A Radar Guided Vision System for Vehicle Validation and Vehicle Motion Characterization

This paper describes a radar-guided monocular vision system that detects, validates, and tracks the preceding vehicle and thus predicts its lane-change intentions. A vision-based lane tracking process is developed to create a stable motion model in order to map the radar targets to image coordinates and consequently generate the region of interest (ROI) to search for a potential preceding vehicle. Model-based object classification algorithms are then applied to validate the existence of a vehicle in this ROI. Once the detected primary target vehicle, which is in the same lane as the host vehicle, is validated, it will be continuously tracked until it leaves the host lane. The spatial-temporal tracking history of the primary target vehicle is used to infer its intention of changing lanes. This prediction results from a characterization process for the primary target motion vector. The radar-vision integrated system has been evaluated on real-world data collected using a test vehicle equipped with a radar sensor, vision sensor, and a host processor.