Developing Smooth, Quiet, Safe Portland Cement Concrete Pavements, March 2004

The concrete paving industry has spent large amounts of time working to provide safe, quiet, and smooth pavements for the traveling public as their needs and driving habits have changed since the advent of the automobile. During that time, the efforts of research, design, and construction were directed at one of the problems at a time. Current public surveys indicate that the traveling public wishes to have safe, quiet, and smooth pavements. This report identifies the problems remaining in the areas of developing smooth, quiet, and safe portland cement concrete pavement in each pavement we build. It develops the research framework that can be used to bring the existing information together with additional research in each area. The resulting answers can be used in each pavement design for a quiet, safe, and smooth pavement that is also long lasting.

Development and Implementation of an Expert System for Forecasting Fog on US Highway 30 in Cedar Rapids, Iowa, HR-357, 1996

Several accidents, some involving fatalities, have occurred on U.S. Highway 30 near the Archer Daniels Midland Company (ADM) Corn Sweeteners plant in Cedar Rapids, Iowa. A contributing factor to many of these accidents has been the large amounts of water (vapor and liquid) emitted from multiple sources at ADM's facility located along the south side of the highway. Weather and road closure data acquired from IDOT have been used to develop a database of meteorological conditions preceding and accompanying closure of Highway 30 in Cedar Rapids. An expert system and a FORTRAN program were developed as aids in decision making with regard to closure of Highway 30 near the plant. The computer programs were used for testing, evaluation, and final deployment. Reports indicate the decision tools have been successfully implemented and were judged to be helpful in forecasting road closures and in reducing costs and personnel time in monitoring the roadway.

Effects of Implements of Husbandry (Farm Equipment) on Pavement Performance, TR-563, 2012

The effects of farm equipment on the structural behavior of flexible and rigid pavements were investigated in this study. The project quantified the difference in pavement behavior caused by heavy farm equipment as compared to a typical 5-axle, 80 kip semi-truck. This research was conducted on full scale pavement test sections designed and constructed at the Minnesota Road Research facility (MnROAD). The testing was conducted in the spring and fall seasons to capture responses when the pavement is at its weakest state and when agricultural vehicles operate at a higher frequency, respectively. The flexible pavement sections were heavily instrumented with strain gauges and earth pressure cells to measure essential pavement responses under heavy agricultural vehicles, whereas the rigid pavement sections were instrumented with strain gauges and linear variable differential transducers (LVDTs). The full scale testing data collected in this study were used to validate and calibrate analytical models used to predict relative damage to pavements. The developed procedure uses various inputs (including axle weight, tire footprint, pavement structure, material characteristics, and climatic information) to determine the critical pavement responses (strains and deflections). An analysis was performed to determine the damage caused by various types of vehicles to the roadway when there is a need to move large amounts agricultural product.

Using Digital Video Analysis to Monitor Driver Behavior at Intersections

Commercially available instruments for road-side data collection take highly limited measurements, require extensive manual input, or are too expensive for widespread use. However, inexpensive computer vision techniques for digital video analysis can be applied to automate the monitoring of driver, vehicle, and pedestrian behaviors. These techniques can measure safety-related variables that cannot be easily measured using existing sensors. The use of these techniques will lead to an improved understanding of the decisions made by drivers at intersections. These automated techniques allow the collection of large amounts of safety-related data in a relatively short amount of time. There is a need to develop an easily deployable system to utilize these new techniques. This project implemented and tested a digital video analysis system for use at intersections. A prototype video recording system was developed for field deployment. A computer interface was implemented and served to simplify and automate the data analysis and the data review process. Driver behavior was measured at urban and rural non-signalized intersections. Recorded digital video was analyzed and used to test the system.