# Integrating Decentralized Indoor Evacuation with Information Depositories in the Field
## 2 Related Work
### Evacuation Models and Crowd Dynamics  
[PERSON] et al. [16] identified three purposes of evacuation models: (a) performance-based analysis for new and existing buildings in order to evaluate the design and evacuation procedures (e.g., [17; 18]), (b) forensic analysis to reconstruct historical evacuation processes in order to analyze possible failures and inefficiencies (e.g., [19]), and (c) management during evacuation procedures (e.g., [20]). The detailed assessments of the existing modeling approaches and simulation models can be found in the literature [21; 22; 23; 24]. Evacuation models can be roughly categorized into microscopic models and macroscopic models, which simulate crowd movement in emergency situations with different levels of abstraction. In microscopic models, the evacuating population is considered to be discrete individuals, and collective phenomena emerge from the interactions between individuals. Macroscopic models capture the evacuation situation from a global perspective and represent collective phenomena directly [21; 22]. Examples of microscopic models are cellular automata models (e.g., [10; 25; 26; 27; 28; 29; 30; 31]), lattice gas models (e.g., [32]), social force models (e.g., [4; 11; 33; 34; 35]), motion planning with velocity obstacles (e.g., [36; 37]), agent-based models (e.g., [38; 39; 40]), game theoretic models (e.g., [41; 42; 43]), approaches based on experiments with animals (e.g., [44; 45; 46; 47]), and hybrid models (e.g., [48]). Cellular automata models and lattice gas models partition the space into grids or hexagons. Evacuees are supposed to move from one cell to another. A social force model was first proposed by [PERSON] and [PERSON] [49], describing pedestrians as particles that are subject to forces of attraction and repulsion. [PERSON] et al. [4] then developed another social force model to study the collective phenomenon of escape panic, where a mixture of socio-psychological and physical forces was assumed, which includes interaction forces, body force and siding friction force. Velocity obstacle models have been originally developed for robot motion planning. They assume that other robots in the environment maintain their current velocity and thus may define velocity obstacles; such models enable a robot to plan for collision avoidance. Agent-based models describe the evacuation system by simulating each evacuee (or a household [40]) as an autonomous agent with certain behavior and situated in an environment, and studying the emergent system behavior. In contrast, approaches based on experiments with animals study escape dynamics with real biological agents such as mice [44] or ants [45; 46; 47]. Hybrid models combine the previously mentioned microscopic models to benefit from their advantages and to avoid their drawbacks. In contrast to microscopic models describing the crowds as discrete individuals, macroscopic models treat the crowd as a continuous medium characterized by averaged quantities such as density and velocity [50; 51]. Fluid dynamic models are the most recognized macroscopic models [52; 53], which use the analogy of fluid dynamics to describe the crowd flow in the form of partial differential equations [54]. Fluid-dynamic models and social force models are continuous in space and time, compared to cellular automata models and lattice gas models, where space and time are discrete [22]. Agent-based models can have both continuous and discrete representations in space and time. Typical phenomena that can be reproduced in simulations include kin behavior, arching, effect of obstacles, jamming, friction effects, clogging, \"freezing by heating\", \"faster-is-slower\", counterflow, choking flow, mass behavior, pushing behavior, panic propagation, impatience, repulsion behavior, competitive behavior, queuing behavior, and herding behavior [22]. [PERSON] et al.