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Journal Article

Citation

Smith DM, McFadden J, Passetti K. Transp. Res. Rec. 2000; 1734: 29-37.

Copyright

(Copyright © 2000, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/1734-05

PMID

unavailable

Abstract

Automated enforcement involves the use of image capture technology to monitor and enforce traffic control laws, regulations, or restrictions. The increase in aggressive driving and the high percentage of crashes that occur at intersections led to the development and implementation of automated enforcement technology to detect and cite motorists who enter a signalized intersection in violation of the red phase. The primary focus of this research was to establish how well the automated enforcement system achieves its principal objective: reducing crashes and red light running (RLR) violations at signalized intersections. Evaluations of automated enforcement programs at three locations in the United States were performed as part of this research. The automated enforcement programs in New York City; Polk County, Florida; and Howard County, Maryland, were reviewed as a part of this research. Some of the major findings from this research are as follows: (a) In 1997 there were over 789,000 crashes at signalized intersections, of which 97,000 were attributed to RLR; (b) In 1997, 961 deaths were attributed to RLR; (c) Electronic enforcement is a proven technique used globally to curb RLR violations and crashes; (d) A synthesis of automated RLR enforcement programs in the United States showed promising results; (e) New York City has the oldest automated RLR enforcement program in the United States and has yielded a 20 percent reduction in violations since 1993; (f) Although additional data quantifying the effect of automated RLR enforcement campaigns are needed for Polk and Howard counties, preliminary findings are promising; (g) A 10-step process for successful implementation of an automated RLR enforcement program was illustrated.

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