Vision-based Forward Collision Warning System Design Supported by a Field-Test Verification Platform

This paper proposes a novel approach of developing a vision-based forward collision warning system (V-FCW) under an integrated platform with both V-FCW algorithm development and field-test data driven system verification. The developed verification platform provides huge amount of video data collected from field testing under various real driving conditions with labeled ground truth and fast search capability. Under this integrated platform, the V-FCW system can be effectively developed, tested and verified under various real driving conditions and scenarios in a lab environment, and in a repeatable, cost effective and even automatic way to achieve robust, reliable and high performance.