Design of a Physiology-based Adaptive Virtual Reality Driving Platform for Individuals with ASD

Author:

Bian Dayi1ORCID,Wade Joshua2,Swanson Amy3,Weitlauf Amy4,Warren Zachary5,Sarkar Nilanjan6

Affiliation:

1. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN

2. Department of Mechanical Engineering, Vanderbilt University, Nashville, TN

3. Treatment and Research Institute for Autism Spectrum Disorders (TRIAD), Vanderbilt University, Nashville, TN

4. Department of Pediatrics, Treatment and Research Institute for Autism Spectrum Disorders (TRIAD), Vanderbilt University, Nashville, TN

5. Department of Pediatrics, Department of Psychiatry, Treatment and Research Institute for Autism Spectrum Disorders (TRIAD), Vanderbilt University, Nashville, TN

6. Department of Electrical Engineering and Computer Science, Department of Mechanical Engineering, Vanderbilt University, Nashville, TN

Abstract

Driving is essential for many people in developed countries to achieve independence. Individuals with Autism Spectrum Disorder (ASD), in addition to having social skill deficits, may experience difficulty in learning to drive due to deficits in attention-shifting, performing sequential tasks, integrating visual-motor responses, and coordinating motor response. Lacking confidence and feeling anxiety further exacerbates these concerns. While there is a growing body of research regarding assessment of driving behavior or comparisons of driving behaviors between individuals with and without ASD, there is a lack of driving simulator that is catered toward the needs of individuals with ASD. We present the development of a novel closed-loop adaptive Virtual Reality (VR) driving simulator for individuals with ASD that can infer one's engagement based on his/her physiological responses and adapts driving task difficulty based on engagement level in real-time. We believe that this simulator will provide opportunities for learning driving skills in a safe and individualized environment to individuals with ASD and help them with independent living. We also conducted a small user study with teenagers with ASD to demonstrate the feasibility and tolerability of such a driving simulator. Preliminary results showed that the participants found the engagement-sensitive system more engaging and more enjoyable than a purely performance-sensitive system. These findings could support future work into driving simulator technologies, which could provide opportunities to practice driving skills in cost-effective, supportive, and safe environments.

Funder

National Institutes of Health

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Human-Computer Interaction

Reference57 articles.

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1. Exploring the Intersection of Autism, Theory of Mind, and Driving Performance in Novice Drivers;Journal of Autism and Developmental Disorders;2024-08-28

2. The Technology to Enhance Patient Motivation in Virtual Reality Rehabilitation: A Review;Games for Health Journal;2024-08-01

3. Machine Learning Application for Real-Time Simulator;2024 9th International Conference on Machine Learning Technologies (ICMLT);2024-05-24

4. Virtual Reality Adaptive Training for Personalized Stress Inoculation;Human Factors: The Journal of the Human Factors and Ergonomics Society;2024-03-28

5. Stress Detection of Autistic Adults during Simulated Job Interviews Using a Novel Physiological Dataset and Machine Learning;ACM Transactions on Accessible Computing;2024-03-18

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