Abstract

In many virtual environments, autonomous objects, such as people and vehicles, are essential to increase the feeling of presence. A goal is to have autonomous objects behave as humans, or in the case of vehicles, as if humans controlled them. Such objects are known as intelligent autonomous objects. We present a combination of a communication model and a decisionmaking model to achieve the goal of modeling autonomous objects that behave intelligently. Both models are attached to autonomous objects that represent people and vehicles in a virtual environment. This enables such an autonomous object to be an independent entity that is self-motivated and self-controlled. These intelligent autonomous objects are able to communicate with other autonomous objects via their communication model according to decisions reached by their decision-making model. The decision-making model relies on the communication model to investigate possible outcomes before making decisions. The communication model defines senders, receivers, contents, and channels (media through which content is transferred) in realtime to gather desired information from specified objects. The decision-making model is divided into two levels, the global level and the local level. These work, respectively, with global information perceived by a perception model and the local information received by the communications model. A group of logic rules are formulated as decision trees to model the process of making decisions on the basis of real-time activities. We used traffic and people, in a virtual environments based driving simulator, as examples of intelligent communicating autonomous objects

Authors


Ronald R. R.


Zhishuai Yin


Yingzi Lin


Sagar Kamarthi

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