Cut-in vehicle warning system exploiting multiple rotational images of SVM cameras

Smart cruise control (SCC) is one of the representative systems of advanced driver assistance systems (ADAS). Conventional SCC systems have a problem in that they cannot detect a cut-in vehicle in a short distance because the field of view (FOV) of their sensors for detecting vehicles ahead is limited. To solve this problem, this paper proposes a novel method using surround view monitoring (SVM) cameras which can observe the surroundings of a host vehicle without blind spots. To reduce the variation of projected appearance according to the relative position, this paper proposes to exploit multiple virtual camera images (rotational images). In each rotational image, vehicles are detected using a part-based method: tires are detected and then vehicles are detected by combining the tires. Detected tires in multiple rotational images are integrated and tracked in 3D space. Finally, the proposed method determines whether a vehicle has intruded into the cut-in zone based on the position and orientation of the vehicle. The proposed method succeeds to detect vehicle even by a simple method thanks to the rotational image even without any special H/W. The proposed method uses only the sensor adopted in mass-produced vehicles and it is very practical. Moreover, the method can estimate the surrounding vehicle position accurately enough to be used in the braking control system. The performance of the proposed method is evaluated with various driving situations, of which the total length is 447.8 min (43.5 min for the test track and 404.3 min for natural driving). Among 211 cut-in events, 208 events are correctly warned and only 3 false warnings occur. Although the proposed method simultaneously processes the rotational images generated from three SVM cameras (forward, left, and right), the average processing time per frame takes about 58 ms.