Autonomous pedestrians

We address the challenging problem of emulating the rich complexity of real pedestrians in urban environments. Our artificial life approach integrates motor, perceptual, behavioral, and cognitive components within a comprehensive model of pedestrians as individuals. Featuring innovations in these components, as well as in their combination, our model yields results of unprecedented fidelity and complexity for fully autonomous multihuman simulation in a large urban environment. We represent the environment using hierarchical data structures, which efficiently support the perceptual queries that influence the behavioral responses of the autonomous pedestrians and sustain their ability to plan their actions on local and global scales.