Key Takeaways
- Black cars are involved in 12% more fatal crashes than white cars according to a 10-year Australian study.
- In the US, black vehicles have a 47% higher at-fault crash risk during the day per Monash analysis.
- UK data shows black cars 20% more likely to be in accidents in low light conditions.
- Blue cars 5% higher accident involvement than neutrals per studies.
- Yellow cars lowest crash risk at 16.9% below black in Monash.
- Green cars 8% overrepresented UK accidents.
- Red cars 7% higher crash risk overall per Australian research.
- US red vehicles 20% more at-fault daytime crashes.
- UK: red cars 10% overrepresented in accidents.
- Silver cars 11% lower crash rates than dark colors per Monash.
- US silver vehicles 15% safer daytime at-fault.
- UK silver 9% under in serious accidents.
- White cars have 12% lower crash risk than average fleet colors per Monash study.
- White vehicles safest in US with 10% fewer at-fault accidents daytime.
- UK stats: white cars 11% less likely in serious crashes.
Across studies, black cars face consistently higher crash risk than white, especially at night, in urban areas, and in rain.
Black Cars
Black Cars Interpretation
Other Colors
Other Colors Interpretation
Red Cars
Red Cars Interpretation
Silver/Grey Cars
Silver/Grey Cars Interpretation
White Cars
White Cars Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Henrik Dahl. (2026, February 13). Car Colour Accident Statistics. Gitnux. https://gitnux.org/car-colour-accident-statistics
Henrik Dahl. "Car Colour Accident Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/car-colour-accident-statistics.
Henrik Dahl. 2026. "Car Colour Accident Statistics." Gitnux. https://gitnux.org/car-colour-accident-statistics.
Sources & References
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monash.edu
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trafikstyrelsen.dk
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cdc.gov
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adac.de
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nhtsa.gov
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rac.co.uk
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dmv.ca.gov
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lvm.fi
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progressive.com
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infrastructure.gov.au
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nicb.org
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statefarm.com
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etsc.eu
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vegvesen.no
- Reference 23FLEETNEWSfleetnews.co.uk
fleetnews.co.uk
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npa.go.jp
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nt.gov.au
- Reference 26TRANSPORTATIONtransportation.gov
transportation.gov
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- Reference 32ESURANCEesurance.com
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- Reference 33LIBERTYMUTUALlibertymutual.com
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