Quality and Competition: An Empirical Analysis across Industries, March 2006

This paper empirically explores the link between quality and concentration in a cross-section of manufactured goods. Using concentration data and product quality indicators, an ordered probit estimation explores the impact of concentration on quality that is defined as an index of quality characteristics. The results demonstrate that market concentration and quality are positively correlated across different industries. When industry concentration increases, the likelihood of the product being higher quality increases and the likelihood of observing a lower quality decreases.

Final Report on the Portable Computerized Assessments of Sleepy Drivers in Operational Environments, June 29, 2011

Excessive daytime sleepiness underpins a large number of the reported motor vehicle crashes. Fair and accurate field measures are needed to identify at-risk drivers who have been identified as potentially driving in a sleep deprived state on the basis of erratic driving behavior. The purpose of this research study was to evaluate a set of cognitive tests that can assist Motor Vehicle Enforcement Officers on duty in identifying drivers who may be engaged in sleep impaired driving. Currently no gold standard test exists to judge sleepiness in the field. Previous research has shown that Psychomotor Vigilance Task (PVT) is sensitive to sleep deprivation. The first goal of the current study was to evaluate whether computerized tests of attention and memory, more brief than PVT, would be as sensitive to sleepiness effects. The second goal of the study was to evaluate whether objective and subjective indices of acute and cumulative sleepiness predicted cognitive performance. Findings showed that sleepiness effects were detected in three out of six tasks. Furthermore, PVT was the only task that showed a consistent slowing of both ‘best’, i.e. minimum, and ‘typical’ responses, median RT due to sleepiness. However, PVT failed to show significant associations with objective measures of sleep deprivation (number of hours awake). The findings indicate that sleepiness tests in the field have significant limitations. The findings clearly show that it will not be possible to set absolute performance thresholds to identify sleep-impaired drivers based on cognitive performance on any test. Cooperation with industry to adjust work and rest cycles, and incentives to comply with those regulations will be critical components of a broad policy to prevent sleepy truck drivers from getting on the road.

Diagnostic Tools for Identifying Sleepy Drivers in the Field, RB21-012, 2013

The overarching goal of this project was to identify and evaluate cognitive and behavioral indices that are sensitive to sleep deprivation and may help identify commercial motor vehicle drivers (CMV) who are at-risk for driving in a sleep deprived state and may prove useful in field tests administered by officers. To that end, we evaluated indices of driver physiognomy (e.g., yawning, droopy eyelids, etc.) and driver behavioral/cognitive state (e.g. distracted driving) and the sensitivity of these indices to objective measures of sleep deprivation. The measures of sleep deprivation were sampled on repeated occasions over a period of 3.5-months in each of 44 drivers diagnosed with Obstructive Sleep Apnea (OSA) and 22 controls (matched for gender, age within 5 years, education within 2 years, and county of residence for rural vs. urban driving). Comprehensive analyses showed that specific dimensions of driver physiognomy associated with sleepiness in previous research and face-valid composite scores of sleepiness did not: 1) distinguish participants with OSA from matched controls; 2) distinguish participants before and after PAP treatment including those who were compliant with their treatment; 3) predict levels of sleep deprivation acquired objectively from actigraphy watches, not even among those chronically sleep deprived. Those findings are consistent with large individual differences in driver physiognomy. In other words, when individuals were sleep deprived as confirmed by actigraphy watch output they did not show consistently reliable behavioral markers of being sleep deprived. This finding held whether each driver was compared to him/herself with adequate and inadequate sleep, and even among chronically sleep deprived drivers. The scientific evidence from this research study does not support the use of driver physiognomy as a valid measure of sleep deprivation or as a basis to judge whether a CMV driver is too fatigued to drive, as on the current Fatigued Driving Evaluation Checklist.. Fair and accurate determinations of CMV driver sleepiness in the field will likely require further research on alternative strategies that make use of a combination of information sources besides driver physiognomy, including work logs, actigraphy, in vehicle data recordings, GPS data on vehicle use, and performance tests.

Pavement Management Performance Modeling: Evaluating the Existing PCI Equations, RB14-013 2014

The work described in this report documents the activities performed for the evaluation, development, and enhancement of the Iowa Department of Transportation (DOT) pavement condition information as part of their pavement management system operation. The study covers all of the Iowa DOT’s interstate and primary National Highway System (NHS) and non-NHS system. A new pavement condition rating system that provides a consistent, unified approach in rating pavements in Iowa is being proposed. The proposed 100-scale system is based on five individual indices derived from specific distress data and pavement properties, and an overall pavement condition index, PCI-2, that combines individual indices using weighting factors. The different indices cover cracking, ride, rutting, faulting, and friction. The Cracking Index is formed by combining cracking data (transverse, longitudinal, wheel-path, and alligator cracking indices). Ride, rutting, and faulting indices utilize the International Roughness Index (IRI), rut depth, and fault height, respectively.