Virtual Fluid-Flow-Model-Based Lane-Keeping Integrated With Collision Avoidance Control System Design for Autonomous Vehicles
Shuo Cheng, Liang Li, Yonggang Liu, Weibing Li, Hongqiang Guo
Abstract
The automated steering control technology is crucial for autonomous vehicles, and lane-keeping control systems have been developed extensively, but various traffic conditions, and obstacles ahead of the ego vehicle would cause serious traffic collision accidents. Therefore, this paper proposes a virtual fluid-flow-model (VFFM) based lane-keeping integrated with collision avoidance control system (LKCA) to realize the function of both lane-keeping and collision avoidance. Firstly, a novel lane-keeping model is proposed which is inspired by viscous fluid flowing between two parallel plates or around a cylinder. Then, based on the proposed VFFM-based lane-keeping model, the ego vehicle’s path can be planned, and it ensures the performance of lane-keeping and obstacle-avoidance. Finally, an optimal-preview-driver-model-based path tracking controller is designed to track the desired VFFM-based path. The proposed control system is evaluated by both co-simulations of MATLAB/Simulink & CarSim and real-bus tests. Results show the effectiveness of the proposed control system, and it can ensure lane-keeping performance on the premise of obstacle-avoidance.