Model Based Vehicle Tracking for Autonomous Driving in Urban Environments

Situational awareness is crucial for autonomous driving in urban environments. This paper describes moving vehicle detection and tracking module we developed for our successful entry in the Urban Grand Challenge, an autonomous driving race organized by the U.S. Government in 2007. The module provides reliable tracking of moving vehicles from a high-speed moving platform using laser range finders. Our approach models both dynamic and geometric properties of the tracked vehicles and estimates them using a single Bayes filter.