Relationship Between Car Color and Car Accident on the Basis of Chromatic Aberration

  • Seong-yoon Shin
  • Yang-Won Rhee
  • Dai-Hyun Jang
  • Sangwon Lee
  • Hyun-Chang Lee
  • Chan Yong Jin
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 235)


In choosing a car, we consider car performance, design, price, and safety as the most important things without reference to accident occurrence probability. We first studied on the concepts of advancing color and receding color as well as relationships with car accidents. Consequently, advancing color causes less accidents since the color looks closer than it actually is. And receding color causes more accidents since the color looks farther than it actually is. And we classified car colors into seven ones such as black, white, blue, green, silver, red, and yellow. Each representative color includes its detailed colors corresponding to its domain. We also proposed accident occurrence probabilities ordered by each color. The descending order is blue, green, white, red, black, silver, and yellow. The rate of relationship with 74.64 % is high than that of disrelationship with 25.36 %.


Car accident Advanced color Receded color Chromatic aberration 


  1. 1.
    Newstead S, D’Elia A (2007) An investigation into the relationship between vehicle colour and crash risk, accident research centre. report no. 263, Monash University, ClaytonGoogle Scholar
  2. 2.
    Furness S, Connor J, Robinson E, Norton R, Ameratunga S, Jackson R (2003) Car colour and risk of car crash injury: population based case control study. BMJ 327:20–27Google Scholar
  3. 3.
    Owusu-Ansah SO (2010) Investigation of the relationship between vehicle color and safety. University of Dayton, DaytonGoogle Scholar
  4. 4.
    Chang H, Yeh T (2006) Risk factors to driver fatalities in single-vehicle crashes: comparisons between non-motorcycle drivers and motorcyclists. J Transp Eng 132:227–236CrossRefGoogle Scholar
  5. 5.
    Harb R, Radwan E, Yan X, Pande A, Abdel-Aty M (2008) Freeway work-zone crash identification using multiple and conditional logistic regression. J Transp Eng 134:203–214CrossRefGoogle Scholar
  6. 6.
    Houston DJ, Richardson LE (2002) Traffic safety and switch to a primary seatbelt law: the California experience. Accid Anal Prev 34:743–751CrossRefGoogle Scholar
  7. 7.
    Koushki PA, Bustan BA, Kartam N (2003) Impact of safety belt use on road accident injury and injury type in Kuwait. Accid Anal Prev 35:237–241CrossRefGoogle Scholar
  8. 8.
    Gross F, Jovanis PP, Eccles K, Chen K-Y (2009) Safety effects of lane and shoulder combinations on rural, two-lane, undivided roads.Vol FHWA-HRT-09-031, US Department of TransportationGoogle Scholar
  9. 9.
    Baum S (2000) Drinking driving a social problem: comparing the attitudes and knowledge of drink driving offenders and the general community. Accid Anal Prev 32:689–694CrossRefGoogle Scholar
  10. 10.
    Braver ER, Preusser DF, Williams AF, Weinstein HB (1996) Major types of fatal crashes between large trucks and cars. Insurance Institute for Highway Safety, ArlingtonGoogle Scholar
  11. 11.
    Neeley GW, Richardson LE (2009) The effect of state regulations on truck-crash fatalities. Am J Public Health 99:408–415CrossRefGoogle Scholar
  12. 12.
    FEMA (2009) Emergency vehicle visibility and conspicuity study. US Department of Homeland Security, EmmitsburgGoogle Scholar
  13. 13.
    Anders RL (2000) On-road investigation of fluorescent sign colors to improve conspicuity. Virginia Polytechnic Institute and State University, BlacksburgGoogle Scholar
  14. 14.
    Hawkins HG, Carlson PJ, Elmquist M (2000) Evaluation of fluorescent orange signs. Texas Transportation Institute Report, Vol 0-2962-SGoogle Scholar
  15. 15.
    Gates TJ, Hawkins HG (2004) Effect of higher-conspicuity warning and regulatory signs on driver behavior. Texas Transportation Institute Report, Vol 0-4271-SGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Seong-yoon Shin
    • 1
  • Yang-Won Rhee
    • 1
  • Dai-Hyun Jang
    • 1
  • Sangwon Lee
    • 2
  • Hyun-Chang Lee
    • 2
  • Chan Yong Jin
    • 2
  1. 1.Department of Computer Information EngineeringKunsan National UniversityGunsanKorea
  2. 2.Division of Information and Electronic Commerce (Institute of Information Science)Wonkwang UniversityIksanKorea

Personalised recommendations