Integrated object and road border tracking using 77 GHz automotive radars

Radar sensors are widely used in automotive on-board systems such as adaptive cruise control, which tracks the preceding vehicle and keeps a safe distance. The authors go a step further and exploit the potential of a high resolution radar sensor for the estimation of the road borders and the reconstruction of the traffic scenario based on object tracking. A FMCW millimetre wave radar is mounted in the front bumper of a vehicle and delivers object lists to the central fusion processor, where detections are considered as measurements to an integrated model based road border estimation system. The algorithm presented is designed to improve the prediction of paths and trajectories of the ego-vehicle in future enhanced collision warning and collision avoidance systems. Given the characteristics and limitations of a radar system, such as heavy clutter, the algorithms are tested with real data and perform reliably in highway and extra-urban scenarios and are competitive with data fusion and stereo vision systems, but with lower computational load.