NATIONAL ADVANCED DRIVING SIMULATOR

ANNUAL REPORT
COMING SOON Driving Safety Research Institute (page 3)





For years, we’ve been looking to establish our research unit as an institute that better encapsulates our broad level of expertise and interdisciplinary work: not just in simulation, but increasingly in on-road and naturalistic driving research. We’ve recently received approval from the university and from the Board of Regents, state of Iowa, to rename NADS to the University of Iowa Driving Safety Research Institute (DSRI) Simulation will remain a core part of what we do, but we’ll soon carry a name that includes both simulation and on-road research— with our ultimate mission to remain the same: safer roads for all. In the past decade, we have obtained more than $27 million in funding for on-road research studies alone. We’re excited about new opportunities we hope to pursue with this new name, so more to come on that!
We are also excited to report many “firsts” from this past year. Our staff, student, and faculty research team is making a difference in pushing the state of the art.
Our ADS for Rural America automated shuttle is running on rural roads in Iowa through small communities on a variety of road types and in different weather conditions. We are proud to be one of the leading institutions globally for this type of research. Our research staff and partners have done what some say is impossible in this area. By demonstrating highly automated driving in rural America, we bring equity to the next generation of driving and rural transportation
options for those who have mobility impairments. Although rural equity is central to this research, our first goal is safety for our research and safer roads in the future. Automated driving is still far away, and we have the opportunity to develop safety procedures and an operating environment so others can learn from our work.
Our students continue to be another highlight as they will carry the Iowa flag for our next generation. From working on important transfer of control in automated driving, to developing new cannabis impairment metrics to innovations in integrated regenerative braking and crash avoidance systems, our students continue to lead some of the most advanced automotive research in the world.
We’re also excited to announce we’ve received a major contract from NHTSA for a project that will look at roadway interactions between human-driven and automated vehicles—more on that project on page 10.
We look forward to collaborating with many of you in the coming year and catching up at TRB or other conferences. Exciting things are in store for us!
Daniel V. McGehee Director, National Advanced Driving Simulator Associate Professor Industrial & Systems Engineering Emergency Medicine Public Health Public Policy• Human factors
• Distracted driving
• Drowsy driving
• Drugged driving
• Connected and automated vehicles
• Mobility
• At-risk populations (older and novice drivers)
• Safety and crash data analysis
• Simulation science
• Crash biomechanics
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We work with students in all phases of their college careers. A few of our graduate students are highlighted here.
Research interest: modeling cannabis-impaired driving performance
Thomas Burt spent his summer in Washington, D.C., as an intern for the National Highway Traffic Safety Administration on the ADS Vehicle Exemption Program Team. During his internship, Burt reviewed and investigated imported automated vehicles, assessed their use on public roads, and analyzed incident and crash data.
Additionally, Burt presented in Gothenburg, Sweden, at the International Conference on Traffic and Transport Psychology on “THC Potency, Perceived Effects, and Driving Performance,” and in Portland, Oregon, at the Association for Advancement of Automotive Medicine Conference on “Perceived Effects of Cannabis: Generalizability of Changes in Driving Performance.”
During his time at Iowa, Thomas has already published three journal articles on the effects of cannabis intoxication on driving impairment.
Emily Shull uses her background in psychology to understand how we can effectively facilitate the transition of control from partial automation back to the driver in a safe and timely manner. She hopes that this understanding can be applied to much broader concepts and influence the way we design and implement automation in our lives.
Over the summer, Shull presented her research on “The Gap Effect in Shifting Attention in Conditional Automation” at the International Conference on Traffic and Transportation Psychology in Gothenburg, Sweden. This fall, she also received the Human Factors and Ergonomics Society 2022 Student Member with Honors Award for her contributions to human factors research.
Joy Kim’s main research interest includes the safety concern surrounding the transfer of learning and knowledge gaps around new vehicle technologies. She currently is focusing on data collection at NADS on a project investigating the transfer of control from automated driving features to manual driving.
Max Miller is a graduate student who joined our team at NADS over the summer to pursue his interest in engineering research. Miller has a BS in industrial engineering, and he hopes to apply his interests in data analytics, modeling, and computational algorithms to new and unconventional areas of research.
Christopher R. M. Rundus graduated with his PhD in Industrial and Systems Engineering in the spring of 2022 and has since begun his career with Gulfstream Aerospace in Savannah, Georgia, as a human factors engineer.
During his time at the University of Iowa, his research interests focused on the safety benefits of regenerative braking systems in electric vehicles. He authored multiple papers surrounding regenerative braking and has one patent from his dissertation.
This past summer, Rundus presented his research on regenerative braking and driver-foot behavior at the Road Safety and Simulation Conference in Athens, Greece.
We are excited to have welcomed three new staff members this past year.
Justin Mason received his BS in psychology, MS in exercise physiology, and PhD in sport and exercise psychology from Florida State University. He received his postdoctoral training in Driver Rehabilitation Science at the University of Florida, where he was most recently a research assistant professor.
Q: What attracted you to the University of Iowa?
A: “ I chose the University of Iowa’s National Advanced Driving Simulator because of the rigor and way research is conducted. NADS takes a multidisciplinary approach to research while maintaining autonomy. The research coming from the University of Iowa and specifically NADS will make a difference in the long run for road users and drivers.”
Q: What do your areas of research include?
A: “For the past eight years, my research has primarily
focused on older drivers, how they interact with driving systems, and their fitness to drive, as well as how users in general use automated vehicles. Additionally, I have researched traumatic brain injuries, such as concussions, and how these injuries affect an individual’s driving.”
Q: What drives the passion behind your research?
A: “ In short, everyone drives or needs transportation. It is an instrumental activity of daily living that is very important to humans throughout their lifespan. Technology is constantly changing our understanding of driving. There are so many areas of driving that require research. For example, how do we monitor and provide countermeasures in real-time to the driver without distracting them, and how can we support older drivers to maintain their fitness to drive? I am inquisitive, and I love that learning is a vital part of my career.”
Noah Rothermel started out his research career with NADS as an undergraduate, then as a temporary staff member, and finally as a full-time staff member. He has extensive experience in the development, conduct, and analysis of research studies both on-road and in simulation.
On recent projects, Rothermel has authored driving scenarios for studies on the NADS-1 simulator including driver distraction, warning indicators, drowsiness countermeasures, and automated driving systems. He assisted with the development of and participated in data collection of an on-road study that evaluated the use of a bioptic telescope for drivers while navigating in an unfamiliar area. He regularly authors scenarios to be used in simulation studies, creates staff protocols, trains research staff, and writes technical reports with regard to scenario design and verification of methods used.
“My interest in the motorsport industry has created a passion for developing driving safety technologies for the general public,” said Rothermel.
Prior to joining NADS, Christian Bauer worked for more than 15 years as a software developer and research scientist with a focus on computer vision, machine learning, 3D visualization, and user interaction.
Among several projects, he contributed to a distributed VR/AR system that allowed multiple users to collaborate in AR/VR on tasks such as liver surgery planning. The system shared several similarities with the NADS system and NADS’ goal to connect multiple simulators.
“I’ve always enjoyed working in cross-functional teams and am excited about joining the NADS team, working on the software of a large, highfidelity simulator,” said Bauer.
In the fall of 2022, NADS secured a contract with the National Highway Traffic Safety Administration (NHTSA) for a project that will look at roadway interactions between human-driven and automated vehicles. The study—known as Human Interactions with Driving Automation Systems—will involve using the NADS suite of driving simulators to simulate interactions among manually driven vehicles and vehicles that have automated features. Manually driven vehicles will be fully human-driven with no driver-assist or automated features, while the automated vehicles may contain different degrees of human-automation control in the simulator.
“As automated driving features evolve and start to become more common, understanding how they interact with
human-driven vehicles is essential to the safe implementation of these vehicles,” explained John Gaspar, PhD, director of human factors research.
To enable NADS to study these interactions, the project will focus on creating a simulator environment where multiple research participants can interact in the same virtual world. Two of the NADS driving simulators will be connected in the same virtual environment to allow these mixed-traffic interactions to occur.
Chris Schwarz , PhD, director of simulation and modeling, added, “This unique connected simulation capability will allow us to collect data from multiple research participants simultaneously.”
In two recent studies with NHTSA, NADS researchers have been examining various aspects of transition of control (TOC) between human drivers and periods of automated driving.
We asked: How does the timing and design of takeover warnings influence how drivers regain manual control? We first looked at the amount of time given to regain manual vehicle control after engaging in a secondary email task during automation. Edge case events (such as a pedestrian walking onto the road or a dead deer on the road) were used to test situational awareness 5 to 10 seconds after the request to intervene (RTI).
What we found: “When the window was 10 or 15 seconds, drivers were typically
able to transition back to manual control, although some drivers chose to continue emailing,” said Gaspar. To follow up, in a similar study (Temporal Components of Warning), the team looked at shorter windows (4 to 8 seconds) and the minimum window necessary to successfully make the transition back to manual control.
Next, we wanted to see if we could change behavior to get subjects to detect and respond to those edge cases. We created a brake pulse as part of a request to intervene, which was effective at getting participants to look up earlier compared to a condition with no brake pulse. Earlier disengagement from emailing and looking toward the forward road may be effective in reducing crashes in some edge case situations.
Gaspar, PhD, director of human factors researchA pair of driver monitoring systems (DMS) were integrated into the NADS-1 simulator to test how effective the systems are at predicting drowsiness while subjects completed overnight drives of three to four hours. The Aisin DMS is a camera-based eye tracker that measures gaze location, eye closure, and face position.
We performed an analysis that included creating models of drowsiness based on inputs from the DMS and the vehicle. Using these models, we asked: How early can drowsiness be detected, and can it be predicted before driving performance changes?
“We modeled drowsiness using the DMS data and lane keeping data, and we added physiological data from wrist bands,” explained Chris Schwarz, PhD. ”With that, we successfully made a model that detects drowsiness and predicts it ahead of drowsy lane departures.”
Sponsored by AAA Foundation for Traffic Safety, with partners NORC at the University of Chicago
Feeling sleepy, but not sure when to pull over? That’s what one recent study at NADS is analyzing, including:
• Drowsy driver decision-making over three-hour overnight drives (measured by frequency and duration of when subjects chose to take breaks),
• How aware drivers are of their own level of drowsiness (measured by eye-tracking data and head bobbing), and
• How their driving performance changes based on drowsiness (measured by control of lane position).
Drivers were given opportunities to stop at rest areas, get out of the simulator, eat, get caffeine, and take a nap if desired.
The team finished data collection in summer 2022 and is now completing data analysis.
Driver monitoring systems (DMS) use sensors to monitor the state of the driver and can then interact with the driver to enhance safety. Distraction, drowsiness, and other types of impairment can be detected with image-based measures (cameras on the driver), biological-based measures, or by vehicle-based measures (such as steering behavior).
The team is now synthesizing the literature, detailing system specifications, interviewing vehicle and system manufacturers, and detailing test protocols and procedures for DMS evaluation. These findings will inform the design of a driving simulator experiment to be conducted in 2024.
Sponsored by Toyota Collaborative Safety Research Center (CSRC)
“In this study, we’re modeling driver visual attention to understand visual behavior patterns that lead to noticing hazards,” explained Schwarz. “One goal is to warn drivers when they are inattentive in automated driving but need to monitor for hazards or take over.”
Drivers were told to monitor the automation and their environment while the vehicle was under Level 2 automation. They were engaged in a non-driving task on a cell phone through traffic jams, highway congestion, and at the end had a hazard (dead deer) in the road to avoid. Fifty-four percent of drivers did not notice the hazard and drove through it, and another 12 percent noticed it too late to avoid a collision.
The drivers’ gaze patterns were classified every 30 seconds to predict the chance that the driver would look up and see the hazard.
When a vehicle system receives an over-the-air (OTA) update, when do you need to give drivers additional training? That’s what a new project with the Toyota CSRC is analyzing. The project will consist of three phases:
1. Measuring the size of an OTA update to an advanced driver assistance system using a network analysis approach
2. Understanding the relationship between the size of an OTA update and driving performance
3. Measuring the effectiveness of different “quick-fix” driver training strategies for OTA updates
The theme this past year with much of our drugged-driving research has revolved around various methods of detecting driving impairment from cannabis use. We analyze blood, brain activity, and eye tracking data, and we associate that data with driving performance and divided attention while the subjects perform secondary tasks. A few projects from the past year include:
A project with Advanced Brain Monitoring is wrapping up with a publication and a “Best Scientific Paper” award at last year’s AAAM Annual Scientific Conference. In an important step toward identifying who is too impaired to drive, researchers found specific markers in brain activity linked to cannabis intoxication that consistently and negatively impact driving performance.
We ran a data collection with Acclaro and Cognitive Research Corporation for a NHTSA-funded project for the characterization of driving behavior under the influence of alprazolam and cannabis—two drugs known to impact driving-related skills. The NADS team developed scenarios and collected data from a small sample of subjects to evaluate the proposed methodology. The study was conducted using concurrent collection on three miniSims at NADS.
As part of a collaborative project between NADS, the University of Colorado Anschutz Medical Campus, Swinburne University (Australia), and Seeing Machines, the NADS team integrated the DMS developed by Seeing Machines into a miniSim and installed it at the University of Colorado Anschutz Medical Campus.
Data will be collected from cannabis users prior to and after acute administration of cannabis. The DMS data will be examined to identify ocular measures or eye behaviors that are indicative of impairment.
We are also conducting a set of studies with ISBRG Corp. evaluating the accuracy and precision of their device that involves the placement of a finger on the device to detect impairment from cannabis. The device uses advanced machine learning and optics to measure the absorbance and reflection of substances in the finger.
As of fall 2022, we’re more than halfway done with our 2.5-year ADS for Rural America project. This U.S. DOT-funded demonstration project is testing the use of automated driving technologies on rural roadways to examine and understand the unique needs of rural environments, while working toward solutions that improve safety and mobility.
Visit data.ADSforRuralAmerica.uiowa.edu to access our data portal.
Data has been augmented for ease of use and can be filtered using various criteria, including project phase, weather conditions, road type, and more. Additional functionality will be available in the coming year.
During every drive, the co-pilot monitors the operation of both the vehicle and the automation technology, in addition to being a second set of eyes and ears for the safety driver. Here’s an example of what the co-pilot sees on their tablet:
rear view
decision gate
route line (red), planning line (blue)
forward view blue means automation is engaged used by co-pilot to flag data obstacles detected and classified by software
While the red line is the route line that the vehicle is programmed to follow, the wider blue line is the planning line. The planning line reflects the vehicle’s real-time adjustments and position, and it takes into account obstacles. The decision gate indicates the decisions made by the software in reference to a detected obstacle, signage, or situation. When green, it’s making a decision to “follow.”
Farther to the right, the co-pilot taps the flag anytime something noteworthy happens, such as when the automation is disengaged or a vulnerable road user is passed. “The flags are synced with the rest of the data to allow us to easily access incidents that may be of interest for later analysis,” explained Cher Carney, project research lead.
Development of any new technology involves (really, requires) lessons learned along the way. Many of these lessons will be explored further in the remaining project phases. Here are some of those lessons learned so far:
Training and communication are imperative.
• Clearly define the roles for all team members.
• On-site staff should be trained to troubleshoot simpler issues.
• Close communication with technology provider is essential.
• Safety drivers need to have extensive experience and be intimately familiar with the operational design domain.
Conservative automation behavior is the norm.
• To have a vehicle drive autonomously at 65 mph in live traffic is a big deal. It took a lot of testing to raise it from the initial 50 mph max speed.
• Automation behavior is conservative for good reason (i.e., safety), but this means the vehicle is often very slow to start moving from stop signs and railroad crossings (at times to the frustration of drivers behind us).
Automation doesn’t adapt to poor weather conditions.
• The automation does not slow the vehicle for poor weather, slick surface conditions, or snow build-up on the road.
• Icy weather impacts sensor performance and can essentially blind the LiDAR. The photo to the right shows the ice build-up on the LiDAR, and the resulting LiDAR point cloud is shown below.
• The vehicle travels at the speed limit programmed into the HD map, regardless of approaching a blind corner or hill. Virtual speed limits must be added to the HD map to slow the vehicle down at these specific locations.
• On a narrow gravel road, humans drive near the center to avoid the edge of the road, where there can be looser gravel and steep drop-offs (unless approaching another vehicle or blind hill/corner, then they move over). The automation is currently being fine-tuned to reflect the way humans drive on gravel roads.
• Water spray from lawn sprinkler
• Dust clouds (on a gravel road)
The image below shows dust from a passing vehicle and how the LiDAR perceived that dust cloud, below that. The vehicle proceeded to slow to a stop.
Watch a video of the dust cloud encounter: dust cloud
• Pros: Cameras allow you to pick up the state of signal heads without any changes to physical infrastructure.
• Cons: There is a potential to pick up the wrong signal head from an adjacent lane, and the view can be blocked if behind a tall vehicle or near sharp elevation changes.
The vehicle may not be able to classify all objects and has slowed for:
A bioptic telescope (pictured) is used by drivers in some states to read road signs.
For drivers who are visually impaired, many states require the use of a bioptic telescope, which attaches onto eye glasses and are used to read road signs. Using them, however, can lead to lane position issues or a decrease in situational awareness.
In a study led by Mark Wilkinson, OD, FAAO, clinical professor of ophthalmology at University of Iowa Health Care, researchers are looking at the safety and effectiveness of the use of bioptic telescopes for wayfinding while driving.
The study is examining how drivers with and without visual impairments navigate while driving in an unfamiliar area, with the ultimate goal of finding safer alternatives
to the use of a bioptic telescope. While the use of a bioptic telescope for this purpose began in 1970, the advent of talking GPS navigation has eliminated the need for the use of a bioptic telescope. More importantly, a talking GPS allows drivers to keep their eyes on the road, a critical factor for safe driving—visually impaired or not.
“This study will provide information needed to support updating driving standards for individuals who are visually impaired, throughout the United States,” said Wilkinson.
The subjects—with and without bioptic telescopes, all of whom must be unfamiliar with local roads—complete two 35-minute drives during daylight hours. In
one drive, they follow instructions from an auditory GPS navigation device, and in the other they do not. The subjects are asked to identify a variety of signs along the road. Data is being collected to examine variables related to driving (i.e., gaze direction, eyes off road, eyes on road, missed turns, etc.).
NADS has a strong history of interdisciplinary driving research, including partnering with many other departments in the health sciences, such as:
• Neurology: Driving performance as a symptom of Parkinson’s disease
• Pharmacy: Effects of drug use on driving (alcohol, cannabis, prescriptions, and over-the-counter medications)
• Emergency Medicine:
• Drug prevalence in crash victims
• ATV safety
• Orthopedics and Rehabilitation: Driving after distal radius fractures
“Long-standing collaborations are essential to many of our projects,” noted Senior Research Associate Michelle Reyes, whose efforts often focus on safety and crash data research and analysis. Two longstanding partners for traffic safety research are the Iowa DOT and the University of Iowa Injury Prevention Research Center (IPRC).
For more than two decades, the Iowa DOT has been encouraging Iowa communities to consider converting certain four-lane streets to three lanes (also known as a “road diet”) with the aim to improve safety and reduce crashes.
Two areas of concern often raised by communities are the impacts on businesses and on emergency response. In a project recently completed for the Iowa DOT, a team of NADS and IPRC researchers including Reyes and Cara Hamann, PhD, investigated these impacts by surveying businesses and emergency responders in Iowa communities with recent lane conversions. They also analyzed emergency response time data.
The top findings included:
1. One-third of the business respondents reported positive or slightly positive effects, and another 38% thought the road conversion had no impact on their business.
2. Among emergency responders, 34% disagreed with keeping the conversion in place, while 30% agreed, and 28% were neutral.
3. Community education about what to do when emergency vehicles are on the road is important. Many responders with negative perceptions reported that drivers didn’t know where to move to yield to the responders, resulting in blocking lanes and slowing response.
4. Lane conversions had no measurable impact on fire department response times in Cedar Rapids, Iowa.
Effect of Seat Belt
Severity for Adult Rear-Seat Occupants Injured in Motor Vehicle Crashes: Analysis of Iowa crash data from 2016–2019 found, in part, that odds of a fatal injury were 6.2 times higher when adults in the rear seat were unbelted.
Sponsor: Iowa DOT; Partners: IPRC, Governor’s Traffic Safety Bureau
A Crash Data Dictionary was developed to document the data elements collected on the Iowa crash report form. The NADS/ IPRC team reported hundreds of findings, some of which are being implemented now, that have the potential to improve crash data quality in the future.
Sponsor: Iowa DOT; Partners: IPRC, Governor’s Traffic Safety Bureau
Instrumented Farm Vehicle Roadway Study: GPS/video devices were installed on Iowa farm equipment that collected data and recorded vehicles as they approached, followed, and began to pass farm equipment.
Sponsor: CDC/NIOSH and UI Great Plains Center for Agricultural Health; Partner: Iowa State University InTrans
FY22 resulted in a number of system upgrades and custom development for the miniSim team:
• A new feature called “Review” was added to the standard release, so users can review any drive on the main displays.
• Engineering students designed a new steering system for the Simplified Cab. This can be configured for either an aftermarket wheel or an OEM wheel with turn signal and wiper stalks.
• The team integrated another OEM driver monitoring system for use in driver impairment research.
• Three new custom scenarios for testing driver impairment were developed for a NHTSA-sponsored study in three languages: English, Spanish, and French.
• A new computer rack was designed to reduce cost and shipping expense.
New systems or upgrades:
• Cognitive Research Corporation
• Leidos, Inc.
• University of Toronto
• University of Kansas
• San Jose State University
• Westat, Inc.
• Transport Canada
• University of Hartford
• University of Windsor
The University of Toronto’s miniSim was originally delivered in 2013 to the Human Factors and Applied Statistics Lab in the Department of Industrial Engineering. It was upgraded on site in May 2022 with new PCs, steering system, dashboard, four-channel video recording, cameras, and a motion system with three degrees of freedom. Here are some photos of that upgrade process.
Left: Recent University of Iowa engineering graduate Aidan Keen installs the motion base system at the University of Toronto.
A new Interactive Scenario Authoring Tool (ISAT) Demo Scenario Library is making it easier to train users and answer commonly asked questions. In it, 33 demonstration scenarios cover the basics of scenario authoring, each accompanied by instructions for new users.
The miniSim instrument panel has also been enhanced to include odometer components (digit switches), and the initial mileage is now configurable by the user from the scenario. Scenario controls initialize the values (circled in blue below), and vehicle dynamics control the updates.
Users can also now customize the generic instrument panel (not pictured), where different icons can be used on the panel, and the center area can be customized.
A labeled “self-driving” vehicle can come with or without LiDAR on the roof, a driver, and a rear-seat occupant.
Ability to have a one-way loop drive, instead of two-way traffic: The driver is presented with navigation suggestions, but they may drive either route available.
Safety Research Using Simulation (SAFER-SIM) is a grant-funded Tier 1 University Transportation Center that shares its researchers' expertise with students and seasoned researchers alike. Led by the University of Iowa, SAFER-SIM comprises a multidisciplinary team of researchers across four additional consortium sites: University of Massachusetts–Amherst, University of Central Florida, University of Wisconsin–Madison, and University of Puerto Rico–Mayagüez.
SAFER-SIM supports research from a range of disciplines and state-of-the-art driving, bicycling, and pedestrian simulators and microsimulation to study the interactions among road users, roadway infrastructure, and new vehicle technologies.
Cost-Free STEM Activities for K–12 NADS and SAFER-SIM offer free STEM activities to schools and education groups across Iowa. These activities apply math and science concepts to real-world situations using our portable driving simulator. Our goal is to provide applications to students that teach them about careers, research, automated vehicles, and more.
“For many students that work with us, a SAFER-SIM project is their first project. We try to offer them many opportunities to present, network, and develop skills. We see them learn and grow as professionals, knowing they will become our colleagues when they graduate—and that is very rewarding.”
Emily Shull is a graduate research assistant at the National Advanced Driving Simulator and an industrial and systems engineering PhD student at the University of Iowa’s College of Engineering. Shull presented her research on “The Gap Effect in Shifting Attention in Conditional Automation,” a project funded by SAFER-SIM, at the International Conference on Traffic and Transport Psychology in Gothenburg, Sweden.
The presentation focused on how the driver can be aided in shifting attention from a distracting task back to the driving task in a safe and timely manner when the automation issues a request to intervene.
"The Gap Effect in Shifting Attention in Conditional Automation"
Using a Raspberry Pi and a fish-eye camera, three high school students this past summer made enhancements to a robot car, with the goal for it to autonomously back up a trailer between two lane lines.
The students used machine vision software, which the robot vehicle used to detect the lane lines and look for symmetry to center itself in the lane.
The internships were funded by SAFER-SIM, in partnership with Workplace Learning Connection.
Spearheaded by the Iowa DOT, the Iowa Advisory Council on Automated Transportation (ATC) is setting the course for the future of automated transportation in Iowa. The University of Iowa assists with management and logistics, while also providing expertise in vehicle safety, policy, and education.
Long-time NADS staff member Cherie Roe, whose title is now AV transportation & outreach specialist, is now supporting the Iowa ATC by facilitating various committee and working group meetings and assisting with the ATC newsletter. “[This work] strengthens our relationship with the Iowa DOT when doing automated driving research, and it keeps us in the loop on AV activity across the state,” said Roe.
To understand how digital twins are used in transportation, Chris Schwarz, PhD, director of engineering and modeling research, and Ziran Wang, PhD, of Toyota Motor North America–InfoTech Labs, published a magazine article titled “The Role of Digital Twins in Connected and Automated Vehicles” in IEEE Intelligent Transportation Systems Magazine
We thank you!
Linda Angell
President and Principal Scientist Touchstone Evaluations, Inc.
Stacy Balk
National Highway Traffic Safety Administration (NHTSA)
Tom Banta
Vice President, Director Strategic Growth Iowa City Area Development Group
Pujitha Gunaratne
Senior Executive Engineer Toyota Collaborative Safety Research Center
Terry Johnson
Chief Financial Officer and Treasurer University of Iowa
Gary Kay President
Cognitive Research Corporation
Scott Marler Director Iowa Department of Transportation
Brian Philips
Senior Research Psychologist NHTSA, Turner-Fairbank Highway Research Center
Ned Bowden
College of Liberal Arts and Sciences Chemistry
Carri Casteel
College of Public Health Injury Prevention Research Center
Venanzio Cichella College of Engineering Mechanical Engineering
Alejandro Comellas Freymond Carver College of Medicine Internal Medicine
Soura Dasgupta College of Engineering Electrical and Computer Engineering
Jeffrey Dawson College of Public Health Biostatistics
Gary Gaffney
Carver College of Medicine Psychiatry
Amanda Haes
College of Liberal Arts and Sciences Chemistry
Cara Hamann
College of Public Health, Epidemiology Injury Prevention Research Center
Loreen Herwaldt
Carver College of Medicine Internal Medicine
Karin Hoth Carver College of Medicine Psychiatry
Joseph Kearney
College of Liberal Arts and Sciences Computer Science
Gary Milavetz
College of Pharmacy Pharmacy Practice and Science
Nicholas Mohr
Carver College of Medicine Emergency Medicine
David Nembhard
College of Engineering Industrial Engineering and Business Analytics
Jodie Plumert
College of Liberal Arts and Sciences Psychological and Brain Sciences
Thomas Schnell College of Engineering Industrial and Systems Engineering
Gregory H. Shill College of Law Corporate Governance and Control
Ann Ricketts Division of Sponsored Programs University of Iowa
Trent Victor Director of Safety Waymo
C.Y. David Yang Executive Director AAA Foundation for Traffic Safety
Steven Spears
Graduate College School of Planning and Public Affairs
Ergun Uc Carver College of Medicine Neurology
Shaun Vecera
College of Liberal Arts and Sciences Psychological and Brain Sciences
Chao Wang College of Engineering Industrial and Systems Engineering
Mark Wilkinson Carver College of Medicine Ophthalmology
Xun Zhou Tippie College of Business Management Science
Oregon State University
David Hurwitz
University of California, Irvine Federico Vaca
University of Central Florida
Mohamed Abdel-Aty
Naveen Eluru
Zhaomiao (Walter) Guo Samiul Hasan
Amr Oloufa Omer Tatari Yina Wu
Lishengsa Yue Mohamed Zaki
University of Colorado Anschutz Medical Campus
Ashley Brooks-Russell Michael Kosnett
University of Leeds Natasha Merat Richard Romano
University of Massachusetts–Amherst Chengbo Ai
Eleni Christofa Cole Fitzpatrick Michael Knodler
Anuj Pradhan Shannon Roberts
University of Puerto Rico–Mayagüez Carla López
Alberto M. Figueroa Medina Benjamin Colucci-Rios Didier Valdés
University of Washington Linda Ng Boyle
AAA Foundation for Traffic Safety
Acclaro Research Solutions, Inc.
Advanced Brain Monitoring
Aisin Technical Center of America, Inc.
American University of Sharjah
A.T. Still University of Health Sciences
Battelle Memorial Institute
Booz Allen Hamilton, Inc.
Charles River Associates
Cognitive Research Corporation
Colorado Department of Public Health and Environment
Colorado Department of Transportation Colorado State University
Dunlap and Associates, Inc.
Exponent
Federal Law Enforcement Training Centers
Federal Transit Administration
Federal Highway Administration
General Motors Corporation
Georgia Institute of Technology
Governor’s Traffic Safety Bureau
Hexagon | AutonomouStuff
Hyundai America Technical Center, Inc.
Iowa City Area Development Group
Iowa Department of Transportation
Iowa Governor’s Traffic Safety Bureau
Iowa State University
ISBRG Corp.
Leidos, Inc.
Lenstec, Inc. Loyola Marymount University Mandli Communications
Massachusetts Department of Transportation Massachusetts Institute of Technology MetroPlan Orlando
Michigan Technological University National Highway Traffic Safety Administration
National Institute for Occupational Safety and Health
National Institute on Drug Abuse NORC at the University of Chicago
Oakland University
Office of the Assistant Secretary for Research and Technology
Purdue University
San Jose State University State Farm Swinburne University of Technology
Tongji University toXcel
Toyota Collaborative Safety Research Center
Transport Canada University of Hartford
University of Wisconsin–Madison
Madhav Chitturi
John D. Lee
Dan Negrut David Noyce
Jon Riehl
Kelvin R. Santiago Radu Serban
Volpe National Transportation Systems Center
Donald Fisher Xavier University Ryan Miller Yale University Barbara Banz
University of Kansas University of New Hampshire University of Toronto University of Windsor U.S. Department of Transportation U.S. Department of Homeland Security Veterans Affairs Volpe National Transportation Systems Center
Wisconsin Department of Transportation Workplace Learning Connection Westat, Inc.
University of Iowa
National Advanced Driving Simulator
2401 Oakdale Boulevard Iowa City, Iowa 52242 nads.uiowa.edu
The University of Iowa prohibits discrimination in employment, educational programs, and activities on the basis of race, creed, color, religion, national origin, age, sex, pregnancy, disability, genetic information, status as a U.S. veteran, service in the U.S. military, sexual orientation, gender identity, associational preferences, or any other classification that deprives the person of consideration as an individual. The university also affirms its commitment to providing equal opportunities and equal access to university facilities. For additional information on nondiscrimination policies, contact the Director, Office of Institutional Equity, the University of Iowa, 202 Jessup Hall, Iowa City, IA 52242-1316, 319-335-0705, oie-ui@uiowa.edu.