Design and Implimentation of a Real-Time Platform for Studying Interaction Behaviors of Scaled-Down Autonomous Vehicles

Autonomous vehicle was considered to be one of the toughest challenges in the fields of artificial intelligent, pattern recognition, computer vision, sensor fusion and control theory. In the paper, a kind of scaled-down autonomous vehicles was demonstrated and a more human-like environment perception and control system were proposed, including obstacle detection, combined feature-based and model-based lane mark detection algorithm. To verify the efficiency of the proposed perception and control system, a test platform was built. With the platform, the interaction behaviors between autonomous vehicles were studied.