Blue Light, What Should I do? Red Light, 2002

The Iowa State Patrol appreciates your assistance and compliance with these guidelines and laws to ensure the safety of the public and Iowa law enforcement.

Evaluating the Effectiveness of Red Light Running Camera Enforcement in Cedar Rapids and Developing Guidelines For Selection and use of Red Light Running Countermeasures, Midwest Transportation Consortium, Final Report November 2011.

Red light running (RLR) is a problem in the US that has resulted in 165,000 injuries and 907 fatalities annually. In Iowa, RLR-related crashes make up 24.5 percent of all crashes and account for 31.7 percent of fatal and major injury crashes at signalized intersections. RLR crashes are a safety concern due to the increased likelihood of injury compared to other types of crashes. One tool used to combat red light running is automated enforcement in the form of RLR cameras. Automated enforcement, while effective, is often controversial. Cedar Rapids, Iowa installed RLR and speeding cameras at seven intersections across the city. The intersections were chosen based on crash rates and whether cameras could feasibly be placed at the intersection approaches. The cameras were placed starting in February 2010 with the last one becoming operational in December 2010. An analysis of the effect of the cameras on safety at these intersections was determined prudent in helping to justify the installation and effectiveness of the cameras. The objective of this research was to assess the safety effectiveness of the RLR program that has been implemented in Cedar Rapids. This was accomplished by analyzing data to determine changes in the following metrics:  Reductions in red light violation rates based on overall changes, time of day changes, and changes by lane  Effectiveness of the cameras over time  Time in which those running the red light enter the intersection  Changes in the average headway between vehicles entering the intersection

Evaluating the Effectiveness of Red Light Running Camera Enforcement in Cedar Rapids and Developing Guidelines for Selection and Use of Red Light Running Countermeasures Final Report, November 2011

Red light running (RLR) is a problem in the US that has resulted in 165,000 injuries and 907 fatalities annually. In Iowa, RLR-related crashes make up 24.5 percent of all crashes and account for 31.7 percent of fatal and major injury crashes at signalized intersections. RLR crashes are a safety concern due to the increased likelihood of injury compared to other types of crashes. One tool used to combat red light running is automated enforcement in the form of RLR cameras. Automated enforcement, while effective, is often controversial. Cedar Rapids, Iowa installed RLR and speeding cameras at seven intersections across the city. The intersections were chosen based on crash rates and whether cameras could feasibly be placed at the intersection approaches. The cameras were placed starting in February 2010 with the last one becoming operational in December 2010. An analysis of the effect of the cameras on safety at these intersections was determined prudent in helping to justify the installation and effectiveness of the cameras. The objective of this research was to assess the safety effectiveness of the RLR program that has been implemented in Cedar Rapids. This was accomplished by analyzing data to determine changes in the following metrics:  Reductions in red light violation rates based on overall changes, time of day changes, and changes by lane  Effectiveness of the cameras over time  Time in which those running the red light enter the intersection  Changes in the average headway between vehicles entering the intersection

Toolbox of Countermeasures to Reduce Red Light Running Final Report, April 2012

Red light running (RLR) is a problem in the US that has resulted in 165,000 injuries and 907 fatalities annually. In Iowa, RLR-related crashes make up 24.5 percent of all crashes and account for 31.7 percent of fatal and major injury crashes at signalized intersections. RLR crashes are a safety concern due to the increased likelihood of injury compared to other types of crashes. The research team developed this toolbox for practitioners to address RLR crashes. The Four Es—Engineering, Enforcement, Education, and Emergency Response—should be used together to address RLR problems. However, this toolbox focuses on engineering, enforcement, and education solutions. The toolbox has two major parts:  Guidelines to identify problem intersections and the causes of RLR at intersections  Roadway-based and enforcement countermeasures for RLR

Red Light Running in Iowa, Jaunary 2001

Crashes related to red light running account for more than 800 deaths and thousands of injuries each year in the United States. Many states and local jurisdictions have undertaken studies and enacted programs in reaction to this major transportation safety concern. This research study examined the scope of this phenomenon in Iowa, reviewed red light running reduction studies and programs nationwide, and proposed countermeasures to address significant violation problems.

Report on a special investigation of the New Hampton Municipal Light Plant for the period January 1, 2001 through May 31, 2012

Report on a special investigation of the New Hampton Municipal Light Plant for the period January 1, 2001 through May 31, 2012

Report on a special investigation of the Coggon Municipal Light Plant for the period July 1, 2004 through August 27, 2012

Report on a special investigation of the Coggon Municipal Light Plant for the period July 1, 2004 through August 27, 2012

Evaluation of the Confirmation Light System at Signalized Intersections in Medium to Large Iowa Communities to Reduce Red Light Running Violations”, TR-657, 2015

Red light running continues to be a serious safety concern for many communities in the United States. The Federal Highway Administration reported that in 2011, red light running accounted for 676 fatalities nationwide. Red light running crashes at a signalized intersections are more serious, especially in high speed corridors where speeds are above 35 mph. Many communities have invested in red light countermeasures including low-cost strategies (e.g. signal backplates, targeted enforcement, signal timing adjustments and improvement with signage) to high-cost strategies (e.g. automated enforcement and intersection geometric improvements). This research study investigated intersection confirmation lights as a low-cost strategy to reduce red light running violations. Two intersections in Altoona and Waterloo, Iowa were equipped with confirmation lights which targeted the through and left turning movements. Confirmation lights enable a single police officer to monitor a specific lane of traffic downstream of the intersection. A before-after analysis was conducted in which a change in red light running violations prior to- and 1 and 3 months after installation were evaluated. A test of proportions was used to determine if the change in red light running violation rates were statistically significant at the 90 and 95 percent levels of confidence. The two treatment intersections were then compared to the changes of red light running violation rates at spillover intersections (directly adjacent to the treatment intersections) and control intersections. The results of the analysis indicated a 10 percent reduction of red light running violations in Altoona and a 299 percent increase in Waterloo at the treatment locations. Finally, the research team investigated the time into red for each observed red light running violation. The analysis indicated that many of the violations occurred less than one second into the red phase and that most of the violation occurred during or shortly after the all-red phase.

The Effectiveness of Iowa's Automated Red Light Running Enforcement Programs, 2007

The Federal Highway Administration estimates that red light running causes more than 100,000 crashes and 1,000 fatalities annually and results in an estimated economic loss of over $14 billion per year in the United States. In Iowa alone, a statewide analysis of red light running crashes, using crash data from 2001 to 2006, indicates that an average of 1,682 red light running crashes occur at signalized intersections every year. As a result, red light running poses a significant safety issue for communities. Communities rarely have the resources to place additional law enforcement in the field to combat the problem and they are increasingly using automated red light running camera-enforcement systems at signalized intersections. In Iowa, three communities currently use camera enforcement since 2004. These communities include Davenport, Council Bluffs, and Clive. As communities across the United States attempt to address red light running, a number of communities have implemented red light running camera enforcement programs. This report examines the red light running programs in Iowa and summarizes results of analyses to evaluate the effectiveness of such cameras.

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.

Red Light Running in Iowa: The Scope, Impact, and Possible Implications, 2000

This research study, a cooperative effort between the Iowa Department of Transportation and the Center for Transportation Research and Education at Iowa State University, reviewed red light running reduction studies and programs nationwide, examined the scope of this phenomenon in Iowa, and proposed countermeasures to address significant violation problems.

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.