Visual Attention Patterns in Automated and Manual Lane Change Maneuvers

MIT Center for Transportation & Logistics Research Paper No. 2023/036

Proceedings of the Human Factors and Ergonomics Society Annual Meeting, volume 67, issue 1, 2023[10.1177/21695067231192216]

Posted: 25 Apr 2025

See all articles by Thomas Z. Noonan

Thomas Z. Noonan

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics

Pnina Gershon

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics

Bruce Mehler

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics

Bryan Reimer

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics

Date Written: January 01, 2023

Abstract

Tesla auto lane change is a feature which automatically steers the vehicle into an adjacent lane when prompted by the driver. 2,473 naturalistic motorway lane changes were annotated to compare driver eye glance behavior before, during, and after maneuvers performed manually and with automation. Change point detection and glance area prevalence revealed distinct patterns in the drivers’ glance behavior. In manual lane changes drivers had more glances to adjacent lanes and over-the-shoulder prior to and during lane crossing compared to automated lane changes which were associated with fewer glances laterally but more glances to the rearview mirror. These differences were more pronounced in lane changes into the leftmost lane. However, in automated exiting maneuvers, drivers had more preparatory glances to adjacent lanes compared to manual. These behaviors could be related to differences in driver visual attention associated with the use of automation. © 2023 Human Factors and Ergonomics Society.

Keywords: Attention, Automation, Driver Behavior, Driving

Suggested Citation

Noonan, Thomas Z. and Gershon, Pnina and Mehler, Bruce and Reimer, Bryan, Visual Attention Patterns in Automated and Manual Lane Change Maneuvers (January 01, 2023). MIT Center for Transportation & Logistics Research Paper No. 2023/036, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, volume 67, issue 1, 2023[10.1177/21695067231192216], Available at SSRN: https://ssrn.com/abstract=5230345

Thomas Z. Noonan (Contact Author)

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics ( email )

United States

Pnina Gershon

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics ( email )

United States

Bruce Mehler

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics ( email )

United States

Bryan Reimer

Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics ( email )

United States

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