Vehicle Detection and Tracking using Radar for Lane Keep Assist Systems

In this paper we propose a lane keep assist and warning system using automotive radars in different real time scenarios. Owing to radar’s immunity to weather and lighting conditions, it is possible to detect objects with high accuracy. We use Bayesian filtering technique to accurately detect and track vehicles moving towards the ego vehicle. A warning signal is generated if there is a vehicle in the proximity zone. In this work we explain the architecture of lane keep assist and warning (LKAW) systems using radar and also compare it with other lane keep assist systems which use camera as their primary sensors.