Driving Risk Assessment Under the Effect of Alcohol Through an Eye Tracking System in Virtual Reality

  • Maria Rosaria De BlasiisEmail author
  • Chiara Ferrante
  • Valerio Veraldi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 969)


The issue of driving under the effect of alcohol is a matter of several studies in the field of road safety because today alcohol is widely diffused especially among very young people (age ranging between 18 and 25). Each year data provided by authorities are worrying, more than a third of the accidents registered in European countries are caused by alcohol. Italy is aligned with this trend; the ISS – National Institute of Health estimates that alcohol-related road accidents are equal to 30–35% of the total road accidents. Medical researches confirm that alcohol generates negative effects on driving, impairs the ability of perception, attention, processing and evaluation and it has negative effects on cognitive and motor skills. Therefore, the present research is developed in the field of a wider project research with the purpose to investigate and estimate the impact of alcohol on road safety to support awareness campaigns “Drink or Drive”. As demonstrated by findings of the previous study, alcohol has a significant impact on driving performances in terms of geometric, kinematic and dynamic measures. Trajectory, stopping and overtaking maneuvers were studied and a significant delay in reflexes, especially in stopping and overtaking maneuvers, that exposes drivers to high risk level, was calculated. In this research, the focus is on the drivers’ eye-movements that are recorded in the virtual reality driving experiment. To understand how much alcohol impairs attention and concentration in relation to the driving performances, these data are processed and two eye blinking measures (i.e. % blinking and blink rate) are analyzed A sample of 20 drivers were requested to drive the virtual reality-driving simulator situated in the LASS3 Virtual Reality Laboratory of University Research Centre for Road Safety. The route runs in extra-urban and urban areas, in order to study drivers’ behavior in different cases and subjecting drivers to different stimuli (i.e. pedestrian crossing, overtaking maneuver, sudden braking, etc.). The results are a comparison between the results of two conditions drunken and sober. Results show that alcohol affects attention and concentration increasing the absolute value of blinking and its rate. During the stopping and the overtaking maneuvers where driving measures show higher risk levels in drunkenness condition respect the to the sober one, eye measures show a reduction in blinking and frequency (in both conditions) on behalf of a more attention to the road.


Driver behaviour Alcohol effect Driving simulator Human Factor 


  1. 1.
    Burian, S.E., Liguori, A., Robinson, J.H.: Effects of alcohol on risk-taking during simulated driving. Hum. Psychopharmacol., 141–150 (2002).
  2. 2.
    European Trasport Safety Council and ANIA Fondazione per la Sicurezza Stradale, Comunicato stampa, Roma (2014)Google Scholar
  3. 3.
    Smith, R.C., Geller, E.S.: Field investigation of college student alcohol intoxication and return transportation from at-risk drinking locations. Transp. Res. Rec. J. Transp. Res. Board 2425, 67–73 (2014).
  4. 4.
    Christoforou, Z.: A priori evaluation of policy measures against alcohol-impaired driving: French case study. Transp. Res. Record J. Transp. Res. Board, 97–103 (2016).
  5. 5.
    Nuovo Codice della Strada - Decreto Legislativo 30 aprile 1992 n. 285Google Scholar
  6. 6.
    Gengo, F.M., Gabos, C., Straley, C., Manning, C.: The pharmacodynamics of ethanol: effects on performance and judgement. J. Clin. Pharmacol. 30, 748–754 (1990). Scholar
  7. 7.
    Irving, A., Jones, W.: Methods for testing impairment of driving due to drugs. Eur. J. Clin. Pharmacol. 43, 61–66 (1992). Scholar
  8. 8.
    West, R., Wilding, J., French, D., Kemp, R., Irving, A.: Effect of low and moderate doses of alcohol on driving hazard perception latency and driving speed. Addiction 88, 527–532 (1993). Scholar
  9. 9.
    Fromme, K., Katz, E., D’Amico, E.: Effects of alcohol intoxication on the perceived consequences of risk taking, Exp. Clin. Psychopharmacol. (1997)Google Scholar
  10. 10.
    Seitzinger, R., Fries, R., Qi, Y., Zhou, H.: A driving simulator study evaluating traffic sign mounting height for preventing wrong-way driving. In: Transportation Research Board 95th Annual Meeting, Washington DC, United States (2016)Google Scholar
  11. 11.
    Hongji, D., Zhao, X., Zhang, G., Rong, J.: Effect of different breath alcohol concentrations on driving performance in horizontal curves. Accid. Anal. Prev. (2014).
  12. 12.
    Christoforou, Z., Karlaftis, M.G., Yannis, G.: Effects of alcohol on speeding and road positioning of young - drivers driving simulator study. Transp. Res. Record J. Transp. Res. Board 2281, 32–42 (2012). Scholar
  13. 13.
    De Blasiis, M.R., Ferrante, C., Veraldi, V., Santilli, A.: Effects of alcohol on risk perception: a driving simulation study, Road Safety and Simulation RSS Proseedings, The Hague (2017)Google Scholar
  14. 14.
    Savage, S.W., Potter, D., Tatler, B.: Does preoccupation impair hazard perception? A simultaneous EEG and Eye tracking study. Transp. Res. Part F, 52–62 (2013).
  15. 15.
    Benedetto, S., Pedrotti, M., Minin, L., Baccino, T., Re, A., Montanari, R.: Driver workload and blink duration. Transp. Res. Part F 14, 199–208 (2011). Scholar
  16. 16.
    Stern, J.A., Boyer, D., Schroeder, D.: Blink rate: a possible measure of fatigue. Hum. Factors 36, 285–297 (1994)CrossRefGoogle Scholar
  17. 17.
    Wang, Y., Xin, M., Bai, H., Zhao, Y.: Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study. Traffic Inj. Prev. (2017).
  18. 18.
    Cinar, S., Acir, N.: Automatic removal of ocular artefacts in EEG signal by using independent component analysis and Chauvenet criterion. In: Medical Technologies National Conference, TIPTEKNO (2016)Google Scholar
  19. 19.
    Cuevas, A., Febrero, M., Fraiman, R.: An ANOVA test for functional data. Comput. Stat. Data Anal. (2004).
  20. 20.
    De Blasiis, M.R., Ferrante, C., Veraldi, V., Moschini, L.: Risk perception assessment using a driving simulator: a gender analysis. In: Road Safety and Simulation RSS Proseedings, The Hague (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Maria Rosaria De Blasiis
    • 1
    Email author
  • Chiara Ferrante
    • 1
  • Valerio Veraldi
    • 2
  1. 1.Engineering DepartmentRoma Tre UniversityRomeItaly
  2. 2.RISE - Research and Innovation for Sustainable Environment, Ltd.RomeItaly

Personalised recommendations