Human Performance
By integrating engineering ideals with influences from areas like psychology, sociology and kinesiology, CAVS has developed a wide range of capabilities to support active research in areas of athlete engineering and human factors engineering. CAVS’ Human Factors group explores human-machine interactions, including those between autonomous vehicles, pedestrians and passengers. Using a variety of research tools such as virtual reality, augmented reality and a full-function driving simulator, the Human Factors research team explores the impacts of connected and autonomous technology on both the usability and safety of vehicles and systems.
Motion Capture
The CAVS Human Performance Laboratory is equipped with a 12-camera Vicon passive marker-based motion capture system with integrated Noraxon wireless electromyography (EMG), Innovative Sports Training’s Motion Monitor xGen motion analysis software, and Dual Kistler force plates. With this equipment we can collect kinetic, kinematic, and physiological data using gold standard technologies. Current research using these tools include validation of novel technologies such as stretch sensor-based socks for measuring gait, compression shorts for tracking muscle activity, and flexible barbells for strength training.
Virtual Reality
The CAVS Human Performance Laboratory is equipped with two HTC Vive headsets, one wireless HTC Vive Pro headset, three Oculus Rift headsets, and one Oculus Quest headset. With a VR headset, we’re able to emerge a test subject into a situation and evaluate how they react to their environment, while alleviating limiting factors like risk of potential injury, time associated with experiment replication and additional costs. Current CAVS research areas involving virtual reality include data visualization and studies on to pedestrian reactions to autonomous vehicles.
Augmented Reality
CAVS is equipped with two Microsoft HoloLens headsets and two Magic Leap One Creator Edition headsets for augmented reality research. The technology allows researchers to overly digital imagery and data into existing reality. Ongoing research includes using augmented reality in education and workplace training, as well as how to increase augmented reality compatibilities with the natural eye.