Transportation Deployment Casebook/2015/Red Light Cameras in the US

 Implementation of Red Light Cameras in the United States Over Time 

Technology Overview
Beginning in the 1990s, red light cameras have been deployed across the United States in an effort to provide motorists with motivation to obey traffic signals and thus increase safety. The cameras are triggered when sensors in a road along the camera's approach indicate when a vehicle opts to accelerate rather than decelerate when the respective approach's traffic signal is about to turn red. A photo of the violating vehicle is taken and the vehicle information recorded is used to issue a citation (New York City Department of Transportation, 2014). By discouraging red light runners, transportation regulatory bodies hope to decrease severe accidents at signals and promote safety in addition to reducing accident cost. Agencies in the United States utilize them either to hold a driver or a registered owner responsible for passing through an intersection when the respective movement’s signal indication is red. In order to hold a registered owner responsible, a camera need only capture vehicle identifying information. Identifying driver responsibility requires photographic evidence of the driver of the car as well as the car itself. The latter method allows a registered vehicle owner to prove he or she is not responsible for the violation and opt for dismissal of the citation. Though the Federal Highway Administration recommends the use of red light cameras for promoting safety, states are in charge of regulating the technology and determining whether or not it will be utilized (Federal Highway Administration, 2005).

Red light running produces a significant safety risk. The action of running a red light is considered a “human factor” in the National Highway Traffic Safety Administration’s “Haddon Matrix” for traffic accident injury mitigation. Human factors are generally thought of as occurring pre-event and thus avoidable. An estimated ninety percent of crashes occur due to human factors. While cars have become safer over time, human behavior has not. Thus motivation has existed and continues to exist for further regulation of driver behavior (Adams & VanDrasek, 2009).

Before Implementation
Prior to the implementation of red light cameras at intersections, alternative red light running mitigation techniques had been tested. These strategies are still used today to determine if a need exists for a red light camera at an intersection. To begin, engineering improvements are made. These improvements can include timing adjustments such as lengthening yellow times or providing all-red clearance intervals, installation of warning beacons ahead of intersections to alert drivers to impending light changes, coordinating signals and other measures to improve flow, and altering intersection geometry. The next strategy is to inform the public of the dangers of red light running as a part of an informative campaign with warnings about the emotional and economic impacts of accidents, particularly those that are avoidable. The last step in red light running mitigation prior to implementation of automated enforcement technologies is the use of officers to manually enforce laws. Random officer enforcement can help by negating the ability of drivers to predict where and when an officer will be monitoring an intersection while targeted enforcement can help at problem locations. Though the presence of an officer can discourage red light running, once an officer moves to reprimand an offender, cars moving through an intersection return to being unmonitored (Adams & VanDrasek, 2009).

Technology Invention
Red light camera technology has been available for much longer than it has been utilized in the United States. In 1958, Maurice Gatsonides developed a speed monitoring device, the gatsometer, and formed the company Gatsometer to market, produce, and sell it. The company’s first purchaser was the Netherlands. Gatsonides continued developing and innovating technologies, and the first red light camera was brought to the market in 1965. The first red light cameras relied on tubes laid across a road to signal the camera when a violator approached. By the time this technology was developed, the company was exporting its products to countries outside of Europe including South Africa and Australia, but it would be several decades before the technology reached the United States. In 1997, shortly after initial deployment in the United States in 1994, the digital red light camera was developed (Gatso USA, 2015).

Early Development (1993-1997)
Despite the long period of time it took red light cameras to reach the United States after their development, the technology became widely deployed over a short period of time. This is certainly due, in part, to success in early development. By 1996 (just two years after deployment), New York City had implemented 18 cameras and spent approximately $15 million. As a result, 360,000 tickets had been issued based on photographs taken with the cameras, bringing in $14 million in revenue. Beyond the monetary success the program incurred, the city also saw a 25 percent decrease in tickets issued in the first year of operation (Row, 1996).

Arizona became the second of the United States to implement automated red light enforcement in 1996. The policy implemented by Arizona differs from that of New York in that the driver, not the registered vehicle owner, is considered responsible for the violation. This policy required red light cameras to be positioned such that they are able to capture an image of the driver of the vehicle in addition to the vehicle itself. This method, and the method used in New York City, set the models for enforcement options in future implementation in different states (Kraus & Quiroga, 2002).

Role of Policy in Birthing Phase
New York’s adoption of policy legalizing red light cameras was pivotal to their implementation in the city in 1994. This was the first use of the technology in the United States, though it had been subject to research and development for over ten years by the time of implementation. A 1982 accident caused by a red light runner that led to the death of an 18-month old child spurred the debate regarding use of the cameras. Though objections were raised against the surveillance aspect of the technology, the state of New York passed legislation to allow the use of red light cameras in 1988. Following legalization, it took several years for New York City to develop and approve an appropriate plan. To take into account the discomfort drivers felt in having their picture taken, and to avoid any civil rights infringement, the cameras were installed at angles allowing them to only take photos of the rear of an offending vehicle, not the individual driver (Row, 1996).

The vital role of policy in introduction of red light cameras continued to be evident after their first installment in New York City. Since its inception, the technology has been fought through lawsuits against red light camera systems as a whole and appeals to individual citations issued. Adams and VanDresek point out the necessity of legal backing for red light camera technology in their report on red light cameras in Minnesota, “Among the most challenging obstacles to installing an automated enforcement program is establishing a solid basis in state law, the absence of which led to the suspension of the Minneapolis PhotoCop program in 2007” (Adams & VanDrasek, 2009). Without legal backing, the argument can be made and won that public agencies do not have the right to issue citations based on remote evidence not initially collected by a person.

Growth Phase (1998-2007)
The spread of red light camera technology use across the United States has resulted in public agencies using different strategies to maintain and operate red light cameras in use. In contrast to New York City’s initial approach to handle all operations in house, public agencies began outsourcing tasks to private contractors. Public agencies are still supposed to handle project planning and management, plan and installation checks, and the final decision to issue a citation. Aspects such as public information programs, equipment ownership, design and installation, operation and maintenance, citation data processing, and violator inquiries might be handled by either the public agency or a private contractor (Adams & VanDrasek, 2009).

With the change in responsibilities from public to private, communication with the general populace in regards to how income from citations is handled is paramount. The idea that private companies can collect profits through reprimanding citizens who break the law is incredibly problematic. It pervades opinion articles on red light cameras as a defense for the dissolution of red light camera programs, though such articles tend to lack citations of where the behavior is particularly seen. For example, “The company typically collects the fine and returns some share of the money to the municipality. It’s a little like privateering” (Last, 2011). In their support of returning automated enforcement to Minnesota, Adams and VanDrasek acknowledge, “It is inappropriate for vendor compensation to be based on the number of citations issued, just as it is inappropriate for a private contractor to determine the locations of automated-enforcement installations or the terms of operation because of the appearance of conflict of interest” (Adams & VanDrasek, 2009).

Situations in which practice does not align with policy are often resolved in court. In a 2001 case in California, the defendant accused a municipality of not operating their photo red light program in accordance with the California Vehicle Code. The court found that the municipality was indeed not properly running the program as a private contractor was handling the work all but entirely (Adams & VanDrasek, 2009). While the California Vehicle code does allow for red light camera systems to be contracted out, it does place certain limitations on the duties a contractor can perform and requires a governmental agency to oversee these duties (California Deparment of Motor Vehicles, 2011).

Maturity (2008-Present)
Implementation of red light cameras has not been seen in states without programs in recent years (see figure 1 of technology life cycle). While it cannot be said with certainty why this is, a lack of political motivation to implement such programs can be speculated as the reasoning. Though studies have shown red light cameras do generally decrease right angle crashes, public resistance to the technology still remains (Høye, 2013). Perhaps drive for further adoption of the technology could be created with educational campaigns to communicate the safety benefits of red light cameras and clarification of policies surrounding the role of private contractors in operation.

Though red light cameras have presented a viable method for encouraging driver safety, they will likely soon be obsolete. That is, with the implementation of connected or autonomous vehicles, drivers will no longer have the option of running red lights as the decision will no longer be theirs, but the software of the vehicle.

Methods
To illustrate how red light camera use in the United States has changed over time, a mathematical model was developed from data representing growth of the industry. Data was acquired from the 2012 Report 729 of the National Cooperative Highway Research Program (NCHRP) on Automated Enforcement for Speed and Red Light Running. The results of a survey of automated enforcement implementation amongst municipalities taken by the NCHRP are included in the appendices of the report. A link to these appendices can be found below. Included in the information collected is the year in which a municipality implemented red light camera enforcement. The earliest year reported in a specific state by one of its municipalities surveyed was taken as the year in which the state as a whole implemented the technology. Two states with red light cameras were found to be excluded from the report, New York and Delaware. Implementation dates for these states were found on their state websites. Links to these data sources can also be found below.

Once data was acquired, it was plotted in Microsoft Excel. A model of the data was estimated using a three-parameter logistic function:

S(t) = K/[1+exp(-b(t-t0)]

Where,

S(t) is the number of states that have implemented red light cameras

K is the maximum value of the function (several values were tested and 21 was determined the best match to the data using an R-Squared goodness of fit test)

b is a coefficient that was fitted as a part of the modelling process, found to be 0.341.

t0 is the time at which rate of change goes from increasing to decreasing (an inflection point), found to be 2002.5.

t is time as plotted

Figures
The final model is shown in figure 1. Its equation is:

S(t) = 21/[1+exp(-0.341(t-2002.5))]



Data was taken from the following sources:

• https://www.deldot.gov/information/red_light/

• http://www.nyc.gov/html/dot/downloads/pdf/2014-nyc-red-light-camera-program.pdf

• http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_729Appendices.pdf

References

Adams, J. S., & VanDrasek, B. J. (2009). Automated Enforcement of Red-Light Running & Speeding Laws in Minnesota: Bridging Technology and Public Policy. Minneapolis: Center for Transportation Studies University of Minnesota.

California Department of Motor Vehicles. (2011). V C Section 21455.5 Traffic Signal Automated Enforcement Photographic Records. Retrieved November 10, 2015, from CA.gov: https://www.dmv.ca.gov/portal/dmv/?1dmy&urile=wcm:path:/dmv_content_en/dmv/pubs/vctop/vc/d11/c2/a3/21455.5

Federal Highway Administration. (2005). Red Light Camera Systems: Operational Guidelines. United States Department of Transportation.

Gatso USA. (2015). History. Retrieved November 9, 2015, from Gatso USA: http://www.gatso-usa.com/about/history

Høye, A. (2013). Still red light for red light cameras? An update. Accident Analysis and Prevention.

Kraus, E., & Quiroga, C. (2002). Legislative Issues Related to Automated Enforcement of Red Light Running. Transoportation Research Board Record.

Last, J. V. (2011, August 1). Rolling Back the Nanny State. Retrieved November 10, 2015, from the weekly Standard: http://www.weeklystandard.com/keyword/red_light-cameras

New York City Department of Transporation. (2014). New York City Red Light Camera Program Review. New York City: New York City Department of Transportation.

Row, H. (1996, July). Red Light District. CIO, p. 116.