Analysis of Driver Behavior in Mixed Autonomous and Non-autonomous Traffic Flows

Jundi Liu, Linda Ng Boyle

Research output: Contribution to journalConference articlepeer-review

Abstract

Autonomous vehicles are expected to improve road safety and efficiency in future transportation systems. A driving simulator study was designed to identify driving styles and the cooperation between human drivers and other AVs. The study captured driver’s following behavior in a fully autonomous driving environment at unsignalized intersections. Participants were asked to make a series of maneuvers (straight through intersection, left turn, and right turn) in two different speed conditions (30, 40 mph) and two different traffic density conditions (with or without other traffic). Analysis of Variance showed that drivers had a significantly larger deviation (defined as the area between two trajectories) during left turn maneuvers when they were traveling at higher speeds. Moreover, the first turning operation had smaller deviation than the second turning operation. The findings have implications for the design of driver-assistance guidance systems in future mixed autonomous and non-autonomous traffic flows.

Original languageEnglish (US)
Pages (from-to)1447-1451
Number of pages5
JournalProceedings of the Human Factors and Ergonomics Society
Volume66
Issue number1
DOIs
StatePublished - 2022
Event66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022 - Atlanta, United States
Duration: Oct 10 2022Oct 14 2022

ASJC Scopus subject areas

  • Human Factors and Ergonomics

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