Evaluation of the human interaction with automated vehicles on highways

Human-driven vehicles (HVs) will be interacting with automated vehicles (AVs) at AV market penetrations between 0% and 100%. However, little is known about how HVs interact with AVs. This study addresses knowledge gaps related to how HVs will interact with AVs on highways. The research was conducted in Oregon State University's Passenger Car Driving Simulator. Additionally, a Shimmer3 GSR+ sensor was used to measure participants' galvanic skin response (GSR). Two independent variables (i.e. leading vehicle speed and autonomy) were selected and resulted in a 2x2 factorial design. Participants were also exposed to two hard-braking scenarios: one with a leading HV and one with a leading AV. A post-drive survey included questions about the participant's level of comfort following HVs and AVs. The driving simulator experiment was successfully completed by 36 participants. Results from the linear mixed model show that driver level of stress was 70% higher in hard-brake scenarios involving HVs versus AVs. Of the 78 hard-braking scenarios tested in this study, 10 crashes were observed (4 with an HV, 6 with an AV). Half of the participants involved in a crash with an HV perceived the leading vehicle to be at fault, while all the participants who crashed with an AV blamed themselves for the error. Additionally, drivers over the age of 34.5 were found to give AVs 2% larger headways than HVs, while younger drivers gave AVs 18% smaller headways than HVs. Zero participants above the age of 34.5 years self-reported being ‘unconcerned’ when following an AV in the post-drive survey, while 38% of participants under the age of 34.5 did. This study supports the need for a better understanding of how human drivers will interact with AVs to calibrate human driver models when AV market penetrations are between 0% and 100%.

Authors

Institutions

Publication Details

Journal
Traffic Safety Research
Published
2025-01-10
DOI
https://doi.org/10.55329/xwwy8052
Citations
4
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
9.75

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of the human interaction with automated vehicles on highways

Haizhong Wang, David Hurwitz, Cadell Chand, Hisham Jashami
4 citations
Traffic Safety Research
Human-Automation Interaction and Safety
9.75
article

Evaluation of the human interaction with automated vehicles on highways

Haizhong Wang, David Hurwitz, Cadell Chand, Hisham Jashami
article en
4 citations

Abstract

Human-driven vehicles (HVs) will be interacting with automated vehicles (AVs) at AV market penetrations between 0% and 100%. However, little is known about how HVs interact with AVs. This study addresses knowledge gaps related to how HVs will interact with AVs on highways. The research was conducted in Oregon State University's Passenger Car Driving Simulator. Additionally, a Shimmer3 GSR+ sensor was used to measure participants' galvanic skin response (GSR). Two independent variables (i.e. leading vehicle speed and autonomy) were selected and resulted in a 2x2 factorial design. Participants were also exposed to two hard-braking scenarios: one with a leading HV and one with a leading AV. A post-drive survey included questions about the participant's level of comfort following HVs and AVs. The driving simulator experiment was successfully completed by 36 participants. Results from the linear mixed model show that driver level of stress was 70% higher in hard-brake scenarios involving HVs versus AVs. Of the 78 hard-braking scenarios tested in this study, 10 crashes were observed (4 with an HV, 6 with an AV). Half of the participants involved in a crash with an HV perceived the leading vehicle to be at fault, while all the participants who crashed with an AV blamed themselves for the error. Additionally, drivers over the age of 34.5 were found to give AVs 2% larger headways than HVs, while younger drivers gave AVs 18% smaller headways than HVs. Zero participants above the age of 34.5 years self-reported being ‘unconcerned’ when following an AV in the post-drive survey, while 38% of participants under the age of 34.5 did. This study supports the need for a better understanding of how human drivers will interact with AVs to calibrate human driver models when AV market penetrations are between 0% and 100%.

Traffic Safety ResearchVol. 9
Oregon State University (US)
University Transportation Centers
Openalex Percentile: Top 3%
Human-Automation Interaction and Safety
9.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.