Detecting Competitive Behaviors in Conflicts

Daichi Yanagisawa () and Keisuke Yamazaki ()
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Daichi Yanagisawa: The University of Tokyo, Research Center for Advanced Science and Technology
Keisuke Yamazaki: National Institute of Advanced Industrial Science and Technology, The Artificial Intelligence Research Center

A chapter in Traffic and Granular Flow '17, 2019, pp 297-305 from Springer

Abstract: Abstract We developed a method for detecting aggressive agents in egress simulations with a cellular-automata model. There are two types of agents, which are normal agents and aggressive agents. Aggressive agents tend to push out others in conflicts and try to move to their target cell aggressively. We considered all the possible combinations of agent types, labeled them, and computed the joint probabilities of the labels from the conflict data obtained from the egress simulations. The label which achieved the maximum joint probability was regarded as the expected label. The accuracy of our method achieved larger than 95% when a few very aggressive agents exist in a group of normal agents. On the other hand, the accuracy decreases when the aggressiveness of aggressive agents decreases or the fraction of the aggressive agents increases.

Date: 2019
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DOI: 10.1007/978-3-030-11440-4_33

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