The Human Factors Laboratory uses state-of-the-art tools and virtual and real-world methodologies to conduct behavioral research on drivers, pedestrians, bicyclists, and other road users. From this research, the Human Factors team identifies solutions to potential safety concerns in existing and future roadway scenarios.

Research topics explored in this laboratory include driver comprehension of roadway infrastructure and roadway signs, human factors issues related to heavy-vehicle operations and driving automation, and vulnerable road-user safety.

Human Factors researchers use the operator station to monitor and communicate with test participants inside the vehicle's cab.

This simulator features a complete automobile chassis surrounded by seven 4K laser projectors that project a simulated roadway to a 210-degree field-of-view screen. The vehicle is on a six-degree-of-freedom motion base that provides pitches and surges (to simulate acceleration and braking), lateral, roll, yaw (to mimic curves), and heave cues (for bumps), which are synchronized with the visual environment.

The results of the Human Factors Laboratory's research efforts have been incorporated into the Manual on Uniform Traffic Control Devices (MUTCD) guidance document, design guidance for novel interchange signing, and rulemaking decision processes.

The bicycle simulator provides a safe, easy-to-manipulate environment for researchers to study bicyclist behavior. This simulator, or virtual reality (VR) bike, exposes participants to roadway hazards and traffic while cycling and tests their reactions to new technology, traffic signs, road signage, and lane markings. It consists of a stationary bicycle and a VR headset. Researchers deliver physical alerts to participants using vibrating cuffs attached to the bicycle's handlebars.

This system can test different driving scenarios within a minimal space. It provides test participants with 360-degree visualization of a vehicle and roadway, a steering wheel, and foot pedals to control the virtual vehicle. The VR driving system also includes an adjustable seat. A dual-infrared camera system on the headset tracks the driver's hands.

This equipment allows researchers to study full pedestrian mobility within virtual worlds that include large-scale or complex environments. The treadmill implements a high-precision tracking system that uses six optical motion sensors and an optical rotation sensor to allow researchers to track movement through the virtual space.

The Evaluation of Additional Alternatives of and Arrow Sizes for Overhead Arrow-per-Lane (OAPL) Guide Signs project examined drivers' comprehension of sign alternatives and roadway geometry, time for comprehension, and preference among arrow sizes and sign alternatives.

The Human Factors team systematically evaluated drivers' comprehension of and legibility for a large variety of signs, including 84 recreational and cultural interest signs currently in use by the National Park Service. The team has also worked with various State departments of transportation to conduct research that aided in the deployment of safe and innovative intersection designs with appropriate signing, including the diverging diamond interchange and reversible left turn lanes.

This driving simulator includes gas and brake pedals, an instrument cluster for displaying speed and other information, and an in-vehicle touchscreen display. Simulated roadways are displayed on three 48-inch high-definition screens. The driver experiences the feel of the road through a subwoofer in the simulator's base.

In this portion of the laboratory, researchers test a driver's comprehension of signs and intersections. Additionally, researchers study sign legibility, visibility, and infrastructure design through visual display of the information. Legibility software is used to assess participant attitudes and behaviors.

FRVs are used on real roadways to collect, record, and analyze multiple vehicle measurements, such as steering wheel angle, vehicle speed, accelerator position, brake usage, distance traveled, turn signal usage, and steering wheel button usage. These vehicles enable researchers to better understand driver behavior and performance.

Each FRV is equipped with an eye-tracking system consisting of two infrared light sources and three face cameras mounted on the vehicle dashboard. The cameras track the driver's head position and gaze without interfering with normal driver behavior. Eye tracking in FRVs helps researchers study driver perception and attention when the drivers are traveling on actual roadways.

Human Factors researchers explore human performance using cutting-edge cooperative adaptive cruise control (CACC) technology. CACC enables vehicles to follow each other more closely and accurately than conventional cruise control. This technology improves traffic flow and allows drivers to safely use their cruise control at shorter gap settings.

To simulate high-risk crash scenarios involving vulnerable road users (VRUs), researchers use testing devices that simulate an adult pedestrian, a child pedestrian, and an adult-sized bicycle driven by a belt system. Each device uses a rig and belts to support speeds of up to 20 kilometers per hour.

The rig can be triggered manually or automatically through a field research vehicle traveling past light bar sensors to perfectly time different conflict scenarios.

Sensors in autonomous vehicles can detect the devices to advance research on the interaction between VRUs and autonomous vehicles.