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Large-scale crowd behavior evolution analysis method based on Map-Reduce and multi-agent models

A multi-agent and analysis method technology, applied in the field of simulation modeling, can solve the problems of reducing the generality of simulation algorithms, reducing the efficiency of simulation execution, and a large number of cross-node communications, so as to save memory, improve data processing efficiency, and space complexity Reduced effect

Inactive Publication Date: 2016-07-20
WUHAN UNIV
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Problems solved by technology

This implementation method not only reduces the versatility of the simulation algorithm, but also requires a large number of cross-node communications for simulation events that cross partition boundaries, thereby increasing additional data exchange between nodes and reducing the efficiency of simulation execution

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  • Large-scale crowd behavior evolution analysis method based on Map-Reduce and multi-agent models
  • Large-scale crowd behavior evolution analysis method based on Map-Reduce and multi-agent models
  • Large-scale crowd behavior evolution analysis method based on Map-Reduce and multi-agent models

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Embodiment Construction

[0036] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0037] Aiming at the deficiencies of the existing methods, the present invention adopts the map-reduce programming model to design a large-scale crowd simulation method based on the multi-agent method, and implements the method on the Apache Hadoop framework. The agent information list is transformed into a key-value-attribute-value table; the timing of the simulation process is simulated through the mechanism of time slice and cycle, each time slice corresponds to a cycle, and each cycle includes the key-value-attribute value table of agent information A map...

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Abstract

The invention discloses a large-scale crowd behavior evolution analysis method based on map-reduce and multi-agent models. The method is achieved through a map-reduce programming model, and simulation operation is achieved through data processing operation; by converting agent information in multi-agent crowd simulation into entries of a key value and attribute value list and by achieving logical judgment decision and status update of agents through map and reduce operations, large-scale crowd simulation is converted into data processing operation in a key value and attribute value list mode. The method is achieved on clusters based on an ApacheHadoop frame. It is proved through tests that the simulation crowds produced through the simulation method are in accordance with existing serialization simulation results in subsection and morphology; according to the method, the scale of the crowds capable of being simulated is large, the operation speed is high, and occupation of a memory working set is greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of simulation modeling and relates to a crowd simulation method, in particular to a large-scale crowd behavior evolution analysis method based on map-reduce and a multi-agent model. Background technique [0002] Large-scale crowd simulation research, such as emergency evacuation, is playing an increasingly important role in public safety-related research such as facility planning, disaster relief, and combating terrorism. Traditional crowd behavior research mostly adopts research methods based on real scenes or physical experiments to extract data. These methods have the disadvantages of high cost, high risk, many restrictions, and lack of interactivity. With the development of computer simulation technology and high-performance computing technology, it has become possible to use simulation methods to study large-scale crowd scenes. Compared with traditional methods, simulation-based crowd behavior researc...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/367
Inventor 陈丹窦明罡陈靓影王力哲
Owner WUHAN UNIV
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