Shared Driving Assistance Design Considering Human Error Protection for Intelligent Electric Wheelchairs

Abstract

To effectively provide the handicapped with mobility aids, studies on the shared autonomy of robotic systems have been widely cultivated. This study proposes an adaptive shared control strategy to realize reliable and safe driving assistance on an intelligent electric wheelchair with protection against human errors. The theoretical framework of the system is analyzed by the linearized reference wheelchair model and stable characteristics of obstacle avoidance behavior can be subsequently derived according to the Lyapunov analysis and Liénard-Chipart criterion. Based on the convex analysis, the relationships between human input and robot control are investigated to determine shared control weights. As such, safety and reliability can be guaranteed. To verify the performances of the proposed approach, human errors including skill-based errors, decision errors, and violations are considered in the experiments. The experimental results based on a comprehensive study show that the proposed method is capable of enhancing driving safety and reducing operation burden in terms of the designed criteria with fluency, smoothness, and time efficiency while protecting the user from human manual errors.