Abstract

 


 



Attributes Affecting Preferences for Traffic Safety Safety Camera Programs


Lindsey M. Higgins


California State Polytechnic University, San Luis Obispo

W. Douglass Shaw


Texas A&M University

Aklesso Egbendewe Mondzozo


Michigan State University

May 1, 2011

Accident Analysis and Prevention, Vol. 43, pp. 1042-48, May 2011

Abstract:     
With just a few notable exceptions, research supports the concept that red light cameras (RLCs) improve safety. However, many communities that have implemented RLC programs have faced a firestorm of public opinion associated with the use of RLCS, with many communities having to remove the cameras. What makes or breaks a red light camera program? Because of the experimental design process, stated choice is recognized as a tool that can resemble a laboratory experiment for the public policy arena. In this research, a stated choice model was developed and used to explore public preferences for a RLC program through an internet survey and a convenience sample drawn from a typical college town. The results suggest while independently the opposite is true, that when there is an increase in both the fine for violators and the number of cameras together (i.e., the interaction of these two) there is a perceived public safety gain. The interacted variable positively increases utility from the selected RLCS program we analyzed and could be key in generating public support for RLC programs. The results suggest some important deterrence theory implications for improving accident prevention through the use of RLC programs that are designed to avoid unnecessary public scrutiny.

Keywords: Red Light Cameras, Stated Choice Experiment, Transportation Safety

JEL Classification: R40

Accepted Paper Series


Date posted: April 19, 2012  

Suggested Citation

Higgins, Lindsey M., Shaw, W. Douglass and Mondzozo, Aklesso Egbendewe, Attributes Affecting Preferences for Traffic Safety Safety Camera Programs (May 1, 2011). Accident Analysis and Prevention, Vol. 43, pp. 1042-48, May 2011. Available at SSRN: http://ssrn.com/abstract=2042118

Contact Information

Lindsey M. Higgins
California State Polytechnic University, San Luis Obispo ( email )
San Luis Obispo, CA 93407
United States
W. Douglass Shaw (Contact Author)
Texas A&M University (TAMU) ( email )
Department of Statistics
College Station, TX 77843-4353
United States
Aklesso Egbendewe Mondzozo
Michigan State University ( email )
East Lansing, MI 48824-1122
United States
Feedback to SSRN (Beta)


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