Ontology-based crowd simulation for normal life situations

This paper presents the urban environment model (UEM), a novel approach through which a large number of virtual humans can populate a urban space by considering normal life situations. Using this model, the semantic is included in the virtual space considering normal life actions according to different agent profiles distributed in time and space. For instance, children going to the school and adults going to work at usual times. Leisure and shopping activities are also considered. Agent profiles and their actions are also described using UEM. Besides presenting the details of the model, we present its integration into a crowd simulator whose main goal is to provide realistic and coherent population behaviors into urban environments. The results show that urban environments can be populated in a more realistic way by using UEM, escaping from the normal impression we have in such kind of system that virtual people are walking in a random way by predefined paths in the virtual space.