Pedestrian navigation is a complex function of human dynamics, a desired destination, and the presence of obstacles. People cannot stop and start instantaneously and their turning abilities are influenced by kinematic and dynamical constraints. A realistic model of human walking paths is an important development for entertainment applications and many classes of simulations. We present a novel behavioral model of path planning that extends previous models through its significant use of pedestrian performance statistics that were obtained during a suite of experiments. We develop an original interpretation of quantitative metrics for measuring a model's accuracy, and use it to compare our path planning approach to a popular contemporary method. Results indicate that this new path planning model better fits natural human behavior than previous models.
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Brogan et al. (2004) studied this question.
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