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Human Mobility Modeling for Robot-Assisted Evacuation in Complex Indoor Environments | IEEE Journals & Magazine | IEEE Xplore

Human Mobility Modeling for Robot-Assisted Evacuation in Complex Indoor Environments


Abstract:

A large number of injuries or deaths may occur when an emergency happens in a crowded public place. The congestion at exits may slow down the egress rate due to the effec...Show More

Abstract:

A large number of injuries or deaths may occur when an emergency happens in a crowded public place. The congestion at exits may slow down the egress rate due to the effect of “faster-is-slower”. This inspires us to study how human behavior dynamically changes over time at an emergency in a complex indoor environment. In this paper, we refer the panic of evacuees to their perception of the threat and propose a panic propagation model to model how crowd panic changes during evacuation at an emergency. Combined with the existing social force model, our panic model interprets the self-driven force and interactive forces with others in human mobility. To improve evacuation efficiency, robots are introduced to guide evacuees to escape. Using dynamic environment information, we design an evacuation exit selection algorithm where the optimal exit is automatically selected by the robot with the minimum escape time. In our experiments, a real shopping mall is examined, and the dynamic behavior of panicked evacuees is simulated with the proposed panic model. The evacuation performance of using emergency evacuation robots is evaluated. The improvement of evacuation efficiency validates the effectiveness of our robot-assisted evacuation system.
Published in: IEEE Transactions on Human-Machine Systems ( Volume: 46, Issue: 5, October 2016)
Page(s): 694 - 707
Date of Publication: 06 June 2016

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I. Introduction

An emergency happening in crowds, such as a fire or an explosion, may lead to a large number of injuries and deaths. Recent studies and investigations performed after crowd disasters suggest that well-trained agents, such as fire wardens and firemen, can significantly improve the survival rate in such crowd disasters [1], [2]. However, although the agents can guide evacuees to the closest exit, they may not be aware of the congestion at that exit, which may delay the evacuation. To avoid heavy congestions at exits, evacuation flows to all exits should be carefully organized. With recent rapid development on sensors and network technologies, it is possible to install cameras or other surveillance sensors widely at exits in buildings, if not existing already. With such surveillance capabilities, we believe intelligent emergency evacuation robots can offer evacuees better guidance with the updated environment information, compared to traditional guidance from stationary signs or agents.

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