Modeling the Interplay of Trust and Attention in HRI: an Autonomous Vehicle Study, Indu P Bodala, Bing Cai Kok, Weicong Sng, Harold Soh, Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’20

In this paper, we develop a probabilistic model that captures how trust and attention in human robot interaction evolves over time. Within the context of human interaction with autonomous vehicles, we model the trust and attention as latent variables, with the decision to takeover control depending on the trust and attention. We split interactions into a “learning phase” (where users passively observe the autonomous vehicle) and a subsequent “interaction phase” (where users are allowed to take control of the vehicle). We validate our model with a human-subjects study, which revealed that higher trust lead to lower levels of attention and higher cognitive workload lead to lower attention.

## Resources

You can find our paper here. Check out our repository here on github

## Citation

Please consider citing our paper if you build upon our results and ideas.

Indu P Bodala, Bing Cai Kok, Weicong Sng, Harold Soh, “Modeling the Interplay of Trust and Attention in HRI: an Autonomous Vehicle Study”, Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’20

 @inproceedings{Bodala_Kok_Sng_Soh_2020, address={New York, NY, USA}, series={HRI ’20}, title={Modeling the Interplay of Trust and Attention in HRI: An Autonomous Vehicle Study}, ISBN={978-1-4503-7057-8}, url={http://doi.org/10.1145/3371382.3378262}, DOI={10.1145/3371382.3378262}, abstractNote={In this work, we study and model how two factors of human cognition, trust and attention, affect the way humans interact with autonomous vehicles. We develop a probabilistic model that succinctly captures how trust and attention evolve across time to drive behavior, and present results from a human-subjects experiment where participants interacted with a simulated autonomous vehicle while engaging with a secondary task. Our main findings suggest that trust affects attention, which in turn affects the human’s decision to intervene with the autonomous vehicle.}, booktitle={Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction}, publisher={Association for Computing Machinery}, author={Bodala, Indu P. and Kok, Bing Cai and Sng, Weicong and Soh, Harold}, year={2020}, month={Mar}, pages={145–147}, collection={HRI ’20} }