Human-machine shared control for lane departure assistance based on hybrid system theory

To improve the human-machine cooperation of lane departure assistance system (LDAS), a human-machine shared control strategy based on hybrid system theory was proposed. By considering vehicle's discrete and continuous states and time-varying longitudinal speed, the hybrid system was formalized as hybrid automaton, and the shared control strategy was built to govern the human-machine interaction. Robust gain-scheduling energy-to-peak method was adopted to design the assistance system controller. The D-stability of the system was also studied and guaranteed by solving the linear matrix inequality (LMI). The proposed human-machine shared control method was evaluated via the co-simulation of CarSim/Simulink and the hardware-in-loop (HIL) experiment. The results showed that the proposed approach can effectively keep the vehicle in lane and a good human-machine coordination was demonstrated.