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Publication Number: FHWA-HRT-05-048
Date: April 2005

Safety Evaluation of Red-Light Cameras

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Acknowledgments

This study was funded by the Federal Highway Administration and would not have been possible without the enthusiastic cooperation by officials in the study jurisdictions in assembling the database. These jurisdictions include: Baltimore, MD; Charlotte, NC; El Cajon, CA; Howard County, MD; Montgomery, MD; San Diego, CA; and San Francisco, CA. The fundamental research that led to some of the methodological ideas used in the study was funded under an operating grant to Bhagwant Persaud (Ryerson University) from the National Sciences and Engineering Research Council of Canada (NSERC). The photo on the cover of the document is used with permission from TRIMARC/Northrop Grumman Mission Systems.

References

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Other References

Breiman, L., R. Olshen, J. Freidman, and C. Stone. Classification and Decision Trees. Wadsworth International Group, Belmont, CA. 1984.

Butler, Pamela Crenshaw. A Quantifiable Measure of Effectiveness of Red Light Running Cameras at Treatment and Non-Treatment Sites, Washington, DC: Howard University Thesis, May 2001.

Feber, D. J., K.J. Crocker, and J.M. Feldmeier. "The AAA Michigan Road Improvement Demonstration Program: an Analysis of the Effectiveness of Using Safety Enhancements to Help Reduce Societal and Insurance Costs." Transportation Research Board, Washington, DC. 2000.

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[1] "Regression to the mean" is the statistical tendency for locations chosen because of high crash histories to have lower crash frequencies in subsequent years even without treatment.

[2] Spillover effect is the expected effect of RLCs on intersections other than the ones actually treated because of jurisdiction-wide publicity and the general public's lack of knowledge of where RLCs are installed.

[3] The KABCO severity scale is used by the investigating police officer on the scene to classify injury severity for occupants with five categories: K, killed; A, disabling injury; B, evident injury; C, possible injury; O, no apparent injury. (7) These definitions may vary slightly for different police agencies.

[4] A detailed discussion of "human capital" and "comprehensive" costs can be found in Blincoe, et al.(26) In summary, human capital costs include direct and indirect costs to individuals and society as a whole from the decline in the general health status of those injured in motor vehicle crashes. Components include medical and rehabilitation costs, emergency services costs, lost market productivity, lost household productivity, insurance administration, workplace costs, legal costs, travel delay costs, and property damage costs. Comprehensive costs include all these components plus additional costs associated with intangible consequences of crashes to individuals and families such as pain and suffering and loss of life. In studies of motor vehicle crashes, both types of costs are usually keyed to individual levels of injury severity measured on the AIS within an individual body part (because consequences can vary by severity within body part injured). AIS is specified by trained medical data coders, usually within a hospital context. Average human capital or comprehensive costs are often defined in reports for an eight-point injury scale based on the Maximum AIS score (MAIS) for an individual. Appendix A of Blincoe, et al., shows the average human capital cost ranges from approximately two-thirds of the comprehensive cost for a minor (MAIS 1) injury level to less than one-third the comprehensive cost for a fatality (i.e., $0.98 million versus $3.37 million, in Year 2000 dollars).(26)

[5] The KABCO severity scale is used by the investigating police officer on the scene to classify injury severity for occupants with five categories: K, killed; A, disabling injury; B, evident injury; C, possible injury; O, no apparent injury.(7) These definitions may vary slightly for different police agencies.

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