Citation

Izadi V, Ghasemi AH. Transp. Eng. (Amsterdam) 2022; 10: e100141.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.treng.2022.100141

PMID

unavailable

Abstract

This paper quantifies the performance of an adaptive haptic shared control (HSC) paradigm in transferring the control authority between humans and automation when both agents face a conflict. Here, we considered the reverse-intent conflict between the driver and the automation system. We invited 27 participants to drive a simulated vehicle through a course wherein for sixty percent of obstacles, the human driver is instructed to avoid the obstacles in the opposite direction as the automation system was programmed. We employed a model predictive controller to determine the automation's optimal impedance modulation policy so that the differential torque on the steering wheel is minimized while the obstacle is safely avoided. We compared the performance of the dynamic adaptive HSC with two other adaptive haptic shared control paradigms: assistive HSC and active-safety HSC. The assistive HSC paradigm represents a case where the automation has relatively high confidence in the driver's actions. On the other hand, the active-safety HSC paradigm represents a case where the automation has relatively low confidence in the driver's action. In the dynamic adaptive HSC, the automation adaptively assigns different policies to modulate its impedance based on the human's adopted impedance. When a human's adopted impedance is high, the automation in the dynamic adaptive HSC paradigms acts more like the assistive paradigm, and when the human's impedance is low, the automation in the adaptive paradigms acts more like the active-safety paradigm. Here, we used the human grip force as a proxy to estimate the human impedance on the steering wheel. We compared the performance of these three haptic shared control schemes by analyzing five metrics, including obstacle hits and metrics related to driving maneuvers around the obstacles that were avoided. Our statistical analysis indicated that the dynamic adaptive HSC paradigm supports the best overall team performance in resolving a conflict between the driver and automation system while keeping the vehicle safe.

Language: en

Keywords

Haptic shared control; Human factors; Human-automation interaction