Research on adaptive cruise control algorithm considering potential risk avoidance

Abstract

Sensor perception blind areas is one of the main potential threats in the cruising process of intelligent vehicles. To reduce the impact of sensor perception blind areas and maximize the effective environmental information around vehicles, this paper designed an adaptive cruise control algorithm considering potential risk avoidance based on the blind areas identification technology of lidar sensors and Lagrange multiplier method. First of all, this paper summarizes and classifies the common sensor blind areas in daily driving and then divides them into relative motion types and relative static types. Then, based on the motion characteristics of the two kinds of blind area edge line point cloud data, a blind area recognition algorithm is designed to realize the recognition and judgment of the two kinds of sensor perception blind areas. According to the characteristics of the sensor perception blind areas above, under multiple constraints such as comfort and fuel economy, the Lagrange multiplier is introduced, and the adaptive cruise control model considering potential risk avoidance is designed to control the vehicle trajectory and speed, to reduce the influence of the sensor perception blind areas and obtain the surrounding environmental information to the maximum extent. According to the results of simulation analysis, the algorithm can effectively identity the two kinds of sensor perception blind areas and control the intelligent vehicle to drive at the desired trajectory and speed, which enhances the ability to acquire surrounding environment information and avoiding potential risks in the cruising process of the intelligent vehicle.