Exploratory Advanced Research . . . Next Generation Transportation Solutions

If there were only fully automated vehicles, an

intersection could, in theory, greatly reduce

wait times and traffic congestion. Yet even

one manually driven vehicle can greatly

reduce these benefits. Legacy vehicles will be

on the road for years to come, so researchers

at the University of Texas at Austin are

examining how to accommodate both fully

automated and manually driven vehicles on

the road in their research project,

“Collaborative Research: Synergy: Augmented

Reality for Control of Reservation-Based

Intersections with Mixed AutonomousNonautonomous Flows.”

The researchers will use an intersection

control system to transmit a time reservation

to fully automated vehicles and use

augmented reality and a heads-up display,

such as a projection on the windshield, to

notify the human drivers to either speed up or

slow down to drive through the intersection at

their appointed time. This smart intersection

concept would also incorporate nonmotorized

travelers, who would be connected through

augmented reality goggles or their

smartphones. These devices would then

communicate to the pedestrian or the bicyclist

when to cross.

The researchers will develop algorithms based

on human behavior that will help guide

vehicles and humans through the intersection

safely and efficiently. The next phase of the

research project will involve experimenting

with these algorithms with human participants

outfitted with augmented reality devices in

vehicles and on their person. 

Exploring Human Behavior and Trust 

with Autonomous Vehicles

Current research with automated vehicles and

human occupants has focused on how humans

rely on automation, e.g., feeling comfortable

enough to take a nap while the vehicle is in

motion. Yet little research has examined when

In collaboration with the National Science

Foundation (NSF), the Exploratory Advanced

Research (EAR) Program at the Federal

Highway Administration (FHWA) is supporting

two research projects, one led by the University

of Texas at Austin and a second led by the

University of Wisconsin–Madison, which explore

how to use automated vehicles to increase road

safety and improve traffic flow and efficiency.

Smart Intersections for Automated 

and Legacy Vehicles

Automated vehicles create a challenge for

traffic at signalized intersections. A reservation

system, where vehicles enter an intersection at

a specified time, can increase the free flow of

traffic. This system could allow for signalized

traffic control at intersections that have no

physical traffic signals.

The past few years have seen a steady 

increase in automation in America’s 

cars. Many modern vehicles include 

partial automation technologies, such as 

adaptive cruise control and lane keeping 

assist. A small, select number of fully 

automated vehicles are in pilot use, and 

in the future that number will grow, 

bringing with it numerous benefits, 

including increased safety through a 

significant reduction in vehicle crashes, 

smoother traffic flow, and increased 

mobility for seniors and disabled people.1 

Even with the increase in autonomous 

vehicles on the road, there will still be 

vehicles driven by humans as well as 

other road users such as pedestrians

and bicyclists. Researchers need to study 

this interaction between human drivers 

and autonomous vehicles, since it is not 

yet known how human drivers will 

respond to more autonomous vehicles

on the road.

The Exploratory Advanced Research Program Fact Sheet

Preparing Our Nation’s Roadways

for Advanced Vehicle Technologies
humans feel 

discomfort and 

mistrust with 

vehicle automation 

and the resulting 

impact on traffic. 

One example of 

this mistrust would 

be a human 

occupant in an 

automated vehicle 

which is traveling 

in the middle of a 

platoon of 

automated vehicles. The platoon may decide to 

slow down, but the human occupant in the 

middle car may decide the automated vehicle is 

not braking enough and decide to take over 

control and apply the brakes harder. The result 

of this action could cause a chain reaction 

within the platoon, as well as outside of the 

platoon, tying up traffic.

For the research project, “Identifying, 

Characterizing, and Shaping Multi-Scale 

Cyber-Human Interactions in Mixed 

Autonomous/Conventional Vehicle Traffic,” 

researchers at the University of WisconsinMadison are exploring what makes human 

drivers lose trust in vehicle automation, leading 

the driver to intervene unnecessarily. The 

researchers are exploring scenarios that include 

human drivers in both fully automated and 

manually controlled vehicles and how erroneous 

human interventions could negatively impact 

traffic flow. With more automated vehicles on 

the roadways in the upcoming decades, 

researchers are interested in increasing trust in 

automated vehicles which would then help 

improve traffic flow. 

In the first phase of the project, the researchers 

are using a driving simulator and software to 

simulate traffic, providing the capability to test 

automated vehicle algorithms and humandriven vehicle simulations safely and efficiently. 

For the next phase of this project, the

researchers are designing experiments to

include human participants in controlled

field tests.

Learn More

For more information about these EAR 

Program projects, contact Gene McHale, 

FHWA Office of Operations Research 

and Development at 202-493-3275 

(email: gene.mchale@dot.gov).

Publication No. 

FHWA-HRT-20-049

HRTM-30/08-20(WEB)E

Preparing Our Nation’s Roadways

for Advanced Vehicle Technologies

What Is the Exploratory 

Advanced Research Program?

The EAR Program addresses the

need for longer term, higher risk

research with the potential for

transformative improvements to

transportation systems. The EAR

Program seeks to leverage advances

in science and engineering that

could lead to breakthroughs for

critical, current, and emerging issues

in highway transportation by experts

from different disciplines who have

the talent and interest in researching

solutions and might not do so

without EAR Program funding.

To learn more about the EAR 

Program, visit https://highways.dot.

gov/research/exploratoryadvanced-research. The website 

features information on research 

solicitations, updates on ongoing 

research, links to published 

materials, summaries of past EAR 

Program events, and details on 

upcoming events.

EXPLORATORY ADVANCED RESEARCH

Photo credit, page 1: 

© University of Wisconsin–

Madison. Researchers at the 

University of Wisconsin–

Madison are studying when 

and why humans 

erroneously mistrust 

autonomous vehicle 

behavior.

1 National Highway Traffic Safety Administration. Automated Vehicles for Safety [Text]. NHTSA. https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety, 

last accessed June 8, 2020.

© University of Texas at 

Austin. Transportation 

researchers are developing 

smart intersection 

technology that will allow 

both autonomous and 

legacy vehicles to cross an 

intersection without the use 

of physical traffic signals.