Application of vehicle-based sensors assessing highway pavement conditions subject to extreme temperature variation

The technique of using vibration sensors to monitor pavement roughness has been expanding in pavement engineering. The primary objective of this study is to implement cost-effective vibration sensors to predict asphalt roughness and identify critical cracking locations. It has been an increasing discussion in industry whether temperature changes due to climate change will have considerable influence on infrastructure resilience and sustainability. The method presented here uses vehicle-based sensors to assess pavement roughness during extreme hot and cold temperatures in Phoenix, AZ. This project consisted of developing vehicle-based accelerometers and taking monthly road surveys for a year. Five sensors were mounted to a vehicle, four on the tires and one inside the car, as well a sixth smartphone sensor inside the car. This project covers collecting data at pavement temperatures from 40ºF - 150ºF. The analysis consists of converting accelerometer data into international roughness index values using Fourier transforms and using statistical analysis to verify a relationship between pavement temperature and accelerometer vibration. The results show that hot asphalt concrete temperatures increase the amount of observable accelerometer vibration from a vehicle. Sensors mounted near the tires showed to be more reliable than sensors inside the vehicle. This project demonstrates that accelerometer sensing technology is a cost-effective way to advance the day-to-day operations in highway pavement maintenance and management