The impact of auditory continual feedback on take-overs in Level 3 automated vehicles

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Objective: To implement auditory continual feedback into the interface design of a Level 3 automated vehicle and to test whether gaze behavior and reaction times of drivers improved in take-over situations. Background: When required to assume manual control in take-over situations, drivers of Level 3 automated vehicles are less likely than conventional drivers to spot potential hazards, and their reaction time is longer. Therefore, it is crucial that the interface of Level 3 automated vehicles will be designed to improve drivers’ performance in take-over situations. Method: In two experiments, participants drove a simulated route in a Level 3 automated vehicle for 35 min with one imminent take-over event. Participants’ gaze behavior and performance in an imminent take-over event were monitored under one of three auditory interface designs: (1) Continual feedback. A system that provides verbal driving-related feedback; (2) Persistent feedback. A system that provides verbal driving-related feedback and a persistent beep; and (3) Chatter feedback. A system that provides verbal non-driving-related feedback. Also, there was a control group without feedback. Results: Under all three auditory feedback designs, the number of drivers' on-road glances increased compared to no feedback, but none of the designs shortened reaction time to the imminent event. Conclusion: Increasing the number of on-road glances during automated driving does not necessarily improve drivers’ attention to the road and their reaction times during take-overs. Application: Possible implications for the effectiveness of auditory continual feedback should be considered when designing interfaces for Level 3 automated vehicles.

Original languageEnglish
Pages (from-to)145-159
Number of pages15
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Volume75
DOIs
StatePublished - 1 Nov 2020

Keywords

  • Driver performance
  • Gaze behaviour
  • Human-automation interaction
  • Intelligent vehicle system
  • Interface evaluation
  • Warnings

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Applied Psychology

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