Measuring and Predicting Drivers’ Takeover Readiness and Supporting Takeover Transitions in Automated Driving

As vehicle automation progresses, the driver’s role will transform from an operator to a system supervisor. Level 3 automated vehicles (AVs) possess the ability to perceive their surroundings and interpret road conditions while performing driving tasks such as accelerating, braking, steering, and navigating. The advanced capability allows the driver to engage in non-driving related tasks (NDRTs). However, if an AV encounters a system limit, such as vision system failure or path planning issues, the driver must quickly regain control of the vehicle. This transition from automated control to manual control presents a crucial challenge to the human driver, as they become increasingly out of the loop (OOTL) (Zhou et al., 2020; Petersen et al., 2019; Molnar et al., 2017) To help inform and address these issues, this report is organized into two parts, presenting two studies aimed at facilitating takeover transitions when using Level 3 automation. Part 1 examines driver takeover readiness; that is, driver behavior and physiological indices and other factors that are predictive of successful takeover performance. Knowledge of such measures can inform the development and tuning of driver state monitoring (DSM) systems. Part 2 examines a driver support system, a gaze guidance system, that helps orient driver’s attention to areas of potential risk during a control takeover. This study leverages data from an existing naturalistic driving study as well as theoretical models of driver visual attention allocation.

• Record URL:
  https://aaafoundation.org/wp-content/uploads/2023/09/202309-AAAFTS-Predicting-Readiness-and-Supporting-Takeover-Transitions.pdf
• Summary URL:
  https://aaafoundation.org/wp-content/uploads/2023/09/202309-AAAFTS-Driver-Takeover-Summary.pdf
• Supplemental Notes:
  • ©2023, AAA Foundation for Traffic Safety.
• Corporate Authors:

  AAA Foundation for Traffic Safety

  Washington, DC  United States 
• Authors:
  • Han, Doowon
  • Liu, Jundi
  • Zhou, Feng
  • Tilbury, Dawn
  • Robert, Lionel
  • Molnar, Lisa
  • Yang, X Jessie
• Publication Date: 2023-9

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; Photos; References; Tables;
• Pagination: 52p

Subject/Index Terms

• TRT Terms: Autonomous vehicle handover; Behavior; Driver support systems; Drivers; Level 3 driving automation; Physiological aspects
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01895852
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 11 2023 2:21PM