Adaptive shared control strategy for lane changing assistance system via multi-mode switching. Issue 18 (December 2020)

• Record Type: Journal Article
• Authors: Zhang, Wenxin; Zhao, Youqun; Zhang, Xinglong; Lin, Fen
• Is Part Of: Journal of the Franklin Institute. Volume 357:Issue 18(2020)
• Page Start: 13304
• Page End: 13325
• Publication Date: 2020-12
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2020.08.027
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: To address the lateral control issue between the automatic controller and the driver for lane changing assistance system, we present a novel multi-mode adaptive shared control strategy in optimal control framework. Different from traditional approaches that achieve shared control through adjusting control authority allocation, we aim at designing a human-friendly adaptive shared control scheme which can provide the driver with assistance in accordance with driving demands via multi-mode switching. Three control modes are proposed: 1. minimum-lateral error mode; 2. minimum-lateral acceleration mode; 3. minimum-interference mode. Meanwhile, we develop a hybrid model based on hidden markov model (HMM) and support vector machine (SVM) to recognize the optimum control mode. Mathematically, the shared control scheme is described as an optimal control problem, which is then addressed by using the improved Radau pseudospectral method (RPM). Numerical analysis and the driver-in-the-loop (DIL) tests show that the proposed shared control strategy has the advantage of ensuring driving safety while reducing driver's workload.