Vehicle lane change behavior detection method based on machine learning

In this paper, a vehicle forced lane change behavior detection algorithm based on machine learning is proposed. Collect the vehicle's forward looking monocular video image and determine the reasonable region of interest: The intention and process of vehicle forced lane change are analyzed by video image features, and the vehicle forced lane change motivation model is established; Use Kalman filter in machine learning to track vehicles: Calculate the centroid coordinates of the target vehicle and the distance of the lane line, and determine whether the vehicle in front has a forced lane change behavior in combination with the lane change motivation model. The experimental results show that this method has higher accuracy in detecting vehicle lane change behavior. © 2023, Aracne Editrice. All rights reserved.