Gm Global Technolgoy Operations, Inc.

Carolyn Heather MacLeod

Bo Yu

Joon Hwang

Carl P Darukhanavala

Fan Bai

Donald K Grimm

Shuqing Zeng

Vivek Vijaya Kumar

Gui Chen

Muhammad Rehan

A method for crowd-sourcing lane line map data for a vehicle may include receiving a plurality of observations. The plurality of observations includes at least a first observation and a second observation. The method further may include generating a point cloud alignment vector based at least in part on the plurality of observations. The method further may include generating an optimized aligned point cloud based at least in part on the point cloud alignment vector. The method further may include determining a lane line map based at least in part on the optimized aligned point cloud. The method further may include updating a map database based at least in part on the lane line map.

Crowd-sourcing lane line maps for a vehicle

A vehicle system is provided for correcting in real-time a camera-based estimated position of a road object. The system includes a camera for generating an image input signal including image sensor data associated with the road object. The system further includes one or more input devices for generating a vehicle input signal including vehicle sensor data associated with a position, a speed, and a heading of the vehicle. The system further includes a computer, which includes one or more processors and a non-transitory computer readable medium (CRM) storing instructions. The processor is programmed to match the image sensor data and the vehicle sensor data to one another based on a common time of collection. The processor is further programmed to determine an error model and a deviation of a current camera-based position from a predicted position. The processor is further programmed to update the error model based on the deviation.

System and method for correcting in real-time an estimated position of a road object

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Thornhill, Canada

Carolyn Heather MacLeod