Validating Drone Trust Testing in Navigation Deviation Cases in Simulation

TL;DR

This paper explores the effectiveness of using realistic simulation environments to evaluate user trust in drones experiencing path deviations, aiming to replace costly and risky real-world testing.

Contribution

It proposes a method to test and evaluate user trust in simulated drone path deviations, expanding previous models to more complex scenarios.

Findings

Simulations can effectively replicate trust results from real-world tests.

Realistic environments improve the validity of trust assessments.

Simulation-based testing reduces costs and safety risks.

Abstract

Developing videos for trust testing is very time-consuming, expensive and potentially dangerous. For trust tests, it requires a person to be flying the drone while another might be filming. The drones can be very expensive and if something goes wrong the costs might be very high. In previous work, we have looked at how collisions and basic communication loss can be accurately modeled in simulation and to be able to generate the same trust results from users. That work looked at two specific cases using two drones, but to expand upon this in other cases more testing is required. This paper looks to propose how to test and evaluate the change in user's trust of a drone when it is experiencing path deviation in simulation. If the environment is very realistic can simulations be a good alternative to real life videos for trust testing when there is path deviation? This deviation can occur due to the physical conditions of the space, faulty piloting, or communication loss.