The capability of measuring vehicle lengths makes dual-loop detectors a potential real-time truck data source for freight movement studies. However, a previous study found that the dual-loop detection system of the Washington State Department of Transportation (WSDOT) was not consistently reporting accurate truck volumes because of its sensitivity setting problems. Specifically, the sensitivity problems found were: (1) sensitivity discrepancies between the two single loops that form a dual-loop detector; and (2) unsuitable sensitivity level settings for both single loops even when discrepancies weren’t significant. Both problems can result in erroneous vehicle length estimates and, consequently, inaccurate truck counts.
As an extension of the previous study, this research project developed an algorithm for the identification and correction of such loop sensitivity problems. The algorithm identifies dual-loop sensitivity problems using individual vehicle information extracted from high-resolution loop event data and corrects dual-loop sensitivities through a two-step procedure: 1) remove the sensitivity discrepancy between the two single loops and 2) adjust their sensitivities to the appropriate level. The algorithm was also implemented in a computer application named the Advanced Loop Event Data Analyzer (ALEDA) system for convenient usage.
Elimination of dual-loop sensitivity problems enhances the reliability of the dual-loop detection system and improves the quality of truck volume data. The findings and products from this study will help WSDOT obtain more accurate speed and truck volume data from the existing dual-loop detectors.