Likelihood-Field-Model-Based Dynamic Vehicle Detection with Velodyne

Abstract

Dynamic vehicle detection is an important module for Autonomous Land Vehicle (ALV) navigation in outdoor environments. In this paper, we present a novel dynamic vehicle detection algorithm based on the likelihood field model for an ALV equipped with a Velodyne LIDAR. An improved 2D virtual scan is utilized to detect the dynamic objects with the scan differencing operation. For every dynamic object, a vehicle is fitted with the likelihood field model, and the motion evidence and motion consistence of the fitted vehicle are exploited to classify the dynamic object into the vehicle or not. The performance of the algorithm is validated on the data collected by our ALV in various environments.