Robert Boschgmbh

Thomas Glaser

Jason Scott Hardy

Joerg Mueller

Mithun Jacob

Lutz Buerkle

Thomas App

Seyed Abbas Sadat

An action planning system () and method for autonomous vehicles are provided. The system () comprises one or more processors () and one or more non-transitory computer-readable storage medium () having stored thereon a computer program used by the one or more processors (), wherein the computer program causes the one or more processors () to estimate future environment of an autonomous vehicle (), generate a possible trajectory for the autonomous vehicle (), predict motion and reactions of each dynamic obstacle in the future environment of the autonomous vehicle () based on current local traffic context, and generate a prediction iteratively over timesteps.

Action planning system and method for autonomous vehicles

A processing system includes at least one computer processor, which is configured to implement a method that includes receiving crowd-sourced driving path data, map data, and real-time sensor data associated with a roadway. The method includes generating, by the processing system, optimized driving path data for the roadway based on the crowd-sourced path data, the map data, and the sensor data. The method includes providing control signals to control an autonomous or semi-autonomous vehicle based on the optimized driving path data.

System and method of using crowd-sourced driving path data in an autonomous or semi-autonomous driving system

A method for determining a transversal controller parameterization for transversal control of a vehicle on a route segment to be instantaneously traveled on by the vehicle, having a step for determining the parameter based on a piece of information about a curvature of the route segment to be instantaneously traveled on.

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Sunnyvale, CA, United States of America

Thomas Glaser