U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
This section of the Step-by-Step Guide provides information on: Federal funding options for supporting a Stop Red-Light Running program, grassroots fundraising, and obtaining in-kind donations from companies and organizations that support your program.
Before embarking on a Stop Red-Light Running campaign, it can be helpful to first complete an assessment of your both your signal system, and your community’s attitudes about red-light running and the red-light running problem itself. These “pre-program” assessments will give you a starting point from which to measure your results. You can gauge your community’s red-light running program by reviewing citation and crash data and by understanding the community’s awareness of, and attitudes toward, red-light running.
You can measure the number of citations issued and crashes resulting from:
These measurements can be taken before the program starts and then at appropriate intervals thereafter.
A red-light camera must work in harmony with the traffic signal at an intersection. It is therefore essential for traffic engineers to be involved in determining whether or not the exiting signal system at a particular intersection is compatible with red-light camera applications or if it needs to be modified. Research shows that yellow interval duration is a significant factor affecting the frequency of red-light running and that increasing yellow time to meet the needs of traffic can dramatically reduce red-light running. The following memo from the Associate Administrator, Office of Safety, FHWA to Division Administrators and Federal Lands Highway Division Engineers, provides guidance on determining yellow change intervals based on intersection characteristics to reduce red-light running.
National data is available online from the National Highway Traffic Safety Association site's Fatality Analysis Reporting System (FARS). FHWA calculates red-light running related fatalities by reviewing available data where:
Because the data must derived using the factors cited above (which are FARS features), you will need help from the experts when collecting State and/or local crash and citation data. You can obtain data on the number and severity of crashes associated with running red lights from your State and/or local law enforcement agency.
Your local law enforcement agency also can provide you with data on the number and type of citations issued in association with red-light running. Some police departments may not be able to define red-light running violations specifically, but can give you citation data on disregarding traffic signals (failure to yield, failure to stop, improper turn, etc.). If this is the case, use these numbers, but be sure you are consistent in recording the same type of information as you evaluate your success at later dates. It is extremely important to measure "apples to apples." Your statistics will have to withstand media scrutiny for accuracy. You can develop a simple matrix to record these statistics by agency and data type (i.e., crash and/or citation type).
When collecting data, be sure you understand your jurisdiction’s definition of signal noncompliance. In some areas, running a red light includes driving through a yellow light. Other areas provide a grace period to clear the intersection before calling it a violation. This distinction could greatly affect your compliance statistics.
Traffic statistics are not the only measurement that will aid your efforts. If you can find out what drivers in your area think about running red-lights—whether "everybody does it," how risky they perceive it to be, etc.—you can target your program's messages to address these perceptions. For instance, if the perceived risk of getting a traffic ticket for running a red-light is low, you can concentrate a large part of the program's efforts on enforcement. This guide provides information about two methods to determine public attitudes in your community toward running red lights: surveys and focus groups (see below for additional information on both).
Surveys, whether by telephone or face to face, are an effective way to gauge attitudes. They typically involve a relatively large number of structured interviews with a representative sample of the population being studied. In contrast, focus groups involve relatively few people (usually eight to ten people) are conducted face-to-face and allow much more flexibility in asking questions. The group is asked questions regarding the topic by an experienced facilitator who leads them through a discussion.
Surveys obtain a broad scan of information from many people, while focus groups obtain more insight from a few people. Both methods require an array of skills and should be designed and analyzed by experienced market research professionals to ensure statistical accuracy. Use your coalition and its contacts to access these people and put them in charge of your research efforts. This guide includes information on managing this type of research to assist in carrying out this type of attitudinal research.
Not only is it important to measure attitudes at the beginning of your program, but also over time. Conducting this type of research before your campaign can help you choose what to emphasize during the campaign and will also give you a baseline for evaluating the program.Conducting follow-up research (at least a survey) at the end of the program using the same questions can help you assess whether drivers’ attitudes and reported behaviors have changed in the right direction. Attitudinal change usually precedes behavior change, and the attitudinal research can be compared to the crash and citation statistics to further assess program success.
The following pages provide additional information, and sample materials, for conducting surveys and focus groups in a Stop Red-Light Running Campaign:
A study of 800 licensed drivers in United States ages 18 to 65 conducted by the Federal Highway Administration and the American Trauma Society in 1995 revealed some national attitudinal statistics that may help your local cause (the margin of error was ± 3.46):