Automated Winter Road Maintenance Using Road Surface Condition Measurements

Principal Investigator(s):

Rajesh Rajamani, Professor, Chair, Mechanical Engineering

Project summary:

Real-time measurement of tire-road friction coefficient is extremely valuable for winter road-maintenance operations and can be used to optimize the kind and quantity of the deicing and anti-icing chemicals applied to the roadway. In this project, a wheel-based tire-road friction coefficient measurement system was first developed for snowplows. Unlike a traditional Norse meter, this system is based on the measurement of lateral tire forces, has minimal moving parts, and does not use any actuators, making it reliable and inexpensive. A key challenge was quickly detecting changes in the tire-road friction coefficient while rejecting the high levels of noise in measured force signals. Novel filtering and signal processing algorithms were developed to address this challenge, including a biased quadratic mean filter and an accelerometer-based vibration-removal filter. Detailed experimental results are presented on the performance of the friction estimation system on different types of road surfaces. Experimental results show that the biased quadratic mean filter works very effectively to eliminate the influence of noise and quickly estimate changes in friction coefficient. Further, the use of accelerometers and an intelligent algorithm enables elimination of the influence of driver steering maneuvers, thus providing a robust friction measurement system. In the second part of the project, the developed friction measurement system was used for automated control of the chemical applicator on the snowplow. An electronic interface was established with the Force America applicator to enable real-time control. A feedback control system that utilizes the developed friction measurement sensor and a pavement temperature sensor was developed and implemented on the snowplow.

Project details: