Other

Jonathan Shum

BaekGyu Kim

Shinichi Shiraishi

The disclosure includes embodiments for autonomous feature optimization. In some embodiments, a method includes generating one or more candidate navigation routes for a driver of a vehicle. In some embodiments, the method includes determining a set of autonomous features to be provided by the vehicle for each of the one or more candidate navigation routes. In some embodiments, the method includes determining that the set of autonomous features includes an unsafe autonomous feature that is not safe to use during any part between the start point and the end point of the one or more candidate navigation routes. In some embodiments, the method includes displaying a user interface that includes the one or more candidate navigation routes and corresponding autonomous features that are available for each of the one or more candidate navigation routes, wherein the user interface excludes the unsafe autonomous feature.

Autonomous feature optimization for a connected vehicle based on a navigation route

The disclosure includes a system, method, and tangible memory for generating a simulation. The method may include receiving real-world sensor stream data that describes a real-world data stream that is recorded by onboard sensors in one or more test vehicles, wherein the real-world sensor stream data describes real-world active agents and real-world environmental elements. The method may further include generating three-dimensional (3D) models of active agents and 3D models of environmental elements in a vehicle environment. The method may further include generating a simulation of the vehicle environment that synthesizes the real-world active agents with 3D models of active agents and synthesizes the real-world environmental elements with the 3D models of environmental elements.

Mixed reality simulation system for testing vehicle control system designs

A system, method and tangible memory provides a graphical display output including a simulation for testing a design for a vehicle. The method extracts object data from accident data describing an object that contributed to a roadway accident occurring in a real world. The method extracts behavior data from the accident data describing the erroneous behavior of the object. The method constructs an error model that describes a virtual object that represents the object in the simulation based in part on the behavior data, a frequency input and a severity input. The method generates the graphical display output including the simulation based on a roadway model, a vehicle model and the error model. The simulation graphically depicts a virtual vehicle present on a virtual roadway system that includes the virtual object behaving dynamically in the simulation based on the error model.

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Mountain View, CA, United States of America

Jonathan Shum