Abstract
Evacuation robots hold promise for facilitating efficient and safe building evacuations during emergencies. While studies have demonstrated that people will follow an evacuation robot [Nayyar 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN):1–6, 1, Robinette et al. 2016 11th ACM/IEEE International Conference On:101–108, 2], many practical hurdles remain. This paper uses a human subject study in a physical environment to investigate robot-guided evacuation of individuals versus small groups and considers different strategies for using robots to guide evacuees to exits. We further show that the data collected from these human subject studies can be used to train evacuee motion models which accurately predict the movement of the evacuee (9.9 cm mean error) while following the robot. We further show that this model can be used to predict the motion of an evacuee in a different environment and show that the accuracy of our model is superior to the more standard social forces model (SFM). The results from this research will contribute to the creation of evacuation robots and to the modeling and prediction of evacuee behavior.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3155-3171 |
| Number of pages | 17 |
| Journal | International Journal of Social Robotics |
| Volume | 17 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2025 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- General Computer Science
- Social Psychology
- Philosophy
- Human-Computer Interaction
- Electrical and Electronic Engineering