Abrupt Lane Change Recognition Model Towards Autonomous Vehicle Based on Lane Line Inclination

Detection and recognition of abrupt lane change behavior of vehicles are essential for safe driving and hold significant importance for the development of autonomous driving technology. This paper proposes a novel model to recognize the abrupt lane change behavior of vehicles based on the lane line inclination angle obtained through image processing. The model consists of three main components: lane detection, lane line inclination calculation, and recognition of abrupt lane change behavior. First, lanes in images are detected through image processing. Then, the lane line inclination angle is calculated using a devised algorithm of perspective transformation. Finally, by incorporating lane line inclination and vehicle speed, a novel algorithm is proposed to recognize abrupt the lane change behavior dynamically. The proposed model innovatively transforms the detection of abrupt lane change behavior into the recognition of the vehicle's traveling state. Experimental results demonstrate that the proposed model is able to recognize abrupt lane change behavior of vehicles with a high accuracy. Moreover, the algorithm is simple and efficient, enabling real-time processing on autonomous vehicles.