Effective Finite Time Stability Control for Human-Machine Shared Vehicle Following System
Zihan Wang, Mengran Li, Ronghui Zhang, Jing Zhao, Chuan Hu, Xiaolei, Ma, Zhijun Qiu

TL;DR
This paper proposes an adaptive finite time sliding mode control system for human-machine shared vehicle following, effectively maintaining stability despite driver reaction time fluctuations.
Contribution
It introduces a novel two-layer adaptive sliding mode controller that enhances stability and convergence speed in shared vehicle control systems.
Findings
Maintains safe distance with acceleration error within 0.5 m/s^2
Reduces stabilization time by 27.3% compared to traditional controllers
Improves robustness against driver reaction time variability
Abstract
With the development of intelligent connected vehicle technology, human-machine shared control has gained popularity in vehicle following due to its effectiveness in driver assistance. However, traditional vehicle following systems struggle to maintain stability when driver reaction time fluctuates, as these variations require different levels of system intervention. To address this issue, the proposed human-machine shared vehicle following assistance system (HM-VFAS) integrates driver outputs under various states with the assistance system. The system employs an intelligent driver model that accounts for reaction time delays, simulating time-varying driver outputs. A control authority allocation strategy is designed to dynamically adjust the level of intervention based on real-time driver state assessment. To handle instability from driver authority switching, the proposed solution…
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Taxonomy
TopicsVehicle Dynamics and Control Systems · Automotive and Human Injury Biomechanics
