Stochastic Path Generation for Anticipative Road Following Guided by Saccadic Object Detection

Abstract

To implement anticipative road following process, a stochastic perception-control coupling is introduced on satellite-roadway-vehicle network. Random shift of the boundary probability is detected via the saccadic perception process and interpolated by using stochastic growth dynamics to generate continuous trajectories subjected to human's unexpectable decision making. The validity of stochastic path generation scheme is verified via simulation studies.