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The collision avoidance system in an autonomous vehicle, intended to address traffic safety issues, has a crucial function called collision estimation. It accomplishes this by identifying potential dangers and notifying the drivers in advance or by using autonomous control to navigate safely. In this work, a novel approach is proposed for generating and selecting a lane change trajectory for the vehicle in a driving scenario where two vehicles are simultaneously executing lane change processes on highways and approaching the same target lane. Moreover, a novel fuzzy logic estimator based on time-to-collision (TTC) and time-to-gap (TTG) is designed to estimate the collision risk. In the collision avoidance process, the proposed estimator is utilized to determine the risk of a collision with polynomial function-based generation of possible lane change trajectories. The safest lane change trajectory is then provided to the …