Gm Global Technolgoy Operations, Inc.

Rodolfo Valiente Romero

Hyukseong Kwon

Alireza Esna Ashari Esfahani

Marcus J Huber

Michael Cui

Rajan Bhattacharyya

Michael J Daily

Yao Hu

Gavin D Holland

Amir M Rahimi

Andrew Howe

Alexei Kopylov

Dana Warmsley

Alexander Waagen

An end-to-end perception perturbation modeling system for a vehicle includes one or more controllers storing a detection model in memory. The detection model includes a plurality of detection model plots that each indicate a probability value that an object in an environment surrounding the vehicle is detected based on a current weather condition and a distance measured between the vehicle and the object detected in the environment surrounding the vehicle. The one or more controllers execute instructions to receive an input state of the vehicle that is observed during non-inclement weather conditions and indicates one or more vehicle states, the current weather condition, and the distance. The controllers determine a perturbed state of the vehicle observed during the current weather condition.

End-to-end perception perturbation modeling system for a vehicle

According to several aspects, a method for path planning for a vehicle includes determining a predicted trajectory of a remote vehicle. The predicted trajectory of the remote vehicle includes a plurality of predicted trajectory nodes. The method further includes determining a plurality of possible trajectories for the vehicle. The plurality of possible trajectories includes a plurality of possible trajectory nodes. The method further includes determining one or more evaluation metrics of each of the plurality of possible trajectory nodes based at least in part on a weather condition in an environment surrounding the vehicle. The method further includes selecting an optimal trajectory for the vehicle from the plurality of possible trajectories based at least in part on the one or more evaluation metrics of each of the plurality of possible trajectory nodes. The method further includes performing a first action based at least in part on the optimal trajectory.

Weather-informed path planning for a vehicle

A system for verifying accuracy of an object determination made with a perception system for an object detected within a surrounding area of a vehicle. The system may include a semantic extraction module configured for generating semantic information for the object, a semantic generation module configured for generating a plurality of semantic captions based on the semantic information, a consistency evaluation module configured for generating consistency scores for the semantic captions, and a diagnostics module configured for verifying accuracy of the object determination based on the consistency scores.

Object detection verification for vehicle perception system

A method for performing object detection during autonomous driving includes: performing 3D object detection in a 3D object detection segment; uploading an output of multiple sensors in communication with the 3D object detection segment to multiple point clouds; transferring point cloud data from the multiple point clouds to a Region Proposal Network (RPN); independently performing 2D object detection in a 2D object detector in parallel with the 3D object detection in the 3D object detection segment; and taking a given input image and simultaneously learning box coordinates and class label probabilities in a 2D object detection network operating to treat object detection as a regression problem.

3D object detection method using synergy of heterogeneous sensors for autonomous driving

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ORLANDO, FL, United States of America

Rodolfo Valiente Romero