Improving Highway Performance Monitoring Using Advanced Detector Technologies

Research Lead: Stephen Ritchie

UC Campus(es): UC Irvine

Problem Statement: Caltrans along with other state Departments of Transportation (DOTs) are required to submit axle-based classification count reports to the Federal Highway Administration (FHWA) under the Highway Performance Measurement System (HPMS) program. The data are an input to the federal government’s allocation of funds to the states to effectively maintain pavement quality in high priority corridors. However, safety concerns and high costs are associated with existing methods of data collection. For example, setting up road tubes and other temporary data collection devices frequently exposes DOT personnel to safety hazards from their proximity to the highway lanes. In addition, permanent detection systems such as existing piezo-based vehicle classifiers are expensive to install and have high maintenance costs due to their frequent failures.

Project Description: The statewide Truck Activity Monitoring System (TAMS) developed by UC Irvine currently provides continuous truck counts by vocation at 70 major truck corridors in California, and will be expanded to over 90 locations. Although the current classification models in TAMS are focused on truck vocations, initial investigations have shown that there is excellent potential to successfully develop truck classification models that are capable of classifying vehicles according to the axle-based FHWA HPMS scheme using only inductive loop signature data. For this project, researchers will partner with advisors from the Caltrans Traffic Census Program (TCP) to develop HPMS-based classification models and design a streamlined solution within TAMS to process the data for HPMS reporting requirements. Existing data as well new data sources collected at weigh-in-motion (WIM) sites will be used to develop and validate the models, while TCP advisors will provide reporting guidelines to ensure that the developed system meets stakeholder needs. We will also investigate establishing a test detection site using only solar power to study the feasibility of implementing this solution at off-grid sites to further extend the applications of this research.

Status: Completed

Budget: $34,290