Assessment of ND County and Local Road Needs, 2013-2015
Physical Road Testing
As part of its assessment of county and local road infrastructure needs in North Dakota, UGPTI is conducting an extensive statewide data collection effort on county and local roads. Data is being collected on traffic volume, vehicle classification, pavement distress, ride score, pavement layer thickness, and pavement/base/subgrade strength. The following tests are being conducted on roads across the state:
Falling Weight Deflectometer — NDSU is working with Dynatest, a pavement engineering consulting firm to evaluate pavement structural condition on more than 1,500 miles of county and local roads across the state. Technicians are using a trailer-mounted Falling Weight Deflectometer (FWD), a non-intrusive, non-destructive testing device. The device is widely used in pavement engineering to evaluate pavement structural condition. Results are used to select optimum pavement maintenance and rehabilitation strategies. The FWD "thumps" the pavement to produce a dynamic impulse load to a pavement surface, simulating the magnitude and duration of a single heavy moving wheel load. The pavement response (vertical deformation or deflection) at various distances from the loading plate are measured by a series of sensors. Pavement response, layer thickness, and other inputs are then used to calculate measurements of pavement condition. The FWD testing unit will be accompanied by a second vehicle with an arrow board to warn drivers and to protect workers.
Ground Penetrating Radar — Ground Penetrating Radar (GPR) will be used to measure pavement layer thickness on the same roads tested with the falling weight deflectometer. The data collected by GPR is a necessary input for the FWD layer strength analysis and will also help refine the study's pavement analysis which will determine remaining life and necessary overlay thickness. GPR technology is similar to ultrasound, but uses radio waves rather than sound waves to penetrate the pavement. Antennas mounted on a moving vehicle transmit short pulses of radio wave energy into the pavement. As this energy travels down through the pavement structure, echoes are created at boundaries of dissimilar materials (such as the asphalt-base interface). Measurements of these echoes can be used to calculate pavement layer thickness and other properties, such as moisture content. GPR data for this study will be collected by an instrumented vehicle at highway speeds with no impact on normal traffic. NDSU is working with Infrasense Inc., an engineering consulting firm specializing in infrastructure data collection and analysis.
Automated Road and Pavement Condition Survey — NDSU is partnering with NDDOT to collect pavement distress and ride information on more than 6000 miles of paved county roads. The NDDOT Pathway Van will be used to collect video and pavement information. The van is equipped with high resolution high speed cameras which create a video log of the road surface and right of way. A myriad of high tech sensors collect information on various conditions such as roughness(ride), rutting, faulting, and texture along with global positioning system and location information to track exactly where the data is collected. Computer software combines the collected data to measure the length and severity of all the various types of cracks in the pavement and determine a distress score.
Traffic Volume Data — Traffic data is being collected jointly by NDSU students and NDDOT staff. Together they will perform more than 1000 traffic volume counts on county and township roads and more than 600 truck classification counts. The process involves placing rubber tubes across a road at pre-determined traffic count locations for 48 hours. The tubes connect to a traffic data collection box on the side of the road which measures the air pressure from the tubes as a vehicle passes over them. Gravel roads may also be counted by using special tubes with flat bottoms. By using two tubes the number of axles and spacing can be determined. The data is then transferred to a computer where it is checked and processed using seasonal adjustment factors to come up with the AADT (Average Annual Daily Traffic) of both passenger cars and the various truck sizes. AADT is used help predict roadway deterioration and future traffic volume.