Evaluation of the human interaction with automated vehicles on highways
DOI:
https://doi.org/10.55329/xwwy8052Keywords:
autonomous vehicles, driving simulatorAbstract
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%.
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Author Biographies
Cadell Chand, Oregon State University, the United States of America
Cadell Chand received his M.S. at Oregon State University. His research interests cover traffic safety, MaaS, emerging technology, human factors, and active transportation. He is currently a Traffic Analyst at Washington County, OR and serves on the Oregon Traffic Control Devices Committee.
CRediT contribution: Conceptualization, Data curation, Investigation, Methodology, Software, Visualization, Writing—original draft.
Hisham Jashami, Oregon State University, the United States of America
Hisham Jashami is an Assistant Professor (Sr Res) at Oregon State University. Dr. Hisham Jashami's research has been focused on areas related to transportation safety, human factors, driving and bicycling simulators, autonomous vehicles, data visualization, and statistical methods. During the course of his academic career, Dr. Jashami worked on externally funded research from agencies including the Federal Highway Administration, the National High-way Traffic Safety Administration, the Pacific Northwest Transportation Consortium (PacTrans), and various State Departments of Transportation, e.g. Oregon DOT and Michi-gan DOT. This research has led to the publication of over 100 peer-reviewed journal articles, conference papers, and technical reports. He is a certified Road Safety Professional Engineer.
CRediT contribution: Data curation, Formal analysis, Resources, Validation, Visualization, Writing—original draft.
Haizhong Wang, Oregon State University, the United States of America
Haizhong Wang is a Professor at Oregon State University. Dr. Haizhong Wang conducts research in the areas of traffic flow modeling and simulation from both deterministic and stochastic perspectives, transportation system planning and travel behavior analysis, traffic system control and optimization, intelligent transportation system in particular the impacts of connected and autonomous vehicle on traffic operation and infrastructure management, emergency evacuation and disaster response in particular the evacuee decision-making behavior under emergent scenarios through agent-based modeling and simulation, and post-disaster transportation network resiliency and recovery problems.
CRediT contribution: Conceptualization, Funding acquisition, Supervision, Writing—review & editing.
David Hurwitz, Oregon State University, the United States of America
David Hurwitz is a Professor of transportation engineering, Director of the Kiewit Center for Infrastructure and Transportation Research, and Director of the Driving and Bicycling Research Laboratory in the School of Civil and Construction Engineering at Oregon State University. Dr. Hurwitz conducts research in the areas of transportation safety, transportation human factors, traffic control devices, bicycles and pedestrians, and commercial motor vehicles. In particular, Dr. Hurwitz is interested in the consideration of user behavior in the design, evaluation, and innovation of surface transportation systems.
CRediT contribution: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing—review & editing.
References
Barlow, Z., H. Jashami, A. Sova, D. S. Hurwitz, M. J. Olsen (2019), 'Policy processes and recommendations from Unmanned Aerieal System operations near roadways based on visual attention of drivers', Transportation Research Part C: Emerging Technologies, 108, 207–222. DOI: https://doi.org/10.1016/j.trc.2019.09.012
Brackstone, M., B. Waterson, M. McDonald (2009), 'Determinants of following headway in congested traffic', Transportation Research Part F: Traffic Psychology and Behaviour, 12(2), 131–142. DOI: https://doi.org/10.1016/j.trf.2008.09.003
Bridgelall, R., D. D. Tolliver (2020), 'A cognitive framework to plan for the future of transportation', Transportation Planning and Technology, 43(3), 237–252. DOI: https://doi.org/10.1080/03081060.2020.1735728
Brink, P. J., M. J. Wood (1998), Advanced Design in Nursing Research, (Thousand Oaks, USA: SAGE Publications). DOI: https://doi.org/10.4135/9781452204840
Brownell, C., A. Kornhauser (2014), 'A driverless alternative: Fleet size and cost requirements for a statewide autonomous taxi network in New Jersey', Transportation Research Record, 2416(1), 73–81. DOI: https://doi.org/10.3141/2416-09
Buckley, L., S.-A. Kaye, A. K. Pradhan (2018), 'A qualitative examination of drivers' responses to partially automated vehicles', Transportation Research Part F: Traffic Psychology and Behaviour, 56, 167–175. DOI: https://doi.org/10.1016/j.trf.2018.04.012
Cobb, D. P., H. Jashami, D. S. Hurwitz (2021), 'Bicyclists' behavioral and physiological responses to varying roadway conditions and bicycle infrastructure', Transportation Research Part F: Traffic Psychology and Behaviour, 80, 172–188. DOI: https://doi.org/10.1016/j.trf.2021.04.004
Fisher, D. L., M. Rizzo, J. Caird, J. D. Lee (2011), Handbook of Driving Simulation for Engineering, Medicine, and Psychology, (Boca Raton, USA: CRC Press). DOI: https://doi.org/10.1201/b10836
Fleskes, K., D. S. Hurwitz (2019), 'Influence of bicyclist presence on driver performance during automated vehicle take-over requests', Transportation Research Part F: Traffic Psychology and Behaviour, 64, 495–508. DOI: https://doi.org/10.1016/j.trf.2019.06.007
Girden, E. R. (1992), ANOVA: Repeated Measures, (Newbury Park, USA: SAGE Publications). DOI: https://doi.org/10.4135/9781412983419
Hedlund, J. (2017), 'Autonomous vehicles meet human drivers: Traffic safety issues for states', Governors Highway Safety Association.
iMotions, (2017), 'GSR R-Notebooks: Processing in iMotions and algorithms used', iMotions, Copenhagen.
KPMG, (2019), '2019 Autonomous Vehicles Readiness Index: Assessing countries’ preparedness for autonomous vehicles', KPMG Intenational.
Krogmeier, C., C. Mousas (2019), 'Human-virtual character interaction: Toward understanding the influence of haptic feedback', Computer Animation and Virtual Worlds, 30(3-4), e1883. DOI: https://doi.org/10.1002/cav.1883
Nothdurft, T., P. Hecker, S. Ohl, F. Saust, M. Maurer, A. Reschka, J. R. Böhmert (2011), 'Stadtpilot: First fully autonomous test drives in urban traffic', International IEEE Conference on Intelligent Transportation Systems, Washington, DC, USA, 5–7 October 2011. DOI: https://doi.org/10.1109/ITSC.2011.6082883
Oliveira, L., K. Proctor, C. G. Burns, S. Birrell (2019), 'Driving style: How should an automated vehicle behave?', Information, 10(6), 219. DOI: https://doi.org/10.3390/info10060219
Pettigrew, S., C. Worrall, Z. Talati, L. Fritschi, R. Norman (2019), 'Dimensions of attitudes to autonomous vehicles', Urban, Planning and Transport Research, 7(1), 19–33. DOI: https://doi.org/10.1080/21650020.2019.1604155
Ren, R., H. Li, T. Han, C. Tian, C. Zhang, J. Zhang, R. W. Proctor, Y. Chen, Y. Feng (2023), 'Vehicle crash simulations for safety: Introduction of connected and automated vehicles on the roadways', Accident Analysis & Prevention, 186, 107021. DOI: https://doi.org/10.1016/j.aap.2023.107021
Risto, M., M. H. Martens (2014), 'Driver headway choice: A comparison between driving simulator and real-road driving', Transportation Research Part F: Traffic Psychology and Behaviour, 25(Part A), 1–9. DOI: https://doi.org/10.1016/j.trf.2014.05.001
Shladover, S. E. (2017), 'Road vehicle automation: History, opportunities, and challenges', California PATH Program.
Swake, J., M. Jannat, M. Islam, D. S. Hurwitz (2013), 'Driver response to phase termination at signalized intersections: Are driving simulator results valid?', International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design, New York, NY, USA, 17–20 June 2013. DOI: https://doi.org/10.17077/drivingassessment.1501
Tapiro, H., A. Wyman, A. Borowsky, T. Petzoldt, X. Wang, D. S. Hurwitz (2022), 'Automated vehicle failure: The first pedestrian fatality and public perception', Transportation Research Record, 2676(8), 198–208. DOI: https://doi.org/10.1177/03611981221083297
Terkildsen, T., G. Makransky (2019), 'Measuring presence in video games: An investigation of the potential use of physiological measures as indicators of presence', Internation Journal of Human-Computer Studies, 126, 64–80. DOI: https://doi.org/10.1016/j.ijhcs.2019.02.006
Zimmermann, R., R. Wettach (2016), 'First step into visceral interaction with autonomous vehicles', International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Oldenburg, Germany, 24–27 September 2016. DOI: https://doi.org/10.1145/3122986.3122988
Zou, Z., S. Ergan (2019), 'A framework towards quantifying human restorativeness in virtual built environments', arXiv, 1902.05208.
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Copyright (c) 2025 Cadell Chand, Hisham Jashami, Haizhong Wang, David Hurwitz
This work is licensed under a Creative Commons Attribution 4.0 International License.
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University Transportation Centers
Grant numbers 69A3551747110
