Effects of Task-Induced Fatigue in Prolonged Conditional Automated Driving

Oliver Jarosch, Hanna Bellem, Klaus Bengler

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

Objective: The aim of this study was to investigate the effects of task-induced fatigue in prolonged conditional automated driving on takeover performance. Background: In conditional automated driving, the driver can engage in non–driving related tasks (NDRTs) and does not have to monitor the system and the driving environment. In the event that the system hits its limits, the human driver must regain control of the car. To ensure safety, adequate driver fallback performance is necessary. Effects of the drivers’ state and the engagement in NDRTs need to be investigated. Method: Seventy-three participants experienced prolonged conditional automated rides and simultaneously had to engage in either an activating quiz or a fatiguing monitoring task (between subjects). After 50 minutes, a takeover situation occurred, and participants had to regain control of the car. Results: Prolonged conditional automated driving and simultaneously engaging in NDRTs affected the driver’s state and the takeover performance of the participants. Takeover performance was impaired when participants had to deal with monotonous NDRTs. Conclusion: An engagement in monotonous monitoring tasks in conditional automated driving affects the driver’s state and takeover performance when it comes to takeover situations. Especially in prolonged automated driving, an adequate driver state seems to be necessary for safety reasons. Application: The results of this study demonstrate that engagement in monotonous NDRTs while driving conditionally automated may negatively affect takeover performance. A monitoring of the driver state and adapted assistance in a takeover situation seems to be a good opportunity to ensure safety.

Original languageEnglish
Pages (from-to)1186-1199
Number of pages14
JournalHuman Factors
Volume61
Issue number7
DOIs
StatePublished - 1 Nov 2019

Keywords

  • autonomous driving
  • driver impairment
  • drowsiness
  • human automation interaction
  • non–driving related tasks
  • simulation
  • vehicle automation

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