Target Vehicle Identification in Curved Roads in Adaptive Cruise Control Systems

Today, adaptive cruise control systems play an important role in automotive technology. The performance of adaptive cruise control systems has a significant impact on the level of satisfaction of a self-driving car. Vehicles equipped with adaptive cruise control maintain distance with the vehicle in front, control speed, and prevent accidents using their technology and with the help of radar antennas, cameras, or laser rangefinders. However, adaptive cruise controls are incapable in some cases such as detecting vehicles on curved roads. In this project, A real-time solution has been proposed to solve this problem. This method will be validated with the help of data obtained from open-source maps and satellite images of roads, and, finally, the results will be analyzed. The performance of the method is evaluated as appropriate so that the risk of accident is reduced to zero because of the correct identification of target vehicles within a normal ACC range. It also has the capability of correct identification of non-target vehicles.