Method and process for motion planning in (un-)structured environments with pedestrians and use of probabilistic manifolds

摘要

A method for predicting pedestrian movements in structured and unstructured environments to be used for motion planning and control of an autonomous vehicle comprises the steps of: Reading map data where the vehicle is planned to drive. Reading the structure of static (eg buildings)/quasi-static/dynamic (eg pedestrian) obstacles. Computing specific spaces, such as tangency/orthogonal space, and optimal grids. Computing vector fields. Configuring a pedestrian model. Predicting movement based on last captured pedestrian position. Generating a motion plan for the vehicle. Controlling the vehicle according to the motion plan. The method may further comprise the use of uncertainty quantification in motion planning. The method may additionally predict pedestrian trajectories and the environment model by incorporating probabilistic manifold descriptors and topological spaces. The method may include visual measurements (eg of pedestrian gestures) and contextual information about the environment. The method may incorporate network descriptors to capture topological spaces of humans and learn their dynamics