Enhanced Radar-Based Target Identification and Tracking on Curved Road

The paper describes a new algorithm for radar-based target vehicle identification and tracking on curved roads for Adaptive Cruise Control (ACC) applications. The key problems are the distinction between target curve-entry/exit and lane-change and the identification of the host-lane proceeding vehicle from the adjacent-lane one in curves. In order to make a more accurate distinction between curve-entry/exit and lane-change of the target vehicle, the GOF (Goodness of Fit) of regression equations respectively corresponding to these two scenarios is tested by using a correlation coefficient method and by introducing additional distinction criteria which have a clear physical meaning. Furthermore, the deviation of the measured lateral distance from the theoretical value is used to estimate whether the proceeding vehicle is in the host lane or in the adjacent lane. Tests show that the method is able to identify the position of the target vehicle on a curved road with high reliability.