stations situated on Poland's national roads and motorways. Observations reveal that temperature fluctuations introduce biases into the axle load spectrum, significantly impacting several key statistics, including Truck Factors (TF) and number of Equivalent Standard Axle Loads (ESAL) or the percentage of overloaded vehicles. Notably, a shift in air temperature from -10°C to +30°C leads to axle load spectrum biases ranging from 5% to 35%. The technology of axle load sensors plays a crucial role in this phenomenon. The analysis indicates that the uncertainty of truck factors and the subsequent calculation of ESAL’s using the fourth power equation can increase by up to 1.5 times when the axle load spectrum bias reaches 20%.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-031-67252-1_79
- Category
- Publikacja monograficzna
- Type
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language
- angielski
- Publication year
- 2024
