English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper presents an adaptive haptic shared control framework wherein adriver and an automation system are physically connected through a motorizedsteering wheel. The automation system is modeled as an intelligent agent thatis not only capable of making decisions but also monitoring the human'sbehavior and adjusting its behavior accordingly. To enable the automationsystem to smoothly exchange the control authority with the human partner, thispaper introduces a novel self-regulating impedance controller for theautomation system. To determine an optimal modulation policy, a cost functionis defined. The terms of the cost function are assigned to minimize theperformance error and reduce the disagreement between the human and automationsystem. To solve the optimal control problem, we employed a nonlinear modelpredictive approach and used the continuation generalized minimum residualmethod to solve the nonlinear cost function. To demonstrate the effectivenessof the proposed approach, simulation studies consider a scenario where thehuman and the automation system both detect an obstacle and negotiate oncontrolling the steering wheel so that the obstacle can be avoided safely. Thesimulations involve four interaction modes addressing the cooperation status(cooperative and uncooperative) and the desired direction of the controltransfer (active safety and autopilot).

Modulation of Control Authority in Adaptive HapticShared Control Paradigms