Automated Enforcement of Red-Light Running & Speeding Laws in Minnesota: Bridging Technology and Public Policy

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Automated Enforcement of Red-Light Running & Speeding Laws in Minnesota: Bridging Technology and Public Policy

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2009-10

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Center for Transportation Studies, University of Minnesota

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Report

Abstract

This report reviews the use of technology for automated enforcement of traffic laws around the world and across the United States, especially red-light running and speeding, with a focus on Minnesota. Automated enforcement to tag red-light runners and speeders is common internationally and domestically. The report reviews evidence and suggests how Minnesota can use automated enforcement to improve safety, cut deaths and injuries, and reduce the appalling annual cost of property damage due to motor vehicle crashes. Citizens of libertarian bent resent laws requiring that they protect themselves while allowing society to absorb extraordinary costs when they or others are injured or killed in traffic crashes. Others express fundamental resentment of “intrusive government” at all levels and the traffic rules governments impose. Thus, linking automated enforcement technology with effective and politically acceptable public policy presents genuine public safety and public-health challenges. Chapters summarize the high cost of crashes; problems and behaviors linked to red-light running and speeding; case studies of automated enforcement of traffic laws; the short-lived Minneapolis “Stop-on-Red” program; the yellow-light phase controversy; Minnesota litigation ending the Minneapolis program; diverse political cultures and debates across the U.S. concerning automated enforcement; and best practices for implementing automated enforcement legislation and programs. Five appendices summarize legal issues surrounding automated enforcement of traffic laws.

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Adams, John S.; Vandrasek, Barbara J.. (2009). Automated Enforcement of Red-Light Running & Speeding Laws in Minnesota: Bridging Technology and Public Policy. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/97666.

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