Adaptive authority allocation-based driver-automation shared control for autonomous vehicles

To avoid crashes caused by driver error in avoiding obstacles, a driver-centered steering assist controller with an adaptive authority allocation system is proposed for cooperative control purposes. To begin with, a concept of space collision risk (SCR) is introduced creatively for assessing the vehicle's safety status in which the relative distance and the relative angle between the vehicle and the obstacle are taken into consideration. Meanwhile, the SCR-based authority allocation system is addressed to allocate steering authorities between the human driver and the assist controller adaptively to reduce SCR to zero as soon as possible. After that, an autonomous steering controller based on the model predictive control (MPC) technique and the artificial potential field (APF) method, considering not only the vehicle stability constraints but also roads and obstacles constraints, is developed to aid the human driver when necessary. In the end, the proposed algorithm is simulated in the CarSim-Simulink cosimulation platform under a series of typical scenarios, which shows the feasibility and effectiveness of the presented shared steering control method.

Automated summary

A driver-centered steering assist controller is proposed to reduce accidents caused by obstacles avoidance, with an adaptive authority allocation system and a concept of space collision risk introduced. The allocation of steering authorities is done adaptively based on SCR, and an autonomous steering controller using MPC and APF techniques is developed to aid the driver when necessary, showing feasibility and effectiveness in simulations.