US 2026/0084703 A1 · PERSONALIZED VEHICLE LANE CHANGE MANEUVER PREDICTION

Abstract

A learning-based lane change prediction algorithm, and systems and methods for implementing the algorithm, are disclosed. The prediction algorithm evaluates the driving behaviors of a target human driver and predicts lane change maneuvers based on those personalized driving behaviors. The algorithm may include an online lane change decision prediction phase and an offline prediction training and cost function recovery phase. During the offline training phase, a machine learning model may be trained based on historical vehicle states. During the online validation phase, driving data may be collected and fed to the trained model to predict a driver's lane change maneuver, identify potential vehicle trajectories, and determine a most probable vehicle trajectory based on a driver's cost function recovered during the offline phase.

Claims20

Dependent claims

A method for personalized lane change prediction, comprising:

training a machine learning model based on training data to perform lane change prediction, the training data being indicative of historical lane change behavior of a driver of a target vehicle;
predicting, using the trained machine learning model, a lane change-related maneuver of the target vehicle based on real-time vehicle state information associated with the target vehicle;
determining, based on a selected personalized cost function for the driver and the predicted lane change-related maneuver, a most probable trajectory for the target vehicle from a set of candidate trajectories;
and
controlling the target vehicle based on a personalized lane change prediction, wherein the personalized lane change prediction is generated based on the most probable trajectory.

2 more elements

A non-transitory computer-readable medium storing machine-executable instructions that, when executed by one or more processors, cause the one or more processors to:

train a machine learning model based on training data to perform lane change prediction, the training data being indicative of historical lane change behavior of a driver of a target vehicle;
predict, using the trained machine learning model, a lane change-related maneuver of the target vehicle based on real-time vehicle state information associated with the target vehicle;
determine, based on a personalized cost function for the driver and the predicted lane change-related maneuver, a most probable trajectory for the target vehicle from a set of candidate trajectories;
and
control the target vehicle based on a personalized lane change prediction, wherein the personalized lane change prediction is generated based on the most probable trajectory.

2 more elements

Dependencies are inferred from the claim text.

Personalized vehicle lane change maneuver prediction

Life of this patent

Personalized vehicle lane change maneuver prediction

Life of this patent

Abstract

Claims20