Minimum Data Set (MDS) Section Q Education: Helping People Return to the Community, February 12, 2014

Explanation of Minimum Data Set (MDS), implementation of Section Q, overview of the program, local contacts and functions, Referral Agency information, role and assistance provided by Long-Term care Ombudsman

Minimum Data Set (MDS) Section Q Education, February 21, 2014

Information regarding possible questions on Section Q within the Minimum Data Set.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

The Effect of Four-Lane to Three-Lane Conversion on the Number of Crashes and Crash Rates in Iowa Roads, June 2005

We analyze crash data collected by the Iowa Department of Transportation using Bayesian methods. The data set includes monthly crash numbers, estimated monthly traffic volumes, site length and other information collected at 30 paired sites in Iowa over more than 20 years during which an intervention experiment was set up. The intervention consisted in transforming 15 undivided road segments from four-lane to three lanes, while an additional 15 segments, thought to be comparable in terms of traffic safety-related characteristics were not converted. The main objective of this work is to find out whether the intervention reduces the number of crashes and the crash rates at the treated sites. We fitted a hierarchical Poisson regression model with a change-point to the number of monthly crashes per mile at each of the sites. Explanatory variables in the model included estimated monthly traffic volume, time, an indicator for intervention reflecting whether the site was a “treatment” or a “control” site, and various interactions. We accounted for seasonal effects in the number of crashes at a site by including smooth trigonometric functions with three different periods to reflect the four seasons of the year. A change-point at the month and year in which the intervention was completed for treated sites was also included. The number of crashes at a site can be thought to follow a Poisson distribution. To estimate the association between crashes and the explanatory variables, we used a log link function and added a random effect to account for overdispersion and for autocorrelation among observations obtained at the same site. We used proper but non-informative priors for all parameters in the model, and carried out all calculations using Markov chain Monte Carlo methods implemented in WinBUGS. We evaluated the effect of the four to three-lane conversion by comparing the expected number of crashes per year per mile during the years preceding the conversion and following the conversion for treatment and control sites. We estimated this difference using the observed traffic volumes at each site and also on a per 100,000,000 vehicles. We also conducted a prospective analysis to forecast the expected number of crashes per mile at each site in the study one year, three years and five years following the four to three-lane conversion. Posterior predictive distributions of the number of crashes, the crash rate and the percent reduction in crashes per mile were obtained for each site for the months of January and June one, three and five years after completion of the intervention. The model appears to fit the data well. We found that in most sites, the intervention was effective and reduced the number of crashes. Overall, and for the observed traffic volumes, the reduction in the expected number of crashes per year and mile at converted sites was 32.3% (31.4% to 33.5% with 95% probability) while at the control sites, the reduction was estimated to be 7.1% (5.7% to 8.2% with 95% probability). When the reduction in the expected number of crashes per year, mile and 100,000,000 AADT was computed, the estimates were 44.3% (43.9% to 44.6%) and 25.5% (24.6% to 26.0%) for converted and control sites, respectively. In both cases, the difference in the percent reduction in the expected number of crashes during the years following the conversion was significantly larger at converted sites than at control sites, even though the number of crashes appears to decline over time at all sites. Results indicate that the reduction in the expected number of sites per mile has a steeper negative slope at converted than at control sites. Consistent with this, the forecasted reduction in the number of crashes per year and mile during the years after completion of the conversion at converted sites is more pronounced than at control sites. Seasonal effects on the number of crashes have been well-documented. In this dataset, we found that, as expected, the expected number of monthly crashes per mile tends to be higher during winter months than during the rest of the year. Perhaps more interestingly, we found that there is an interaction between the four to three-lane conversion and season; the reduction in the number of crashes appears to be more pronounced during months, when the weather is nice than during other times of the year, even though a reduction was estimated for the entire year. Thus, it appears that the four to three-lane conversion, while effective year-round, is particularly effective in reducing the expected number of crashes in nice weather.

Pavement Markings and Safety Final Report, November 2010

Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking improvements and safety. A recent research interest in this area has been to find a correlation between retroreflectivity and crashes, but a significant statistical relationship has not yet been found. This study investigates such a possible statistical relationship by analyzing five years of pavement marking retroreflectivity data collected by the Iowa Department of Transportation (DOT) on all state primary roads and corresponding crash and traffic data. This study developed a spatial-temporal database using measured retroreflectivity data to account for the deterioration of pavement markings over time along with statewide crash data to attempt to quantify a relationship between crash occurrence probability and pavement marking retroreflectivity. First, logistic regression analyses were done for the whole data set to find a statistical relationship between crash occurrence probability and identified variables, which are road type, line type, retroreflectivity, and traffic (vehicle miles traveled). The analysis looked into subsets of the data set such as road type, retroreflectivity measurement source, high crash routes, retroreflectivity range, and line types. Retroreflectivity was found to have a significant effect in crash occurrence probability for four data subsets—interstate, white edge line, yellow edge line, and yellow center line data. For white edge line and yellow center line data, crash occurrence probability was found to increase by decreasing values of retroreflectivity.

Roadway Lighting and Safety: Phase II – Monitoring Quality, Durability and Efficiency, November 2011

This Phase II project follows a previous project titled Strategies to Address Nighttime Crashes at Rural, Unsignalized Intersections. Based on the results of the previous study, the Iowa Highway Research Board (IHRB) indicated interest in pursuing further research to address the quality of lighting, rather than just the presence of light, with respect to safety. The research team supplemented the literature review from the previous study, specifically addressing lighting level in terms of measurement, the relationship between light levels and safety, and lamp durability and efficiency. The Center for Transportation Research and Education (CTRE) teamed with a national research leader in roadway lighting, Virginia Tech Transportation Institute (VTTI) to collect the data. An integral instrument to the data collection efforts was the creation of the Roadway Monitoring System (RMS). The RMS allowed the research team to collect lighting data and approach information for each rural intersection identified in the previous phase. After data cleanup, the final data set contained illuminance data for 101 lighted intersections (of 137 lighted intersections in the first study). Data analysis included a robust statistical analysis based on Bayesian techniques. Average illuminance, average glare, and average uniformity ratio values were used to classify quality of lighting at the intersections.

Roadway Lighting and Safety: Phase II – Monitoring Quality, Durability and Efficiency, November 2011

This Phase II project follows a previous project titled Strategies to Address Nighttime Crashes at Rural, Unsignalized Intersections. Based on the results of the previous study, the Iowa Highway Research Board (IHRB) indicated interest in pursuing further research to address the quality of lighting, rather than just the presence of light, with respect to safety. The research team supplemented the literature review from the previous study, specifically addressing lighting level in terms of measurement, the relationship between light levels and safety, and lamp durability and efficiency. The Center for Transportation Research and Education (CTRE) teamed with a national research leader in roadway lighting, Virginia Tech Transportation Institute (VTTI) to collect the data. An integral instrument to the data collection efforts was the creation of the Roadway Monitoring System (RMS). The RMS allowed the research team to collect lighting data and approach information for each rural intersection identified in the previous phase. After data cleanup, the final data set contained illuminance data for 101 lighted intersections (of 137 lighted intersections in the first study). Data analysis included a robust statistical analysis based on Bayesian techniques. Average illuminance, average glare, and average uniformity ratio values were used to classify quality of lighting at the intersections.

Drivers' Behavior at Railroad Grade Crossings: Before and After Safety Campaign, HR-335, 1992

In April 1991 the Iowa Department of Transportation, the CNW Transportation Company, the SOO Line, and local agencies and business in the Mason City/Clear Lake area initiated an Operation Lifesaver program to attempt to increase public awareness of safety issues and safe behavior at railroad-highway grade crossings. This document reports an initial study of data on traffic characteristics at a selected set of grade crossings in Cerro Gordo County taken before and after the safety program. Twenty-two crossings were studied. The 13 crossings at which collisions were reported for the five years prior to the study were included in the sample of sites. Two field observations were made at each study crossing before the Operation Lifesaver campaign was in full swing, and two observations were made after the conclusion of the main effort of the campaign. The summary of each data set is contained in a companion volume. The research shows that Operation Lifesaver altered drivers' behavior in the following ways: (1) reduced approach speeds and crossing speeds at crossings with low speed limits, (2) reduced the percent of drivers approaching the crossing at speeds in excess of the posted speed limit, and (3) increased alertness of drivers to railroad crossing hazards as evidenced by more drivers looking for a clear track. Thus, Operation Lifesaver enhanced safety in street and highway traffic operations in the vicinity of railroad-highway grade crossings.

Investigation of Rapid Thermal Analysis Procedures for Prediction of the Service Life of PCCP Carbonate Coarse Aggregate, HR-337, 1993

The major objective of this research project was to use thermal analysis techniques in conjunction with x-ray analysis methods to identify and explain chemical reactions that promote aggregate related deterioration in portland cement concrete. Twenty-two different carbonate aggregate samples were subjected to a chemical testing scheme that included: • bulk chemistry (major, minor and selected trace elements) • bulk mineralogy (minor phases concentrated by acid extraction) • solid-solution in the major carbonate phases • crystallite size determinations for the major carbonate phases • a salt treatment study to evaluate the impact of deicer salts Test results from these different studies were then compared to information that had been obtained using thermogravimetric analysis techniques. Since many of the limestones and dolomites that were used in the study had extensive field service records it was possible to correlate many of the variables with service life. The results of this study have indicated that thermogravimetric analysis can play an important role in categorizing carbonate aggregates. In fact, with modern automated thermal analysis systems it should be possible to utilize such methods on a quality control basis. Strong correlations were found between several of the variables that were monitored in this study. In fact, several of the variables exhibited significant correlations to concrete service life. When the full data set was utilized (n = 18), the significant correlations to service life can be summarized as follows ( a = 5% level): • Correlation coefficient, r, = -0.73 for premature TG loss versus service life. • Correlation coefficient, r, = 0.74 for relative crystallite size versus service life. • Correlation coefficient, r, = 0.53 for ASTM C666 durability factor versus service life. • Correlation coefficient, r, = -0.52 for acid-insoluble residue versus service life. Separation of the carbonate aggregates into their mineralogical categories (i.e., calcites and dolomites) tended to increase the correlation coefficients for some specific variables (r sometimes approached 0.90); however, the reliability of such correlations was questionable because of the small number of samples that were present in this study.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.