This project developed and tested a low-cost novel sensing system to detect and classify wide-base tire (WBT) types and their distributions. It will also demonstrate the system's usefulness in data collection for pavement analysis and design applications. The first phase of the project involved developing and testing prototypes of a novel low-cost sensing system that detects tire widths, wheel wander, and truck/axle configurations at highway speeds using piezoelectric sensors. These sensors generate a voltage proportional to the applied force when a wheel applies pressure. Considering practical field installations, a rubber-based sensor casing was designed. A prototype sensor assembly was prepared using the ethylene propylene diene monomer (EPDM) rubber strips, incorporating piezoelectric sensors between two rubber strips for evaluating their response to varying tire widths and wander. Field tests with vehicles validated the EPDM sensor strip embedded with piezoelectric sensors. Sensor responses were collected for an SUV and a sedan from the EPDM rubber strip housing 16 piezoelectric sensors to compare model results with the experimental data in the field. The analytical model used these field tests' strain and voltage data and successfully identified the vehicle passage, classification, and tire widths. Based on the findings from field tests, a 24-foot-long EPDM rubber strip was prepared with 32 piezoelectric sensors embedded between two rubber strips. This strip was placed across Wilson Road on the Michigan State University (MSU) campus to gather traffic data using the electronic system. The developed model analyzed field traffic data to validate the time response signals and classify vehicles. Also, the sensor system collected data for axle passage time, tire width, and wheel wander over 36 hours, including 139 vehicles. The data analysis and validation results showed consistent measurements with a 1.6% error in vehicle classification. Subsequently, the team developed a 40-foot-long sensor strip that housed 48 piezoelectric sensors positioned along the expected wheel path in the outer lane. The sensor was placed adjacent to a WIM site on US127 in Mason, MI, and in St. Johns, MI, to collect vehicle passage data for vehicle classification (i.e., based on axle count, wheelbase, and wheelbase ranges), along with tire width and wheel wander. The sensor was deployed for 5 and 3 days at Mason and St. Johns locations. The sensor collected over 20,000 vehicles at Mason and identified 19% as WBTs for Class 9 trucks. Over 12,000 vehicle data was collected at the St. Johns location, with about 16% WBTs for Class 9 trucks. Compared to WIM data, the classification exhibited an error rate of less than 2%. Additionally, the team analyzed vehicle loads by matching the timing of vehicle passage over the sensor with WIM data. This provided detailed load spectra for tandem axles with WBT and dual tires.
There are several perceived benefits of the developed system to transportation stakeholders. By collecting data that directly informs pavement design, the system extends infrastructure lifespan and lowers maintenance costs. Its low-cost, scalable design makes it accessible for agencies aiming to enhance road monitoring without the high expense of traditional weigh-in-motion systems, offering a practical, budget-friendly alternative. Moreover, this system supports broader transportation safety and sustainability goals by helping enforce tire width regulations and promoting road safety through accurate tire and vehicle classifications. This product represents a forward-thinking tool for state and national agencies looking to modernize their monitoring practices, enabling cost-effective and reliable road infrastructure management.

The Final Report is available.