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.

Repairing the Impaired: Two Iowa Success Stories, 2005

More than 200 lakes, streams and rivers are on Iowa’s impaired waters list. Pollutants prevent these waters from supporting aquatic life, or from being used for drinking water or for full body recreational contact, like swimming. While improving Iowa’s water quality may seem a daunting task, two southern Iowa lakes show that it can be done.

Fact Sheet: Winter Driving Fact Sheet, 2009

The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

Fact Sheet: Winter Driving Storm Sheet, 2009

The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

Fact Sheet: Winter Driving, 2011

The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

Examining Driver Behavior in Response to Work Zone Interventions: A Driving Simulator Study, 2010

Construction zones pose a significant threat to both workers and drivers causing numerous injuries and deaths each year. Innovations in work zone safety could reduce these numbers. However, implementing work zone interventions before they are validated can undermine rather than enhance safety. The objective of this research is to demonstrate how driving simulators can be used to evaluate the effect of various work zone interventions on driver performance.

Driving with Diminished Skills, August 6, 2007

Because driving is a complex task, drivers need to be sure they have the mental and physical capacity for driving safely as they experience changes with aging. Most drivers who are aware of their changing capacity to drive can adjust their driving plans and improve their driving habits to drive safer and longer.

Driving Retirement Planning and making it work, August 2, 2007

The value of driving We as Americans - and especially as Iowans - value the independence of getting around in our own vehicles and staying connected with our families and communities. The majority of older Iowans enjoy a more active, healthy and longer life than previous generations. Freedom of mobility shapes our quality of life. With aging, driving becomes an increasing concern for older Iowans and their families. How we deal with changes in our driving ability and, eventually, choose when and how to retire from driving, will affect our safety and our quality of life.

Curb it-Click it Electronic Communication Devices Prohibited Uses While Driving

This brochure explains Iowa's laws concerning the use of cell phones and other electronic communication devices while driving.

Prevalence and Distribution of Young Driver Distraction Errors in Naturalistic Driving, TPF-5(207), 2014

Naturalistic driving studies are the latest resource for gathering data associated with driver behavior. The University of Iowa has been studying teen driving using naturalistic methods since 2006. By instrumenting teen drivers’ vehicles with event-triggered video recorders (ETVR), we are able to record a 12-second video clip every time a vehicle exceeds a pre-set g-force threshold. Each of these video clips contains valuable data regarding the frequency and types of distractions present in vehicles driven by today’s young drivers. The 16-year old drivers who participated in the study had a distraction present in nearly half of the events that were captured. While a lot of attention has been given to the distractions associated with technology in the vehicle (cell phones, navigation devices, entertainment systems, etc.), the most frequent type of distraction coded was the presence of teen passengers engaging in conversation (45%). Cognitive distractions, such as singing along with the radio, were the second most common distraction. Cell phone use was the third most common distraction, detected in only 10% of the events containing distraction.

Winter Driving A Guide for Your Safety, January 17, 2012

The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

Evaluating the Relationship between the Driver and Roadway to Address Rural Intersection Safety using the SHRP 2 Naturalistic Driving Study Data, RB05-013, 2016

Rural intersections account for 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Transportation agencies have traditionally implemented countermeasures to address rural intersection crashes but frequently do not understand the dynamic interaction between the driver and roadway and the driver factors leading to these types of crashes. The Second Strategic Highway Research Program (SHRP 2) conducted a large-scale naturalistic driving study (NDS) using instrumented vehicles. The study has provided a significant amount of on-road driving data for a range of drivers. The present study utilizes the SHRP 2 NDS data as well as SHRP 2 Roadway Information Database (RID) data to observe driver behavior at rural intersections first hand using video, vehicle kinematics, and roadway data to determine how roadway, driver, environmental, and vehicle factors interact to affect driver safety at rural intersections. A model of driver braking behavior was developed using a dataset of vehicle activity traces for several rural stop-controlled intersections. The model was developed using the point at which a driver reacts to the upcoming intersection by initiating braking as its dependent variable, with the driver’s age, type and direction of turning movement, and countermeasure presence as independent variables. Countermeasures such as on-pavement signing and overhead flashing beacons were found to increase the braking point distance, a finding that provides insight into the countermeasures’ effect on safety at rural intersections. The results of this model can lead to better roadway design, more informed selection of traffic control and countermeasures, and targeted information that can inform policy decisions. Additionally, a model of gap acceptance was attempted but was ultimately not developed due to the small size of the dataset. However, a protocol for data reduction for a gap acceptance model was determined. This protocol can be utilized in future studies to develop a gap acceptance model that would provide additional insight into the roadway, vehicle, environmental, and driver factors that play a role in whether a driver accepts or rejects a gap.