Eric J Fitzsimmons

Investigation of Violation Reduction at Intersection Approaches with Automated Red Light Running Enforcement Cameras in Clive, Iowa, Using a Cross-Sectional Analysis

Red light running causes more than 100,000 crashes and 1,000 fatalities annually and results in an estimated economic loss of over

Determining Vehicle Operating Speed and Lateral Position Along Horizontal Curves Using Linear Mixed-Effects Models

14 billion per year in the United States. Red light running is a significant safety issue facing communities which rarely have the resources to place additional law enforcement in the field. As a result, communities are increasingly turning to automated red light running camera-enforcement systems to address the problem. The effectiveness of red light running cameras in reducing the number of drivers who run the red light (violations) in an Iowa community was evaluated. The number of red light running violations at camera-enforced intersection approaches were compared to violations at approaches at intersections where cameras were not used within the same metropolitan area using a cross-sectional analysis. A Poisson lognormal regression was used to evaluate the effectiveness of the cameras in reducing violations. Results indicated that red light running cameras substantially reduced the number of violations at camera-enforced approaches as compared to control approaches.

Analyses of Vehicle Trajectories and Speed Profiles Along Horizontal Curves

Objective: Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes. Methods: For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of “risky” drivers. Results: Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves. Conclusions: Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.

Implications of Distracted Driving on Start-Up Lost Time for Dual Left-Turn Lanes

Vehicle speed and lane position are two of the many possible factors that lead to crashes on horizontal curves. Vehicle position and speed through horizontal curves are of great relevance to many areas of traffic engineering, including countermeasure design, design consistency, and policy. This article discusses the results of an exploratory analysis of vehicle trajectories and speed profiles at two horizontal curves located in central Iowa. The sites include an urban and rural curve. Data were collected at five stations within the horizontal curves in both directions of travel using pneumatic road tubes set up in a Z-configuration. Overall, vehicles were found to cut the horizontal curve in the inside and outside travel lanes. However, the trajectories were seen to be different at the two curve sites. Vehicle mean speed profiles indicated that the curve site selected for evaluation operate differently and are reflected in the speed profiles. Speed deviations of individual vehicles as they traversed the curve were evaluated. More vehicles were found to adjust their speeds and lateral position in the vicinity of the center of the curve, and then at the end of the horizontal curve.

Measuring Horizontal Curve Vehicle Trajectories and Speed Profiles: Pneumatic Road Tube and Video Methods

Previous research has found that distracted driving measurably increases driver response times to unanticipated roadway hazards. These instances are of particular consequence as they tend to be highly correlated with vehicle crashes resulting in property damage and/or injury. However, comparatively little attention has been allocated to quantifying the negative impacts of distracted driving on driver reaction to anticipated stimuli. This study empirically determined the impact of distracted driving on queue discharge rates at signalized intersections with protected left turn phases for dual left turn lanes. Observational studies were conducted at 11 intersection approaches at six signalized intersections in three states resulting in the observation of 844 distracted and 3,726 undistracted left turning drivers. A statistical model was developed for the startup lost time resulting from the average headways of the samples in each state. The difference in startup lost times between queues comprised entirely of distracted or undistracted drivers

Economic Impact of Closing Structurally Deficient or Functionally Obsolete Bridges on Very Low-Volume Roads

AbstractHorizontal curves present drivers with numerous tasks that, if not performed while approaching and negotiating the curve, may result in a roadway departure crash. A vehicle’s lateral position within the lane and its speed are two indicators of interest from safety and operational perspectives. These can and have been measured simultaneously at multiple locations along the curve. However, researchers face the challenge of collecting operational data while minimizing impacts on driver behavior, and developing robust, efficient, and accurate means to obtain the data. This paper presents the findings of a series of pilot studies on closed and open courses that investigated the effectiveness and accuracy of pneumatic road tubes and digital video cameras for collecting such data. Closed-course studies investigated a single data collection station setup, whereas an open-course study investigated multiple data collection stations on a horizontal curve. The data were reduced manually and automatically, and...

Value of confirmation lights and their unintended impact on driver compliance and deterrence to running a red light

The state of Kansas has approximately 25,464 bridges located on state, county, and city roadway networks. As of May 2012 approximately 1,229 bridges on very low-volume roads were determined to be structurally deficient and candidate structures to be potentially closed, replaced, or repaired. This study was designed to provide such critical information for county commissioners or practicing engineers as (a) where structurally deficient or functionally obsolete bridges on low-volume roads were located, (b) what distance was the shortest drivable detour if these bridges were to be closed, and (c) whether to recommend closing or to repair or replace the structurally deficient bridges on the basis of both potential detour length and average daily traffic (ADT). The results of the study indicated that many of the structurally deficient bridges on very low-volume roadways had detours of 2 mi or less, were steel bridges, and had ADT values of fewer than eight vehicles. On the basis of the analysis, bridge closure was recommended for a low-volume roadway with an ADT value less than eight and a detour length of less than 9 mi.

Evaluation of Gateway and Low-Cost Traffic-Calming Treatments for Major Routes in Small Rural Communities

In the United States, red light running (RLR) continues to be a safety concern for many communities with signalized intersections. In 2012, the Insurance Institute for Highway Safety reported that nationwide, RLR had resulted in 683 fatalities and 133,000 injury-related crashes. Confirmation lights have been deployed in many communities as a countermeasure to aid law enforcement in reducing RLR violations; however, the effectiveness of confirmation lights has not been well documented. This research study was conducted to determine the effectiveness of confirmation lights at signalized intersections for the purpose of reducing RLR violations. Confirmation lights were installed for the protected left-turn movements at two signalized intersections in Lawrence, Kansas. In addition to the two treatment sites, 11 comparison sites, including six spillover intersections and five control intersections, were studied. A before–after analysis was conducted with field-based violation data. Without changing the local, traditional police department–run RLR enforcement program during the study period, video data were collected before installation, and 1 month and 3 months after installation. A test of proportions found a statistically significant 42% reduction in left-turning RLR violations 3 months after the installation of confirmation lights at the treatment sites. An analysis of RLR time into red with chi-square tests indicated that the system was less effective in changing the time from the onset of red until the mean RLR violation occurred. Overall, the presence of the confirmation lights at the signalized intersection indicated effectiveness in both reducing the number of RLR violations and also changing driver behavior.