In a recent study of inspection reports, design documents and other data to evaluate the safety performance of bridge barriers, investigators found that the most commonly used barrier designs meet newer safety requirements and keep Minnesota drivers safe.Continue reading Assessing Bridge Barriers for Today’s Vehicle Needs
How well do the stop lines at stop-controlled intersections actually work as a safety feature? Through an extensive safety study and a before-after field observation, a recent Minnesota Local Road Research Board study showed that the assumed safety effects of stop lines as a means of influencing driver behavior are not well supported by the evidence.Continue reading How Well Do Stop Lines Work as a Safety Feature?
Overweight and oversize vehicles can accelerate pavement damage, increasing the cost of maintenance and rehabilitation of road infrastructure networks.Continue reading New Project: Economic Benefits of Truck Weight and Safety Enforcement Improvements
A new guidebook published by the Minnesota Local Road Research Board offers a uniform approach and practical methods for selecting locations and the right treatment for uncontrolled pedestrian crosswalks in Minnesota.
MnDOT construction projects require tons of hot mix asphalt each year, with over 188 road and bridge projects in the 2020 construction season alone.
Historically, plant mixed asphalt has been weighed, tracked and paid for with computer-generated paper tickets. Paper ticketing isn’t an ideal process for a variety of reasons—on-site ticket collection poses safety risks, tickets can be easily lost, and data must be tabulated manually, just to name a few.Continue reading Asphalt Delivery Tracking Goes Digital with Some 2020 Construction Projects
A new research study has shown that few landowners know about MnDOT’s snow fence program, its benefits to community safety and mobility, and incentives to install snow fences. Following community meetings and surveys in four regions of Minnesota, researchers identified promising promotional methods for the snow fence program, the constraints landowners face in adopting snow fences, and incentives and assistance to improve snow fence adoption. Project results will guide MnDOT’s efforts to expand the use of snow fences around the stateContinue reading Promoting Snow Fence Adoption in Minnesota
A two-year research project underway in the City of St. Paul is already improving pedestrian safety and driver behavior by applying lessons learned from a national award-winning pedestrian traffic study. The city began using the practices last fall with the “Stop for Me” campaign, and driver yield rates have already gone up by 9 percent.
Each year, dozens of Saint Paul pedestrians legally crossing the street are struck by vehicles driven by motorists who fail to stop. In 2015, 40 pedestrians died in Minnesota after being hit by a motor vehicle; 900 were injured. In 2017, there were 192 vehicle-pedestrian crashes in Saint Paul, three of which proved deadly.
Pedestrian fatalities and injuries represent a growing percentage of traffic fatalities and injuries nationwide. For example, pedestrian fatalities comprised 10.9% of all traffic deaths nationwide in 2004, but 14.5% in 2013.
A recent study supported by the National Highway Traffic Safety Administration demonstrated that driver behavior can be changed on a city-wide basis. The introduction of highly-visible pedestrian right-of-way enforcement in Gainesville, Florida increased driver yield rates for pedestrians by 22% to 30%.
University of Minnesota researchers are charged with reviewing the City of St. Paul’s efforts to improve pedestrian safety and investigate whether a program similar to the one in Gainesville can change driver yielding for pedestrians and speed compliance. The activities in St. Paul are being planned together with city traffic engineers and enforcement officers and will include various educational, engineering and enforcement countermeasures and media campaigns.
Last fall, St. Paul began the “Stop for Me” campaign, which enforces pedestrian laws, increases driver and pedestrian education and works towards enhanced signage and other changes to crosswalks around the city.
On June 25, the St. Paul Police Department began the second phase of the campaign by ticketing drivers who fail to stop for pedestrians at crosswalks.
Additionally, police officers are ticketing drivers for “endangerment” if they pass a vehicle that is stopped for a pedestrian at a crosswalk. This citation leads to a mandatory court appearance for the driver.
Weekly stopping percentages can be viewed at eight intersections across the city from now until the end of fall.
Watch for new developments on this project (expected end date of August 2019) here. Another MnDOT study is looking at pedestrian traffic safety in rural and tribal communities. Other Minnesota research on pedestrian travel can be found at MnDOT.gov/research.
MnDOT recently entered into a contract with the University of Minnesota (UMN) to complete a research project to keep wind from damaging rural intersection conflict warning signs (RICWS) and other digital message signs (DMS).
The project is titled “Understanding and Mitigating the Dynamic Behavior of RICWS and DMS Under Wind Loading.” Lauren Linderman, assistant professor at UMN’s Department of Civil, Environmental and Geo-Engineering, will serve as the principal investigator. Jihshya Lin of MnDOT will serve as technical liaison.
“This project will find out the behavior of the DMS and RICWS under AASHTO defined design loads and develop the retrofitting system to avoid the experienced problems that will improve the public safety, reduce the maintenance cost and minimize impact to the traffic,” Lin said.
RICWS have exhibited excessive swaying under wind loads, leading to safety concerns regarding failure of the support structure at the base. It is believed the heavy weight of these signs has brought the frequency range of these systems too close to that of the wind excitations. There is a need to investigate the wind-induced dynamic effects on these sign structures and to propose modifications to the systems to reduce the likelihood of failure. There is also interest in investigating the dynamic behavior of the DMS, particularly the loads on the friction connection.
This research project involves a field investigation to determine the structural performance of these two types of sign structures. Laboratory tests using a towing tank facility and a wind tunnel will be performed on scaled models and opportunely modified models to improve performance and minimize unsteady loads.
The outcome of this project is expected to develop an understanding of the RICWS and DMS sign structures and to provide modifications to improve the structural performance of the RICWS sign structures while maintaining the crashworthy requirements. The results will help to ensure the uninterrupted service of these sign structures, which are important to public safety.
- Task 1A: Development of Field Instrumentation Plan and Instrumentation Purchase
- Task 1B: Experimental Determination of Load Effects and Dynamic Characteristics of Post Mounted DMS in Field
- Task 2A: Development of Numerical Models to Investigate Post Mounted DMS Sign Demands and Fatigue
- Task 2B: Validation of Numerical Models to Investigate Post Mounted DMS Sign Demands and Fatigue
- Task 3A: Investigation of Design Loads and Relevant Fatigue Considerations for DMS
- Task 3B: Analysis of Design Loads and Anticipated Fatigue Life of DMS
- Task 4: Experimental Determination of Dynamic Characteristics of RICWS in Field
- Task 5: Development and Validation of Numerical Models to Investigate RICWS Signs
- Task 6: Numerical and Experimental Investigation of Drag and Vortex Shedding Characteristics of RICWS Signs Using Scaled Models
- Task 7: Numerical and Small-Scale Experimental Investigation of Modifications to RICWS Sign Panel to Reduce Effects of Vortex Shedding
- Task 8: Numerical and Analytical Investigation of Noncommercial Means to Damp Motion of RICWS Blankout Sign Structure
- Task 9A: Research Benefits and Implementation Steps Initial Memorandum
- Task 9B: Research Benefits and Develop Implementation Steps
- Task 10: Compile Report, Technical Advisory Panel Review and Revisions
- Task 11: Editorial Review and Publication of Final Report
The project is scheduled to be completed in March 2019.
Researchers studied driving behavior at four multilane roundabouts to better understand the relationship between traffic control designs and driver errors. Data collected showed that certain traffic control changes decreased turn violations but failed to eliminate yield violations. Researchers were unable to identify long-term solutions for improving roundabout design and signage, and recommended further research to improve the overall safety and mobility of multilane roundabouts.
“Even though the study did not provide a silver bullet on how to prevent crashes at multilane roundabouts, it did create an efficient tool to analyze and quantify driving behavior data,” said Joe Gustafson, Traffic Engineer, Washington County Public Works.
“This study has advanced our knowledge in multilane roundabout safety and is one step closer to providing much needed improvements to roundabout design guidance,” said John Hourdos, Director, Minnesota Traffic Observatory, University of Minnesota.
What Was the Need?
Roundabouts have been shown to improve overall in-tersection safety compared to traditional traffic signals. However, noninjury crashes are sometimes more frequent on multilane roundabouts than on single-lane roundabouts due in part to driver confusion. Common driver errors such as failing to yield and turning violations on multilane roundabouts have contributed to an increase in noninjury crashes.
Given the benefits of improved mobility, traffic throughput and injury reduction of multilane roundabouts, reducing the noninjury crash rate at multilane roundabouts is important to facilitating their use by Minnesota cities and counties. Identifying solutions to reduce common driving violations would be more sustainable than the current practice of converting multilane roundabouts back to single-lane roundabouts.
In a previous study on a two-lane roundabout in Richfield, Minnesota, researchers demonstrated that traffic control changes could reduce some of these driver errors. However, more data was needed to support study results. Understanding driver behavior and improving traffic control devices are key factors in designing safer multilane roundabouts.
What Was Our Goal?
With limited research on modern multilane roundabouts, the Minnesota Traffic Observatory sought to collect more data to evaluate the correlation between traffic control design features and collisions. Instead of conducting manual observations, researchers used an innovative video analysis tool to collect and process recorded videos of driving behaviors at test sites. Based on the analysis, they attempted to identify driver behaviors and error rates to help reduce noninjury crashes at multilane roundabouts.
What Did We Do?
The research team selected four multilane roundabouts in Minnesota — two in Mankato, one in Lakeville and one in St. Cloud — to observe undesirable driving maneuvers. At each roundabout site, researchers mounted video cameras at key locations to record one to two weeks of driving behavior. Only one roundabout could be observed at a time because only one set of specialized video equipment was available.
The raw videos were processed to produce a data set for analysis. Researchers used TrafficIntelligence, an open-source computer vision program, to automate extraction of vehicle trajectories from the raw footages. They used the same software to correct any errors to improve data reliability. The resulting clean data from the recorded videos were supplemented with historical crash frequency data reports obtained from the Minnesota Department of Public Safety. Collectively, data from both sources allowed researchers to thoroughly investigate the frequency and crash types from the four roundabouts. A statistical analysis of the data revealed that turn violations and yield violations were among the most common driving errors.
Researchers also looked at how violation rates vary with the roundabout’s location and relevant design features. Based on these findings, researchers proposed signage and striping changes to reduce driver errors at the two Mankato test sites. After the changes were implemented, they collected additional video data.
What Did We Learn?
This study provided one of the most comprehensive analyses to date of driving behavior at multilane roundabouts. Researchers were successful in finding solutions for reducing turn violations, but they were unable to identify solutions for yield violations despite the vast amount of data.
Minor differences in the design at each roundabout presented specific challenges. The analysis focused on how each varying design feature impacted driving behavior. Proposed traffic control changes such as extending solid lines between entrance lanes, adjusting the position of yield signs and adding one-way signs successfully decreased turn violations. However, data from before and after traffic control changes showed an insignificant impact on decreasing yield violations. Importantly, the study produced a list of ineffective traffic control methods that can be eliminated from future studies, saving engineers time and money.
The TrafficIntelligence tool was crucial in efficiently processing and cleaning large amounts of raw video. With improvements made to the software program, the tool should be an asset to future research on roundabouts and to other studies requiring observations of driving behavior.
The traffic control changes that were successful at reducing crashes at two-lane roundabouts should be implemented by traffic engineers. In particular, large overhead directional signs or extended solid lines between entrance lanes should be installed to help reduce turning violations. The analysis method used in this study could also be used for a robust before-and-after evaluation of future modifications to traffic control devices.
Additional research could further scrutinize the data already collected, and researchers recommend that more data be collected to examine additional traffic control methods and other intersection design elements to improve the overall safety and mobility of two-lane roundabouts. This research could also serve as an impetus for the study of numerous roundabouts in a pooled fund effort involving several states.
This post pertains to the LRRB-produced Report 2017-30, “Evaluation of Safety and Mobility of Two-Lane Roundabouts,” published July 2017. A webinar recording of the report is also available.
This project developed a methodology using traffic data collected by the SMART-Signal system to identify intersections prone to red light running and, therefore, serious crashes. This methodology could help MnDOT prioritize intersections for safety improvements.
“The essence of this project was to develop a toolbox that traffic engineers can use to determine an intersection’s safety performance,” said Henry Liu, Research Professor, University of Michigan Transportation Research Institute.
Liu served as the study’s principal investigator.
“This research provides a way to classify intersections that have a higher potential for red light running,” Mick Rakauskas, Former Research Fellow, HumanFIRST Program, University of Minnesota
What Was the Need?
Engineers traditionally measure an intersection’s safety using the number of crashes that actually occur there. However, collisions are rare and somewhat random events, and it can take a long time to collect enough data to accurately assess a single location’s safety.
Traffic conflicts—“close calls” in which one or both drivers must brake, swerve or take some other evasive action to avoid a crash—happen much more often than collisions do. As a result, many research projects use traffic conflicts as an alternative measure of safety.
Red light running (RLR) is one of the most common and dangerous causes of traffic conflicts at signalized intersections. While not every RLR event leads to a collision, it is often the first step in a process that ends in one.
Additionally, crashes caused when drivers run red lights are typically right-angle crashes, which are frequently severe. About 45 percent of right-angle collisions result in injury compared to about 25 percent of other crash types. Reducing right-angle-crash frequency can therefore significantly improve overall road safety and reduce costs related to traffic collisions.
MnDOT’s Safety Group wanted to determine whether it was possible to objectively and automatically identify intersections where RLR events are most likely to occur. Developing a methodology to identify the most dangerous intersections would help MnDOT prioritize locations for safety improvements.
What Was Our Goal?
Several previous MnDOT research projects had developed the SMART-Signal system, an automatic system that collects data from traffic signal controllers at signalized intersections. MnDOT has installed the system at more than 100 intersections in the Twin Cities. This project sought to develop tools that use SMART-Signal data to evaluate safety performance at intersections.
What Did We Do?
Researchers analyzed SMART-Signal data collected at the intersection of Boone Avenue and Trunk Highway 55 (TH 55) in Golden Valley between December 2008 and September 2009. This intersection is equipped with both stop-bar detectors and advance detectors located about 400 feet upstream of the intersection. Researchers used stop-bar-actuation data and details about traffic signal phases to identify RLR events at the intersection.
However, since most intersections are equipped only with advance detectors, this method cannot be used to measure RLR events at all intersections. As an alternative, re-searchers used vehicle-speed and traffic-volume data from the advance detectors, along with recorded traffic-signal-phase information from SMART-Signal, to identify potential RLR events. They compared these potential events to actual RLR events identified using stop-bar data and developed a formula to predict whether an RLR event would occur. This formula can be applied at intersections of major and minor roads that are not equipped with stop-bar detectors.
Researchers then used data from a minor road to develop a method that identified whether an RLR event would lead to a traffic conflict. In this method, an intersection is first divided into four conflict zones (two in each direction). When a vehicle from the main road enters the intersection, the method enables researchers to calculate when the vehicle enters and leaves each of the conflict zones it passes through. Then they determine whether a vehicle from the minor road is in the same conflict zone. Using this methodology, researchers estimated the number of daily traffic conflicts at other inter-sections on TH 55. These estimates were based on data collected in 2009 and between 2012 and 2015.
Finally, researchers developed a regression model to evaluate whether adding the number of predicted traffic conflicts to a more standard model that used average annual daily traffic (AADT) would correlate with the number of actual collisions at that site. They evaluated the model using data from seven four-legged intersections and two T-intersections on TH 13 and TH 55.
What Did We Learn?
The formula for predicting RLR events matched observations 83.12% of the time, based on more than 2,000 data points.
The number of daily crossing conflicts at TH 55 intersections ranged from 7.9 (at Glenwood Avenue in 2009) to 51.2 (at Winnetka Avenue in 2013).
While limited data were available for the regression model (as no site had more than four years of SMART-Signal data available, and there were only 11 crashes in total), the model suggests that estimated average traffic conflicts and minor-road AADT both contribute to accurate prediction of right-angle-crash frequency, while major-road AADT does not. Due to the limited data available, however, these conclusions should be considered preliminary.
While there are currently no plans for follow-up studies, additional research efforts could include continuing to evaluate and improve the prediction model as more data are collected, and installing video cameras at intersections to validate the proposed methodologies.
This Technical Summary pertains to Report 2017-08, “Estimation of Crossing Conflict at Signalized Intersection Using High-Resolution Traffic Data,” published March 2017.