Application of Human-Machine Co-driving in Multi-vehicle Formation of Deepracer Automatic Driving Platform

This article introduces the application of human-machine collaborative driving in multi-car platooning based on the Amazon DeepRacer autonomous driving platform, which includes the use of AirTag recognition and lane recognition. In traditional autonomous driving, vehicle control is mostly managed by algorithms with little human intervention. In our research, we enable both algorithms and drivers to share control, with algorithms providing precision and drivers offering adaptability. We discuss the principles and implementation methods of AirTag recognition and how the location information obtained from AirTag recognition can be applied to multi-car platooning. Furthermore, we explore the relevant technologies of lane recognition, which is the core of our autonomous driving system. Finally, we propose some improvement measures for practical application to ensure the safety and reliability of human-machine collaborative driving in multi-car platooning. The results of this article shows that manual driving can handle special situations, such as changing lanes, avoiding complex obstacles, and so on. Autonomous driving is more suitable for regular road driving and emergency situations.