Supervising the self-driving car: Situation awareness and fatigue during highly automated driving

Vehicle automation promises to reduce the demands of the driving task, making driving less fatiguing, more convenient, and safer. Nevertheless, Level 3 automated vehicles rely on a human driver to be ready to resume control, requiring the driver to reconstruct situation awareness (SA) and resume the driving task. Understanding the interaction between non-driving-related task (NDRT) use, SA, and takeover capacity is important because an effective takeover is entirely dependent on, and scaffolds from, effectively reconstructed SA. While a number of studies have looked at the behavioral impact of being ‘in- or on-the-loop’, fewer consider the cognitive impact, particularly the consequences for SA. The present study exposed participants to an extended simulated automated drive involving two critical takeover scenarios (early- and late-drive). The authors compared automated vehicle (AV) operators who were required to passively monitor the vehicle to those engaging with self-selected NDRTs. Monitoring operators demonstrated lower total- and schema-specific SA count scores following a fatiguing drive compared to those engaging with self-selected NDRTs. NDRT engagement resulted in no significant difference in SA count scores early- and late-drive. Assessment of differences in the type and sensory modality of NDRTs indicated operators make fundamentally different selections about the NDRTs they engage with in an automated driving environment compared to a manual environment. The present study provides further evidence linking SA and AV operator behavior and underscores the need to understand the role of SA in takeover capacity. The findings suggest that although SA declines over time regardless of driving task requirements (Monitoring versus NDRT engagement), NDRT use may facilitate better SA construction, with implications for the regulation of NDRT use in AVs as the technology progresses.


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  • Accession Number: 01882330
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 22 2023 1:28PM