Baidu USA LLC

Apollo Autonomous Driving USA LLC

Ang Li

Yu Long Cao

Jiangtao Hu

Shu Jiang

Weiman Lin

Szu-Hao Wu

Yu Cao

A system generates a first variant of a first machine learning (ML) model, the first variant associated with an initial hyperparameter value. The system determines a prediction metric for the first variant of the first ML model, the prediction metric indicating an accuracy of the behavior prediction. The system generates an estimated simulation metric for the first variant of the first ML model by applying a second ML model to the prediction metric. The system identifies a first hyperparameter associated with a second variant of the first ML model, the second variant of the first ML model having a corresponding prediction metric and a corresponding estimated simulation metric that meet a first predetermined criteria, the second variant of the first ML model is used by an autonomous driving vehicle (ADV) for behavior prediction.

Multi-level optimization framework for behavior prediction in autonomous driving

The present disclosure provides methods and techniques for evaluating and improving algorithms for autonomous driving planning and control (PNC), using one or more metrics (e.g., similarity scores) computed based on expert demonstrations. For example, the one or more metrics allow for improving PNC based on human, as opposed to or in addition to optimizing certain oversimplified properties, such as the least distance or time, as an objective. When driving in certain scenarios, such as taking a turn, people may drive in a distributed probability pattern instead of in a uniform line (e.g., different speeds and different curvatures at the same corner). As such, there can be more than one 'correct' control trajectory for an autonomous vehicle to perform in the same turn. Safety, comfort, speeds, and other criteria may lead to different preferences and judgment as to how well the controlled trajectory has been computed.

Distributional expert demonstrations for autonomous driving

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Sunnyvale, CA, United States of America

Ang Li