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A New Method for Target Object Selection for ACC System Based on Analysis of Vehicle Trajectories
Abstract:
The trajectory variation of preceding objects with changing road curvature and uncertain driving behaviors of both host and preceding cars make it difficult for conventional radar-based Adaptive Cruise Control (ACC) system to effectively select its valid target object, which is mainly caused by the deficient judgment about the preceding curves and the behaviors of preceding cars. Through analysis of the trajectories that host and preceding objects generate, the new proposed method can differentiate the operating conditions of each car, either in straight lane, on curve or in lane-change, thus front path prediction and host vehicle's future lane estimation can be precisely fulfilled.
From radar and host car's information a coordinate that changes under several criteria can be established, and based on this coordinate the trajectories of preceding and host car can be recorded and analyzed, some mathematics methods are adopted to reach the qualitative conclusion.
The new method can find the valid target for ACC system and enable the system to conquer some typical drawbacks of conventional ACC, such as the confusion between lane-change and curve-enter of a preceding car, and also the speed of a preceding object can be modified as soon as it enters a curve. Simulations have been conducted to validate the method, and the results show that the proposed method could exactly judge the operating condition and find correct target for ACC system.