SCC-CIVIC-FA Track B: Community Informed AI-Based Vehicle Technology Simulator with Behavioral Strategies to Advance Neurodiverse Independence and Employment
Lead PI:
Nilanjan Sarkar
Co-Pi:
Abstract

One in 36 individuals in the US has autism spectrum disorder (ASD). Each year in the US, approximately 70,000 autistic children become autistic adults and face a litany of disheartening statistics regarding independent living, community participation, and employment. The estimated cost of supporting Americans with autism having limited employment prospects will grow to $461 billion per year by 2025. One key to addressing this civic challenge is employment; some 85 percent of autistic adults are un/under-employed, and adults with autism rate employment as their top concern for improved quality of life. However, a major impediment for autistic individuals to access work opportunities and a life of independence, is lack of independence with transportation; fewer than 30 percent of driving-age autistic individuals are licensed to drive. The CIVIC Stage 2 award to Vanderbilt University will support the rapid pilot deployment of the team’s AI-based Vehicle Technology Simulator with Behavioral Strategies (AI-VTSBS) system, specifically designed for the ASD population – comprising a virtual-reality driving simulator with artificial intelligence-based analysis and feedback, together with a curriculum built on a cognitive behavioral intervention for driving – to address this critical civic need. The project will perform community-based participatory research including multiple stakeholders to make the AI-VTSBS system adaptable to use within multiple employment contexts and multiple employment outcomes of relevance to stakeholder communities. 

The team led by Vanderbilt University and partner San Diego State University will build on its work on Stage 1 and will conduct a full Stage 2 pilot deployment with multiple types of civic partners and support providers – including community-based vocational training centers, behavioral health clinics, and secondary schools – toward an effective, low-cost, commercializable, integrated driving-instruction platform and curriculum, with a value proposition that offers increased independence and expanded career options for autistic people. The Stage 2 research pilot project will use an implementation science framework involving Exploration, Preparation, Implementation and Sustainment (EPIS) to specifically assess and pilot-test deployment factors with both qualitative and quantitative methods. Additionally, the AI-VTSBS technology may also be generalizable beyond adults with autism; some 1 in 6 people have a related neurodevelopmental disability (e.g., ADHD) or temporary cognitive impairment (e.g., traumatic brain injury) that manifest similar challenges for transportation independence. The CIVIC Stage 2 work will be integrated with the NSF NRT program in Neurodiversity Inspired Science & Engineering (NISE) through Vanderbilt University’s Frist Center for Autism & Innovation, thus providing advanced training for students in interdisciplinary research and translation.

CIVIC is a joint collaboration with Department of Energy, Department of Homeland Security, and the National Science Foundation

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Nilanjan Sarkar
I am interested in the analysis, design, and development of intelligent and autonomous systems that can work with people in a versatile and natural way. The applications of this research range from helping individuals with autism and other developmental disabilities in learning skills, aiding stroke patients to regain some of their movement abilities through robot-assisted rehabilitation, and providing more autonomy in robots for a variety of tasks. We are developing new generations of robots and computer-based intelligent systems such as virtual reality systems that can sense human emotion from various implicit signals and cues such as one’s physiology, gestures, facial expressions and so on, to be able to interact with people in a smooth and natural way. My current research involves both theoretical analysis and experimental investigation of electromechanical systems, sensor fusion and machine learning, modeling of human-robot and human-computer interaction, kinematics, dynamics and control theory leading to the development of these smart systems.
Performance Period: 10/01/2023 - 02/28/2025
Institution: Vanderbilt University
Award Number: 2322029