How Do Drivers Behave in a Highly Automated Car?
Open accessAbstract
This paper outlines the results of a driving simulator study conducted for the European CityMobil project, which was designed to investigate the effect of a highly automated driving scenario on driver behaviour. Drivers’ response to a number of ‘critical’ scenarios was compared in manual driving with that in automated driving. Drivers were in full control of the vehicle and its manoeuvres in the manual driving condition, whilst control of the vehicle was transferred to an ‘automated system’ in the automated driving condition. Automated driving involved the engagement of lateral and longitudinal controllers, which kept the vehicle in the centre of the lane and at a speed of 40 mph, respectively. Drivers were required to regain control of the driving task if the automated system was unable to handle a critical situation. An auditory alarm forewarned drivers of an imminent collision in such critical situations. Drivers’ response to all critical events was found to be much later in the automated driving condition, compared to manual driving. This is thought to be because drivers’ situation awareness was reduced during automated driving, with response only produced after drivers heard the alarm. Alternatively, drivers may have relied too heavily on the system, waiting for the auditory alarm before responding in a critical situation. These results suggest that action must be taken when implementing fully automated driving to ensure that the driver is kept in the loop at all times and is able to respond in time and appropriately during critical situations.
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Human beings quickly cease to pay attention to-or even to perceive-features of their environment that are not relevant to the tasks in which they are engaged.
“Human beings quickly cease to pay attention to - or even to perceive - features of their environment that are not relevant to the tasks in which they are engaged”
From When human beings are like drunk robots: Driverless vehicles, ethics, and the future of transport (2017) · cites this paper as Merat and Jamson, 2009
The Conclusions (page not available) report slower anticipation of traffic events during automated driving and suggest that driver underload may have reduced awareness, although excessive trust in the system is another possible explanation. This supports a narrower point about attention in automated driving, not the general claim that people quickly stop attending to, or perceiving, environmental features irrelevant to their tasks. (LLM, conf=0.83)
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Research works printed but not linked: 3
- Hancock, P.A. & Parasuraman, R. (1992). Human Factors and safety in the design of Intelligent Vehicle-Highway Systems (IVHS). Journal of Safety Research, 23, 181-198.
- Moray, N., Inagaki, T., & Itoh, M. (2000). Situation adaptive automation, trust and self- confidence in fault management of time-critical tasks. Journal of Experimental Psychology: Applied, 6, 44-58.
- Seppelt, B.D. & Lee, J.D. (2007). Making adaptive cruise control (ACC) limits visible. International Journal of Human Computer Studies,65, 192-205.
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When human beings are like drunk robots: Driverless vehicles, ethics, and the future of transport
Sparrow, R., & Howard, M. (2017) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2017.04.014 · Cited by 182 · see citing works
- Authors
- Merat, N., & Jamson, A. H.
- Affiliations
- University of Leeds (GB)
- ORCID
- Merat, Natasha
- Venue
- Driving Assessment Conference 2009
- Published
- 2009-06-25
- OpenAlex
- W1490945078
- Cited by
- 109
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 6 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 11 · 2019: 15 · 2018: 11 · 2017: 13 · 2016: 10 · 2015: 12 · 2014: 5 · 2013: 2 · 2012: 2
- FWCI
- 2.50
- Type
- conference paper
- Language
- en
- Open access
- green
- ir.uiowa.edu
- Locations
- International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design (Driving Assessment Conference) (publishedVersion)
- Iowa Research Online (University of Iowa) (submittedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Keywords
- highly automated driving, driver behavior, situational awareness, driver reaction time, longitudinal and lateral control, driver takeover, auditory alerts, driver-in-the-loop
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