Citation

Ho TH, Chong JK, Xia X. Proc. Natl. Acad. Sci. U. S. A. 2017; 114(12): 3074-3078.

Affiliation

Department of Decision Sciences and Managerial Economics, Chinese University of Hong Kong Business School, Chinese University of Hong Kong, Shatin, NT, Hong Kong.

Copyright

(Copyright © 2017, National Academy of Sciences)

DOI

10.1073/pnas.1612551114

PMID

28265081

Abstract

Is there a link between the color of a taxi and how many accidents it has? An analysis of 36 mo of detailed taxi, driver, and accident data (comprising millions of data points) from the largest taxi company in Singapore suggests that there is an explicit link. Yellow taxis had 6.1 fewer accidents per 1,000 taxis per month than blue taxis, a 9% reduction in accident probability. We rule out driver difference as an explanatory variable and empirically show that because yellow taxis are more noticeable than blue taxis-especially when in front of another vehicle, and in street lighting-other drivers can better avoid hitting them, directly reducing the accident rate. This finding can play a significant role when choosing colors for public transportation and may save lives as well as millions of dollars.

Language: en

Keywords

car color; data science; road safety; sensory perception; transportation science