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Automated Enforcement for Speeding and Red Light Running (2012)

Chapter: Chapter 4 - Conclusions and Recommendations

« Previous: Chapter 3 - Guidelines for Automated Enforcement
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Suggested Citation:"Chapter 4 - Conclusions and Recommendations." National Academies of Sciences, Engineering, and Medicine. 2012. Automated Enforcement for Speeding and Red Light Running. Washington, DC: The National Academies Press. doi: 10.17226/22716.
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Suggested Citation:"Chapter 4 - Conclusions and Recommendations." National Academies of Sciences, Engineering, and Medicine. 2012. Automated Enforcement for Speeding and Red Light Running. Washington, DC: The National Academies Press. doi: 10.17226/22716.
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Suggested Citation:"Chapter 4 - Conclusions and Recommendations." National Academies of Sciences, Engineering, and Medicine. 2012. Automated Enforcement for Speeding and Red Light Running. Washington, DC: The National Academies Press. doi: 10.17226/22716.
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Suggested Citation:"Chapter 4 - Conclusions and Recommendations." National Academies of Sciences, Engineering, and Medicine. 2012. Automated Enforcement for Speeding and Red Light Running. Washington, DC: The National Academies Press. doi: 10.17226/22716.
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Page 27

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24 C h a p t e r 4 The two objectives of this project were to identify current and suggested practices and les- sons learned from current and past automated enforcement programs and to develop a set of guidelines to assist agencies in implementing and operating successful automated enforcement programs. The following sections present a discussion of the gaps in the available knowledge, recommendations, and conclusions. Gaps in Data During the process of collecting information and reviewing best practices, various gaps in the available knowledge on speed enforcement and red light enforcement emerged. It is recom- mended that these gaps be filled in subsequent research efforts. Speed Enforcement Gaps Influence Area What distance upstream or downstream of an enforced site would speed enforcement be expected to reduce collisions? This information is required to estimate the expected crash reduc- tion when calculating expected benefits as well as to determine the required number of camera units to enforce all desired locations. Available information is vague. General Deterrence Effects Is there a general deterrence effect and, if so, what is its magnitude? Automated speed enforce- ment is intended to impact driver behavior in general, leading to fewer crashes far away from the enforced locations and on non-enforced roadways in the same jurisdiction. The existence and mag- nitude of this general deterrence effect on collisions is still to be definitively established, although at least one study has found a positive systemwide impact for red light cameras and others have studied the impacts of automated speed enforcement on speed at non-enforced locations. Crash Migration In contrast to general deterrence, is there a possibility of crash migration? Reduced speeds near an enforced location may yield a safety benefit, but there may be compensatory increases in speeds further away resulting in increased crash frequencies at these locations. The existence and/or magnitude of possible crash migration has not been demonstrated. Covert Versus Conspicuous Enforcement Are there advantages to the uncertainty of a covert (i.e., hidden) radar unit over conspicu- ous enforcement in influencing driver behavior and reducing crashes? This question remains unanswered in the United States. Conclusions and Recommendations

Conclusions and recommendations 25 Fixed Versus Mobile Enforcement Are there differences in effects on driver behavior and crash effects for fixed versus mobile enforcement? That is, if the speed enforcement cameras are installed at fixed locations within a community, is the effect the same as if the speed enforcement cameras were part of a mobile sys- tem that could be used at numerous locations? Similar to the question of covert versus conspicu- ous enforcement, with fixed speed enforcement, the public knows exactly where the cameras are, whereas mobile enforcement introduces uncertainty to drivers. Which one has a greater impact on driver behavior and crash reduction is unknown. Enforcement Intensity and Rotation How does enforcement intensity and rotation influence the effect of the program and how can these be optimized? The enforcement intensity refers to the number of hours of enforcement to achieve results and how long the benefits last until enforcement is again required. The rota- tion of mobile speed enforcement is dependent on these requirements. When speed cameras are deployed at any location, the violation rate is expected to show a decreasing effect until it reaches a lower threshold or “steady-state” level. During this adaptive learning phase, drivers learn over time that the automated speed enforcement is there and decrease their tendency to speed. If the automated enforcement remains constant for a sufficient period of time, the violation rate will reach a lower steady-state level. Conversely, when the speed cameras are removed, drivers will learn eventually that there is no enforcement and their likelihood of speeding will increase. This time period is associated with maladaptive learning and is typically known as the “time halo” of traffic enforcement. Further research is required to measure the lengths of the adaptive and maladaptive learning phases. Number of Enforcement Units Required How can one determine the number of speed enforcement units required for a jurisdiction given its size and road network? This number will depend on a number of factors, including those discussed above: Is a general deterrence effect the goal versus enforcing specific locations that exceed some crash threshold? What is the expected influence area of a single unit? What is the required enforcement intensity for a single location, i.e., hours of operation? What is the enforcement density required for general deterrence if it exists? Effects for Specific Crash Types What are the effects for specific crash types affected and what influences these effects? Most studies on the effects of speed enforcement have looked at effects on all crash types, likely at least partly due to the difficulty of identifying those crashes truly relating to speeding in many crash databases. A more efficient site selection procedure and accurate cost-benefit estimates would result from estimating the safety effects on true target crash types. Site Selection How can sites best be selected to maximize the use of limited resources to reduce the most crashes, fatalities, and injuries that result from those crashes? The literature review did not reveal any sound methodologies used to select sites for automated speed enforcement. To resolve this question, there is a need for a procedure to estimate the anticipated reduction in crashes by speed cameras at individual locations. The procedure should consider differential impacts on different crash types, crash severities, and site-specific expected crash frequencies. Resolution of other gaps identified would be useful in defining such a methodology. Recidivism What practices exist to combat recidivism rates? Neither the literature review nor the survey of agencies found ways to reduce recidivism rates. This is a gap for both speed enforcement and red light cameras.

26 automated enforcement for Speeding and red Light running Red Light Camera Gaps General Deterrence Effects Is there a general deterrence effect, and if so, what is its magnitude? Red light camera programs are intended to impact driver behavior in general and lead to fewer collisions at non-enforced locations. Although some studies have demonstrated spillover effects for violations and crashes, the existence and magnitude of this general deterrence effect is still to be definitively understood and quantified. Mitigation of Negative Impacts How can the negative impacts of red light cameras be mitigated? The observed increases in rear-end crashes may be caused by some drivers driving more conservatively as a result of the RLC program, and others not, resulting in rear-end crashes when a following driver expected a lead vehicle to proceed through an intersection. If red light camera programs are truly effec- tive at changing driver behavior in general, then these negative effects may go away over time. A related question is whether adjustments to signal change intervals that typically accompany red light camera installation may contribute to any negative impacts by extending the dilemma zone. Impacts of Signal Timing How do signal timing parameters, particularly cycle length and coordination, influence the safety effects of red light cameras? Knowledge on the effects of cycle length is limited. Cycle length is needed both to provide some measure of the number of red phases (and thus the number of opportunities for red light running) in a given time period, but also because longer red phases might “induce” more red light running. With respect to signal coordination, the issue is whether the treated signal approach is part of a set of coordinated signals that lead to queuing of vehicles. Camera Rotation Schedules How does camera rotation influence the effect of the program and how can this be optimized? When enforcement is in place, the violation rate is expected to show a decreasing effect until it reaches a lower threshold or “steady-state” level. During this adaptive learning phase, drivers learn over time that the enforcement is there and decrease their likelihood of running a red light. If the enforcement remains constant for a sufficient period of time, the violation rate will reach a lower steady-state level. Conversely, when the camera is removed and tickets are not issued to violators, drivers will learn eventually that there is no enforcement and their likelihood of running a red light will increase. This time period is associated with maladaptive learning and is typically known as the “time halo” of traffic enforcement. Further research is required to measure the lengths of the adaptive and maladaptive learning phases. Site Selection How can sites best be selected to maximize the use of limited resources to reduce the most crashes, as well as the fatalities and injuries that result from those crashes? To resolve this ques- tion, there is a need for a procedure to estimate the anticipated reduction in crashes by red light cameras at individual locations. The procedure should consider differential impacts on different crash types, crash severities, and site-specific expected crash frequencies. Front- Versus Rear-Facing Cameras Which of these two enforcement approaches has a greater affect on driver behavior and in reducing crashes? Some jurisdictions photograph the rear plate of the vehicle and apply the fine to the vehicle owner; others photograph the front plate and driver and ticket the offending driver with the ability to assign demerit points. Whether overcoming the privacy and practical issues of front-facing cameras is worthwhile is unknown.

Conclusions and recommendations 27 Recommendations When used appropriately, automated enforcement can be a valuable tool for enforcement of speed and red light running. Agencies seeking to implement an automated enforcement program should learn from the experiences of other agencies and, in particular, should consider using these guidelines to structure their program. It is recommended that, at a minimum, a program should have the following qualities: • Open to the public — The public must have knowledge, awareness, and assurance of the systems. Transparency and accessibility is important to the success of the program and general public acceptance. • Motivated by safety — Properly identifying that either a red light running or speed problem is causing crashes is critical to establishing a program. If a program is not motivated by safety, it will not succeed. • Strong enabling legislation — Enabling legislation should be tailored to the local commu- nity needs and existing legislative constraints. The legislation should provide authority for operating an automated traffic enforcement program without attempting to specify every component of a program. • Repeatable — A well-run automated enforcement program should be repeatable. This includes all steps of the program, from initiation to site selection and evaluation. A program with well-documented, repeatable processes will help gain the trust and respect of the public. It will also encourage neighboring jurisdictions to follow the same protocol. • Monitored and evaluated — The program should be monitored on a regular basis to evaluate performance and operation. Regular monitoring can help determine if the goals of the program are being met, ensure that the systems are operating correctly, and identify any conditions that may have changed since initiation of enforcement that would require a modification to a system or the program. Automated enforcement should only be used at locations as a supplement to traditional engi- neering, enforcement, and education countermeasures and should never replace these mea- sures. Officers should continue to provide traditional enforcement at locations with automated enforcement. Any deficiencies in the design or operation of the locations should be corrected before automated enforcement is put into use. Locations selected for automated enforcement should be designed and operated with a solid engineering foundation and be appropriate for local conditions. For automated speed enforcement locations, the program director should ensure that the speed limit is clearly communicated to approaching drivers, set based on an engineering study, and appropriate for the location. For automated red light enforcement locations, the pro- gram director should ensure that all traffic control devices are visible and conspicuous and that the traffic signal timing, particularly the yellow interval, is appropriate for the local conditions. The guidelines developed from this research effort should be used for implementing and oper- ating an automated enforcement program, either for red light running or speed violations. The intended audiences for this research are public agencies primarily responsible for the safety of the roadways and intersections. This includes, but is not limited to, enforcement agencies, high- way engineers, legislators, and elected officials. As this report shows, several well-run programs exist. Four of these programs are highlighted in the case studies provided herein as Appendix H. Agencies can learn from these jurisdictions and use their noteworthy practices when implement- ing their own program. As programs expand and additional research is conducted, the guidelines should be updated.

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TRB’s National Cooperative Highway Research Program (NCHRP) Report 729: Automated Enforcement for Speeding and Red Light Running includes guidelines designed to help transportation agencies start-up and operate automated enforcement programs to improve highway safety by reducing speeding and red light running.

Appendices A through G to NCHRP Report 729 are available in electronic versions only. The appendices are not available in the PDF or print version of the report.

TR News 292: May-June 2014 includes an article about the report.

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