CHS: Small: Improving user trust of autonomous vehicles through human-vehicle collaboration

University Of Maine, Orono ME

Investigators

Abstract

Fully autonomous vehicles (FAVs) represent a key future direction for transportation, especially for populations who are currently disenfranchised by traditional, manually operated vehicles, such as those with visual impairments or older adults. Unfortunately, the benefits of self-driving technology for these demographics have yet to be adequately considered in the design of FAVs. This concern is part of a larger problem in which the majority of people simply do not trust that self-driving cars will meet their needs. This project explores new ways to share decision-making information between people and FAVs. Instead of existing systems where the FAV makes the decisions in a "black box" way that users don't see or understand, the project will develop a Human-Vehicle Collaboration (HVC) framework in which effective communication about the vehicle's decision-making process improves users' sense of agency and decisions around trusting the FAV. Through studying people's reactions to and understanding of FAV driving decisions and developing algorithms and interfaces that help FAVs communicate in ways that address them, the HVC framework will promote appropriate levels of trust in FAVs for all users, while providing substantial benefits around improving accessibility for under-served populations. The HVC framework will be designed and evaluated using a high-fidelity driving simulator that tests new interaction methods for sharing information during key driving events. Research will use this simulator and experimental platform to manipulate a host of variables relating to decision states while driving. Human data will be collected on reaction time, interpretation of vehicle decision-making, physiological measures based on galvanic skin response and heart rate, as well as pre-post survey measures for assessing trust in fully-autonomous vehicles. Results will form the foundation for developing and testing HVC profiles that provide individualized interactions and collaborations during driving events. These profiles and the resulting guidelines represent a key deliverable for the project as they will be designed from the outset to improve trust, accessibility, and the overall optimization of fully-autonomous vehicles. 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.