Congestion-aware Evacuation Routing using Augmented Reality Devices
Zeyu Zhang, Hangxin Liu, Ziyuan Jiao, Yixin Zhu, Song-Chun Zhu
Abstract
We present a congestion-aware routing solution for indoor evacuation, which produces real-time individual-customized evacuation routes among multiple destinations while keeping tracks of all evacuees’ locations. A population density map, obtained on-the-fly by aggregating locations of evacuees from user-end Augmented Reality (AR) devices, is used to model the congestion distribution inside a building. To efficiently search the evacuation route among all destinations, a variant of A⋆ algorithm is devised to obtain the optimal solution in a single pass. In a series of simulated studies, we show that the proposed algorithm is more computationally optimized compared to classic path planning algorithms; it generates a more time-efficient evacuation route for each individual that minimizes the overall congestion. A complete system using AR devices is implemented for a pilot study in real-world environments, demonstrating the efficacy of the proposed approach.
BibTeX
@inproceedings{icra2020_congestionawaree,
title = {Congestion-aware Evacuation Routing using Augmented Reality Devices},
author = {Zeyu Zhang and Hangxin Liu and Ziyuan Jiao and Yixin Zhu and Song-Chun Zhu},
booktitle = {ICRA 2020},
year = {2020}
}