Haptic shared steering control with an adaptive level of authority based on time-to-line crossing

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Abstract

Traditional driver-automation interaction trades control over the vehicle back and forth between driver and automation. Haptic shared control offers an alternative by continuously sharing the control through torques on the steering wheel and pedals. When designing additional feedback torques, part of the design choice lies in the stiffness around the neutral steering point: also called the Level of Haptic Authority (LoHA), which is usually static and tuned to balance safety benefits (better at high LoHA) with conflicts torques in case of different intentions between automation and driver (higher conflict torques with increased LoHA). In this paper we explore the idea of situation-adaptive LoHA: in this case during lane-keeping by changing the LoHA based on time to lane crossing (TLC). Consequently, when safety margins are high (e.g., when driving on a wide road) the LoHA is low, but the LoHA would only increase when safety margins decrease. We propose two alternative design approaches to apply the LoHA: symmetrically and asymmetrically (i.e., only increase of LoHA in the direction of the low TLC). We compared these design in an explorative driving simulator study (n=14) to driving with two static LoHA designs (low and high). We found that compared to the high LoHA controller, both adaptive LoHA controllers designs resulted in similar safety margins, but at decreased conflict torques. Hence, a TLC-based adaptive LoHA controller seems to be an effective approach to mitigate conflicts while maintaining the safety benefits associated with HSC.
Original languageEnglish
Pages (from-to)49-54
JournalIFAC-PapersOnLine
Volume52
Issue number19
DOIs
Publication statusPublished - 2019
Event14th IFAC Symposium on Analysis, Design, and Evaluation of Human Machine Systems, HMS 2019 - Tallinn, Estonia
Duration: 16 Sept 201919 Sept 2019

Keywords

  • Haptic Shared Control
  • Adaptive
  • Level of Haptic Authority
  • Human-Machine interaction
  • driving simulator

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