Bridge decks reinforced with one layer of epoxy-coated rebar and a bottom layer of uncoated steel rebar show corrosion damage sooner than decks constructed with all epoxy-coated rebar. Inspection methods should be enhanced to add a rating for cracking density on the underside of bridge decks. Repairs to mixed rebar decks should be conducted once a key deck surface inspection element has received a condition rating of two and held that rating for seven years, which is sooner than the average repair time of 8.5 years.
Continue reading Epoxy-Coated Rebar Bridge Decks Outperform Mixed Rebar DecksCategory Archives: research
General research posts.
Speed Notification System Warns Drivers Approaching Urban Work Zones
Using an innovative method to calculate vehicle trajectories and gather large amounts of driver data, researchers tested and evaluated the new Smart Work Zone Speed Notification system and determined that its messages successfully influenced drivers to reduce their speed.
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Preparing Roads for Connected and Autonomous Vehicles
Proprietary technologies, industry competition and federal regulatory concerns are slowing the advent of defined standards for connected and autonomous vehicles (CAVs). Researchers investigated the state of CAV implementation to help local agencies begin preparing for the infrastructure needs of these vehicles. CAV-friendly options are considered for eight infrastructure categories. Since truck platooning is the likely first application of this technology, and optical cameras appear imminent as an early iteration of sensing technology, researchers suggest that wider pavement striping and well-maintained, uniform and visible signage may effectively serve the needs of CAVs in the near future while enhancing infrastructure for today’s drivers.
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Bus–Highway Connections Make Transit More Competitive With Driving
Researchers developed a method for associating travel times and travel costs with transit mobility. In an evaluation of bus–highway system interactions, investigators found that park-and-ride lots and managed lanes put suburban and walk-up urban transit options on equal footing. Bus–highway system interactions improve access to job locations and have improved transit access to job sites by about 20 percent compared to automobile access. When wage-related costs are included, the benefit of automobile use over transit use diminishes significantly.
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New project: Effectiveness of Teenage Driver Support System
The Minnesota Local Road Research Board (LRRB) has funded a follow-up study to determine whether a monitoring system it field tested for new drivers, called the Teen Driver Support System (TDSS), affected teenagers’ long-term driver behavior.
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Concrete Grinding Residue Doesn’t Appear to Negatively Affect Roadside Vegetation and Soil
A new MnDOT research study determined that depositing concrete grinding residue (CGR) slurry at specific rates on roadside vegetation and soil may not cause lasting harm to plant growth and soil quality; however, follow-up research is recommended.
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Study recommends strategies for reducing transportation disparities
Transportation contributes to many broad societal outcomes, such as employment, wealth, and health. Some Minnesotans, however, are underserved by current systems and face disparities and barriers in reaching their destinations. According to new research from the U of M, efforts to improve transportation equity need to focus on societal inequities—such as racial segregation and auto dependency—as well as the transportation barriers that affect specific communities and population groups.
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MnDOT’s Smart Bridge Sensors Are Leveraged to Measure Vertical Displacement
A Minnesota Department of Transportation research study has developed a new method for estimating vertical displacements on bridges using accelerometers installed on the Interstate 35W St. Anthony Falls Bridge in Minneapolis. The dual-model approach shows potential for using these sensors to measure vertical displacement on steel, cable-stayed and other less-stiff bridges where traffic generates higher vibration frequencies. The method expands the industry’s knowledge of how to use smart sensors in new ways.
What Was the Need?
Since September 2008, the I-35W St. Anthony Falls Bridge has carried traffic over the Mississippi River in Minneapolis and funneled sensor data to researchers and MnDOT bridge engineers. This smart bridge features over 500 sensors that monitor strain, load distribution, temperature, bridge movement, and other forces and functions.
Sensors help designers and bridge managers learn more about how bridges shift and flex over time. Concrete expands and contracts, and bearings shift; sensor systems continuously gather data about these minute changes, offering an alternative to time-consuming inspection.
Researchers continue to identify potential uses for sensor data and new ways to use such information to analyze bridge properties and performance. In a 2017 study about monitoring bridge health, researchers learned to distinguish and associate specific vibration frequencies with structural damage, weather conditions and other factors. These frequencies were gathered by accelerometers, which measure structural vibrations triggered by traffic and environmental conditions.
Decks, piers and other structural elements displace vertically under loads and environmental conditions. Researchers and bridge managers wanted to know if accelerometers could be used to measure vertical displacements and help monitor bridge health.
What Was Our Goal?
MnDOT needed a procedure for measuring and monitoring vertical displacement on bridges under traffic and environmental forces. Investigators would use the sensor systems on the I-35W St. Anthony Falls Bridge to design and analyze this procedure.
“We need to learn more about sensors because we don’t have a lot of experience with them. This study gave us valuable information about accelerometers and the information they provide,” said Benjamin Jilk, Complex Analysis and Modeling Design Leader, MnDOT Bridge Office.
What Did We Do?
Indirect analysis and measurement of vertical displacements rely on estimations obtained through modeling. Investigators evaluated the most well-developed approach for measuring vibration frequencies like those tracked by accelerometers and refined the method. The team developed a dual-model approach: One model estimates loads and the other estimates displacements.
In a laboratory, investigators evaluated the impact of loading on displacement and vibration frequencies on a girder with contact sensors and accelerometers under moving and stationary loads. Researchers applied the dual-model analysis to laboratory displacement readings to compare the effectiveness of the model with contact sensor responses to loading.
Using laboratory data, investigators tuned the dual-model approach to accelerometer data available from the I-35W St. Anthony Falls Bridge. The research team then applied its identified tuning approach to the data from the bridge’s 26 accelerometers to determine the procedure’s suitability for estimating vertical displacement from vibration response on this bridge and its potential for other structures in the MnDOT bridge system.
Affordable GPS-Based System Warns Drivers About Lane Departures, Approaching Curves
Researchers have developed an affordable camera-free curve and lane departure warning system that relies on consumer-level GPS, rather than sophisticated, expensive digital maps.
The technology uses cumulative driving trajectory data from GPS points detected every 100 milliseconds to predict driving path trajectories and compare these to mapped curves and lanes. With further development, the system can be used as an inexpensive smartphone app or retail device to warn drivers of lane drift and approaching curves.
“The goal of the project is to reduce lane departure crashes. We viewed this as a seed project and demonstrated that the system can be successful,” said Victor Lund, Traffic Engineer, St. Louis County.
What Was Our Goal?
The Minnesota Local Road Research Board sought research to develop a camera-free curve and lane departure warning system that uses consumer-level GPS capability without reliance on sophisticated, expensive digital maps.
What Was the Need?
Lane departures and run-off-road crashes cause more fatalities and serious injuries in Minnesota than any other accident type.
Many current warning technologies rely on cameras that identify lane position based on pavement markings. In inclement weather, stripes and pavement markings can be difficult or impossible to identify; markings also wear off over time, reducing visibility even in clear conditions. Camera-based lane departure warning systems are also expensive and generally restricted to newer luxury vehicles, making them inaccessible to the general driving public.
Though in-vehicle technology for the public usually falls outside the research interests of the Minnesota Department of Transportation and the Minnesota Local Road Research Board, the agencies have been funding development of lane departure warning technologies to improve driver safety. GPS technologies offer an intriguing path to consumer-level lane departure warning systems.
High-level GPS can be accurate to the centimeter level, but access is restricted and use is expensive. These systems also rely on accurate, lane-level roadway mapping, an elusive data set with high access costs.
What Did We Do?
Researchers began with a literature search of the uses of standard GPS receivers in lane departure and navigation. The research team then developed an algorithm for travel direction that uses standard GPS in a straight road lane departure system to determine driving trajectories at accuracy levels suited to safe driving needs.
Investigators adapted a publicly available digital mapping platform to the same algorithm to identify navigational points along curves and develop the curve lane departure warning system. The team enhanced standard safe distance methods to consider driver reaction time in determining when approach warnings should be issued.
Researchers then brought the two developmental stages of the system together with a warning system that identifies vehicle speed, curvature characteristics and safe speed limits, and calculates distance for driver response times to issue an audible warning to drivers on lane drift and a text warning of when and how much to reduce speed as the vehicle approaches a curve.
For project testing and demonstration, investigators programmed the algorithm into a device with a built-in GPS receiver, connected it to a laptop for messaging and conducted driving tests on Rice Lake Road and on Interstate 35 near Duluth.
“From a technical point of view, this approach works. We developed a warning system with standard GPS that everyone has in a phone or vehicle. This is a lifesaving technology in a sense,” said Imran Hayee, Professor, University of Minnesota Duluth Department of Electrical Engineering.
What Did We Learn?
Finding no research on development of consumer-grade GPS for lane departure purposes, the research team adapted previous work on the relative accuracy of GPS readings from a MnDOT study on wearable GPS for work zone safety.
Researchers adapted a consumer-level GPS device to acquire data at 10-hertz frequency, which yields a GPS position point of 2.7 meters if a vehicle is driven at 60 mph.
The system calculates lane trajectory from cumulative readings and detects turns or drift. The curve warning system plots trajectories and compares these with open-source digital maps with road-level (rather than lane-level) accuracy to anticipate curves.
In road testing, the system issued audio warnings for every one of the approximately 200 lane changes, including curves. For curve warnings, the system scanned for curves at least half a mile ahead and calculated the vehicle’s speed and the distance to a curve to issue a timely text warning of the curve ahead and an advisory speed limit. Additional messages were issued when the vehicle was on the curve and when the curve had ended.
False alarms—warnings issued when the vehicle was not departing its lane—occurred in 10 percent of the tests, usually on sharp curves. Further adjustment of the algorithm and additional testing reduced false alarms significantly as the system accumulated data over multiple uses of the same roadway.
What’s Next?
Investigators filed a patent for the technology and will continue to develop the system. Further refinement of reference road direction information will improve accuracy and safety; the research team has developed a new project to employ vehicle-to-vehicle dedicated short-range communication technology to expand road direction reference data. The system will then need to be adapted for a consumer-level device or a smartphone app for use in any vehicle.
This post pertains to the LRRB-produced Report 2018-34, “Development and Demonstration of a Cost-Effective In-Vehicle Lane Departure and Advanced Curve Speed Warning System,” published December 2018.
New System Measures Travel-Time Reliability to Reduce Traffic Delays
Researchers for the Minnesota Department of Transportation have developed a new travel-time reliability measurement system that automates the process of gathering and managing data from multiple sources, including traffic, weather and accident databases, to generate travel-time reliability measures and reports for the metropolitan freeway network.
What Was the Need?
Improving traffic efficiency has become a key goal of traffic operations managers. In heavy traffic periods, MnDOT’s Regional Transportation Management Center (RTMC) coordinates with Minnesota State Patrol and MnDOT Maintenance Services to detect and quickly respond to freeway incidents in the Twin Cities. The RTMC works with the Freeway Incident Response Safety Team to assist and remove stranded vehicles using MnDOT emergency road service trucks. RTMC also updates real-time road condition information on its 511 traveler information system.
bad weather and road construction that cause freeway congestion.
MnDOT and RTMC measure delay and congestion on the metropolitan freeway system, reporting the data in annual reports like the 2017 Congestion Report. While useful, this data offers little predictive value on its own. MnDOT’s metropolitan freeway system features 4,000 loop detectors that transmit traffic data every 30 seconds; this data informs the congestion and delay reports.
Correlating this data with locations on the freeway system and various operating conditions, such as weather and traffic incidents, is time- consuming. But the data could be used to systematically evaluate traffic delays and develop strategies to mitigate congestion.
What Was Our Goal?
In this project, investigators sought to develop a system for automatically accessing weather, crash and traffic data to assess travel-time reliability—the variability in travel times for any given route. Travel-time reliability measures are becoming the key indicators for transportation system operations and management.
What Did We Implement?
Investigators developed a new travel-time reliability measurement system (TTRMS) that integrates different types of data (such as weather, traffic, incident, work zone and special event) acquired from multiple sources and automatically produces various types of travel-time reliability measures for selected corridors following user-specified operating conditions and time periods.
“Travel-time reliability is another way of looking at congestion and at strategies for making it more tolerable. It used to take several hours, even days, to process travel-time reliability data. The TTRMS processes it in minutes,” said Brian Kary, Director, MnDOT Regional Transportation Management Center.
How Did We Do It?
Investigators began by developing a detailed design of the TTRMS architecture—its modules, their functions and their interactions. The team then developed a work-zone data input module, where detailed lane configurations of a given work zone can be specified.
Developers designed a travel-time reliability calculation module as the core of the new system that can automatically access MnDOT’s traffic data archive, its incident database and the National Oceanic and Atmospheric Administration’s weather database. It can also accept a set of input data for work zones, such as lane-closure periods and locations. The reliability calculation module was then integrated with user interfaces and reporting modules. Finally the integrated system was tested with the real data gathered in 2012 and 2013 from Interstates 35E and 35W, U.S. Highway 169 and State Highway 100.
What Was the Impact?
The system generated accurate travel-time reliability measures for the test periods and given operating conditions. In particular, the output measures were automatically generated in both table and graphical formats, thus saving traffic engineers significant amount of time and effort.
The TTRMS includes map-based interfaces, which provide administrators and general users with substantial flexibility in defining corridors, specifying operating conditions and selecting types of measures depending on the purposes of applications.
To test the new system’s performance, the research team used the TTRMS to evaluate traffic strategies deployed for the February 2018 Super Bowl in Minneapolis. Two weeks before the event, reliability was low for the freeway system serving the football stadium. During the week of the Super Bowl, MnDOT and the Department of Public Safety aggressively managed traffic incidents to keep traffic moving, and reliability rose substantially despite the increase in tourist traffic. In the days immediately after the Super Bowl, operational strategies returned to normal levels, and reliability fell to previous levels. Results suggest that aggressive incident management during this exceptionally high-volume regional event enhanced traffic efficiency.
What’s Next?
Further enhancements to the TTRMS should include automating inputs for work zone data, such as lane closures, changes in work zone locations and time periods. Future research could help traffic operations prioritize resources and develop short-term and long-term freeway improvements, including studies of bottlenecks and the freeway network’s vulnerability and resilience for natural events and large-scale incidents.
This post pertains to Report 2018-28, “Development of a Travel-Time Reliability Measurement System,” published September 2018.
Crossroads 