Communication models for crowd simulation

Abstract

Modeling and animation of behaviorally plausible virtual crowds are important problems of crowd simulation research. We propose a communication model in order to equip virtual agents with the ability to autonomously communicate with each other. We investigate whether such a communication model would improve the plausibility of the simulated crowds. Initially, our efforts were towards a model that is as human-like as possible and towards combining this model with an agent architecture that contains psychological attributes. Early experimental results showed that when we look at a crowd, the influences such as different agent personalities causing different communicative behavior are hardly visible. Besides, achieving these effects introduces complexity. Thus, a generic and easyto- use communication model instead of a human-like one became the target and psychological agent attributes were dropped. The proposed communication model and its application in several scenarios are presented in this dissertation. As a second contribution, one of the application scenarios led us to develop a planning algorithm for an agent in an unknown environment. Simulation results are analyzed both visually and by using various measurements and metrics. Our conclusion is that in addition to improving observed behavioral variety, the effects of employing the communication model are clear in the quantitative results and these effects are in line with our expectations in each scenario.