Weigh-in-motion (WIM) systems are used to automatically determine the weights of trucks passing over transducers without requiring those vehicles to stop. Although these devices have been in existence for more than 40 years and are now being deployed on a significant scale, unresolved problems associated with their installation, maintenance, and use prevent them from attaining high levels of accuracy. These problems are directly related to the fact that WIM systems are used to estimate static weights on the basis of the dynamic forces produced by axles that are oscillating continuously and in a complex manner. Existing approaches to WIM rely on empirical methods to interpret dynamic measurements to provide equivalent static information. The algorithms used in these methods are generally more than 10 years old. Although they usually incorporate the best technology available at the time of their development, they do not explicitly address the vehicles, WIM transducers, pavement profile, and pavement structure as a single complex dynamic system. Recent advances in both hardware (sensors and computers) and software technology now allow the dynamic phenomenon of truck axle weight fluctuations in the context of the vehicle-transducer-pavement system to be identified, quantified, characterised, and explicitly included in the interpretation of WIM sensor output signals. The general problem of weighing trucks in motion and its proposed solution using advanced sensor technology, signal processing algorithms, and analytical techniques, including the application of artificial intelligence, are addressed. The current status of the research to accomplish these objectives is also presented.
Abstract