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From Euler's seven-bridge problem to modern robot motion planning techniques, path finding has been a very important part of network analysis in operations research. And finding the shortest path between two nodes in a network is a classical problem in a number of research areas. Although some general one-source-to-one-target shortest path algorithms have already been developed, such as Dijkstra's shortest path algorithm, in some cases, some alternative algorithms with lower computation complexity may be preferred due to the properties of real tasks. The algorithms in this thesis are developed for a real-time evacuation system which is on the platform of a 3D Virtual Reality augmented environment, for which some fast shortest path algorithm is to be developed. In this order, this thesis will analyze some common inside-building topologies first, and then developed a fast shortest path algorithm for the topologies, which frequently appear in indoor areas, such as campus and commercial buildings. With the much lower computation complexity than Dijkstra's shortest path algorithm, this algorithm can be a useful tool for real-time optimal path finding in Euclidean networks. (Euclidean networks refer to the networks whose edge weights are assigned based on their Euclidean lengths). Some flow control techniques have also been discussed; and a fast evacuation flow control algorithm has been developed as well. Compared to previous evacuation flow control algorithms, this one is more suitable for real-time systems due to its fast computing speed. A test bed evacuation system has been built in order to implement this algorithm. Optimal path finding and flow control algorithms can provide very practical utilities for an evacuation system, and make the system a good tool for emergency rescuing tasks. The research in this thesis will give a deep insight in this aspect. 11 ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library

Path finding and flow control for virtual reality augmented evacuation system for large indoor areas