This section provides a list of some of the papers that have utilized the data acquired from the experiment described in this chapter. The following papers should be cited when using the experiment design or the data provided with this chapter.

  • 1. Almahasneh H, Chooi W-T, Kamel N, Malik AS. Deep in thought while driving: an EEG study on drivers’ cognitive distraction. Transp Res Part FTraffic Psychol Behav. 2014;26:218-226.
  • 2. Almahasneh H, Kamel N, Walter N, Malik AS. r-principal subspace for driver cognitive state classification. In: Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE; 2015, pp. 4118-4121.


This chapter provides the details of the experiment design available in the papers mentioned in Section 12.5 and in the PhD thesis of Mr. Hossam Almahasneh, which is available at Universiti Teknologi PETRONAS.


  • 1. Stutts JC,Association AA. The Role of Driver Distraction in Traffic Crashes.Washington, DC: AAA Foundation for Traffic Safety; 2001.
  • 2. Dingus TA, Klauer S, Neale V, et al. The 100-car naturalistic driving study, Phase II-results of the 100-car field experiment; 2006.
  • 3. Young K, Regan M, Hammer M. Driver distraction: a review of the literature. Distracted Driv. 2007:379-405.
  • 4. Engstrom J, Johansson E, Ostlund J. Effects of visual and cognitive load in real and simulated motorway driving. Transp Res Part FTraffic Psychol Behav. 2005;8(2):97-120.
  • 5. Strayer DL, Cooper JM, Turrill J, Coleman J, Medeiros-Ward N, Biondi F. Measuring cognitive distraction in the automobile; 2013.
  • 6. Harbluk JL, Noy YI, Eizenman M. The impact of cognitive distraction on driver visual behaviour and vehicle control; 2002.
  • 7. Amin HU, Malik AS, Kamel N, Hussain M. A novel approach based on data redundancy for feature extraction of EEG signals. Brain Topogr. 2016;29(2):207-217.
  • 8. Amin HU, Malik AS, Ahmad RF, et al. Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques. Australas Phys Eng Sci Med. 2015;38(1):139-149.
  • 9. Knoll PM.The use of displays in automotive applications./ Soc InfDisp.1997 ;5(3): 165-172.
  • 10. White C, Fern L, Caird J, et al. The Effects of Dvd Modality on Drivers’ performance.

Paper presented at: Proceedings of the 37th Annual Conference of the Association of Canadian Ergonomists; 2006.

  • 11. Stavrinos D, Jones JL, Garner AA, et al. Impact of distracted driving on safety and traffic flow. Accid Anal Prev. 2013;61:63-70.
  • 12. Sumila M. Evaluation of the drivers’ distraction caused by dashboard MMI interface.

Paper presented at: International Conference on Transport Systems Telematics; 2014.

13. Pfleging B, Schneegass S, Schmidt A. Multimodal interaction in the car: combining speech and gestures on the steering wheel. Paper presented at: Proceedings of the 4th

International Conference on Automotive User Interfaces and Interactive Vehicular Applications; 2012.

  • 14. Redelmeier DA, Tibshirani RJ. Association between cellular-telephone calls and motor vehicle collisions. N Engl J Med. 1997;336(7):453-458.
  • 15. Wilson FA, Stimpson JP. Trends in fatalities from distracted driving in the United States, 1999 to 2008. Am J Public Health. 2010;100(11):2213-2219.
  • 16. Nelson E, Atchley P, Little TD. The effects of perception of risk and importance of answering and initiating a cellular phone call while driving. Accid Anal Prev. 2009;41(3):438-444.
  • 17. Klauer SG, Guo F, Simons-Morton BG, Ouimet MC, Lee SE, Dingus TA. Distracted driving and risk of road crashes among novice and experienced drivers. N Engl J Med. 2014;370(1):54-59.
  • 18. Nemme HE, White KM. Texting while driving: Psychosocial influences on young people’s texting intentions and behaviour. Accid Anal Prev. 2010;42(4):1257-1265.
  • 19. Farmer CM, Braitman KA, Lund AK. Cell phone use while driving and attributable crash risk. Traffic Inj Prev. 2010;11(5):466-470.
  • 20. Petridou E, Moustaki M. Human factors in the causation of road traffic crashes. Eur J Epidemiol. 2000;16(9):819-826.
  • 21. Perrow C. Normal Accidents: Living with High Risk Technologies. Princeton, NJ: Princeton University Press; 2011.
  • 22. Rudin-Brown CM, Parker HA. Behavioural adaptation to adaptive cruise control (ACC): implications for preventive strategies. Transp Res Part F Traffic Psychol Behav. 2004;7(2):59-76.
  • 23. Almahasneh H, Chooi W-T, Kamel N, Malik AS. Deep in thought while driving: An EEG study on drivers’ cognitive distraction. Transp Res Part F Traffic Psychol Behav. 2014;26:218-226.
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