Vehicle axle counting using two LIDARs for toll collection systems

We propose vehicle wheel detection and axle counting techniques using LIDARs (Laser Imaging Direction and Ranging) for toll collection systems. Commonly-available LIDARs have insufficient scan speeds to count axles for high-speed vehicles. We install two LIDARs at left and right sides of the road to compensate for low scanning resolution. Range data of LIDARs are transformed into orthogonal coordinates that represent the depth from the LIDARs and the height from the road surface. Wheel candidates are extracted by using depth histograms above the road surface. The wheel candidates of two LIDARs are integrated and verified to reduce impacts of noises and missing data of wheel candidates. Experimental results using 206 transit data explain that our approach makes axle counting robust and reduces counting errors.