US Patent Application 17715011. PERSONALIZED VEHICLE LANE CHANGE MANEUVER PREDICTION simplified abstract
Contents
PERSONALIZED VEHICLE LANE CHANGE MANEUVER PREDICTION
Organization Name
TOYOTA JIDOSHA KABUSHIKI KAISHA
Inventor(s)
ZIRAN Wang of San Jose CA (US)
KYUNGTAE Han of Palo Alto CA (US)
ROHIT Gupta of Santa Clara CA (US)
PRASHANT Tiwari of Santa Clara CA (US)
PERSONALIZED VEHICLE LANE CHANGE MANEUVER PREDICTION - A simplified explanation of the abstract
- This abstract for appeared for US patent application number 17715011 Titled 'PERSONALIZED VEHICLE LANE CHANGE MANEUVER PREDICTION'
Simplified Explanation
The abstract describes a learning-based algorithm that can predict when a driver will change lanes based on their individual driving behaviors. The algorithm has two phases: an offline training phase where a machine learning model is trained using historical driving data, and an online validation phase where real-time driving data is used to predict lane change maneuvers. The algorithm can identify potential vehicle trajectories and determine the most likely trajectory based on the driver's preferences, which are learned during the offline training phase.
Original Abstract Submitted
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.
