Sage Journals: Discover world-class research

Abstract

One path to significantly reducing traffic deaths is the implementation of automated vehicles. However, the proliferation of automation relies on public acceptance, and debiasing can be a useful approach to persuade the public of the safety benefits of automated vehicles. The research team surveyed 186 adults about their comfort level on drowsy driving, trust in automated vehicles, and whether they would trust an automated vehicle if they were falling asleep at the wheel. Increased age and drowsy driving comfort level predicted a lower level of overall trust in automated vehicles, while only age predicted degree of trust in automated vehicles when sleepy. Participants’ trust in automated vehicles increased when considering the risky circumstance of nodding off at the wheel. Identifying other cases in which drivers would trust automation is one key to de-biasing overconfidence in one’s driving and increasing public trust of automation in situations when automation may be superior.

Keywords

automation trust surface transportation judgment and decisionmaking survey drowsy driving

Get full access to this article

View all access options for this article.

References

AAA (2016) AAA fact sheet: Vehicle technology survey – Phase IIIB. Retrieved from: http://publicaffairsresources.aaa.biz/wp-content/uploads/2016/02/Automotive-Engineering-ADAS-Survey-Fact-Sheet-FINAL-3.pdf

AAA. (2017). AAA fact sheet: Vehicle technology survey – Phase IIIB. Retrieved from: https://newsroom.aaa.com/download/10067/

AAA. (2018). AAA: American Trust in Autonomous Vehicles Slips. Retrieved from: https://newsroom.aaa.com/2018/05/aaa-american-trust-autonomous-vehicles-slips/

Bergdahl

(2005). Sex differences in attitudes toward driving: A survey. The Social Science Journal, 42(4), 595-601.

Choi

J. K.

Y.G.

(2015). Investigating the importance of trust on adopting an autonomous vehicle. International Journal of Human-Computer Interaction, 31, 692-702.

Dunning

Heath

Suls

J. M.

(2004). Flawed self-assessment: Implications for health, education, and the workplace. Psychological Science in the Public Interest, 5, 69–106.

Fan

A. Z.

Grant

B. F.

Ruan

W. J.

Huang

Chou

S. P.

(2019). Drinking and driving among adults in the United States: Results from the 2012–2013 national epidemiologic survey on alcohol and related conditions-III. Accident Analysis & Prevention, 125, 49-55.

Fildes

Keall

Bos

Lie

Page

Pastor

… Tingvall

(2015). Effectiveness of low speed autonomous emergency braking in real-world rear-end crashes. Accident Analysis & Prevention, 81, 24-29.

Ingre

Åkerstedt

Peters

Anund

Kecklund

(2006). Subjective sleepiness, simulated driving performance and blink duration: examining individual differences. Journal of Sleep Research, 15, 47-53.

10.

Kalra

Paddock

S. M.

(2016). Driving to Safety: How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?. Santa Monica, CA: RAND Corporation. Retrieved from: https://www.rand.org/pubs/research_reports/RR1478.html

11.

Lee

C. J.

Beck

K. H.

(2019). Mediational impact of perceived risk on drowsy driving intention and willingness in university students. Transportation Research Part F: Traffic Psychology and Behavior, 63, 165-173.

12.

Lee

J. D.

See

K. A.

(2004). Trust in automation: Designing for appropriate reliance. Human factors, 46(1), 50-80.

13.

MacLean

A. W.

Davies

D. R.

Thiele

(2003). The hazards and prevention of driving while sleepy. Sleep Medicine Reviews, 7, 507-521.

14.

Matthews

M. L.

Moran

A. R.

(1986). Age differences in male drivers' perception of accident risk: The role of perceived driving ability. Accident Analysis & Prevention, 18(4), 299-313.

15.

Fisher

Morris

N.L.

(2018). Possible Futures in Semi-Automonous Vehicles. Presentation. Young Driver Subcommittee Mid-Year Meeting. Woods Hole, MA.

16.

Johns

M. W.

(1991). A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep, 14(6), 540-545.

17.

Kaur

Rampersad

(2018). Trust in driverless cars: Investigating key factors influencing the adoption of driverless cars. Journal of Engineering and Technology Management, 48, 87-96.

18.

König

Neumayr

(2017). Users’ resistances towards radical innovations: The case of the self-driving car. Transportation Research Part F: Traffic Psychology and Behavior, 44, 42-52.

19.

McKenna

F. P.

(1993). It won't happen to me: Unrealistic optimism or illusion of control? British Journal of Psychology, 84(1), 39-50.

20.

National Center for Statistics and Analysis. (2017, October). Drowsy Driving 2015 (Crash•Stats Brief Statistical Summary. Report No. DOT HS 812 446). Washington, DC: National Highway Traffic Safety Administration.

21.

NHTSA (2019). Early Estimates of Motor Vehicle Traffic Fatalities in 2018. (DOT HS 812 749). US Department of Transportation, Washington, D.C. Retrieved from: https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812749

22.

Payre

Cestac

Delhomme

(2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation Research Part F: Traffic Psychology and Behaviour, 27, 252-263.

23.

Peterson

Douma

Morris

(2017). Addressing key concerns regarding automated speed enforcement via interactive survey. Transportation Research Record, 2660, 66-73.

24.

Ratcliffe

Burd

Holder

Fields

(2016). Defining rural at the US Census Bureau. American Community Survey and Geography Brief, 1, 8.

25.

Rahman

M. M.

Deb

Strawderman

Burch

Smith

(2019). How the older population perceives self-driving vehicles. Transportation Research Part F, 65, 242-257.

26.

Rottenstreich

Tversky

(1997). Unpacking, repacking, and anchoring: Advances in support theory. Psychological Review, 104(2), 406-415.

27.

Saleh

Chevrel

Claveau

Lafay

J. F.

Mars

(2013). Shared steering control between a driver and an automation: Stability in the presence of driver behavior uncertainty. IEEE Transactions on Intelligent Transportation Systems, 14, 974-983.

28.

Singh

(2015, February). Critical reasons for crashes investigated in the National Motor Vehicle Crash Causation Survey. (Traffic Safety Facts Crash•Stats. Report No. DOT HS 812 115). Washington, DC: National Highway Traffic Safety Administration

29.

Svenson

(1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47(2), 143-148.

30.

Tefft

B. C.

(2014). Prevalence of Motor Vehicle Crashes Involving Drowsy Drivers, United States, 2009 – 2013 (November 2014). Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.684.6347&rep=rep1&type=pdf

31.

Tversky

Koehler

D.J.

(1994). Support theory: A nonextensional representation of subjective probability. Psychological Review, 101, 547-567.

32.

U.S. Census Bureau (2019, July 1). Quick Facts- United States: Population Estimates. Retrieved from: census.gov/quickfacts/fact/table/US

33.

Watson

N. F.

Morgenthaler

Chervin

Carden

Kirsch

Kristo

… Weaver

(2015). Confronting drowsy driving: the American Academy of Sleep Medicine perspective. Journal of Clinical Sleep Medicine, 11, 1335-1336.

34.

Weinstein

N. D.

(1988). The precaution adoption process. Health Psychology, 7(4), 355.

35.

Wheaton

A.G.

Chapman

D.P.

Presley-Cantrell

L.R.

Croft

J.B.

Roehler

D.R.

(2013). Drowsy driving – 19 states and the District of Columbia, 2009-2010. (pp. 1033-1037). Atlanta, GA: Centers for Disease Control.

36.

World Health Organization (2018). Global status report on road safety 2018. Report retrieved from: https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/

37.

Wohleber

R. W.

Matthews

(2016). Multiple facets of overconfidence: Implications for driving safety. Transportation Research Part F: Traffic Psychology and Behaviour, 43, 265-278.

38.

Zhang

Tao

Zhang

Lin

Zhang

(2019). The roles of initial trust and perceived risk in public’s acceptance of automated vehicles. Transportation Research Part C: Emerging Technologies, 98, 207-220.

Trust in Automated Vehicles under Normal and Drowsy Driving Conditions

Abstract

Keywords

Get full access to this article

References