Inventor

SUN HONGYI

US22 patents

⚠️ This page may combine multiple inventors who share the name “SUN HONGYI”. Patents are grouped by organization below to help distinguish them — per-person disambiguation is on the roadmap.

SUN HONGYI

BAIDU USA LLC

Confidence levels along the same predicted trajectory of an obstacle

Lane-attention: predicting vehicles&#39; moving trajectories by learning their attention over lanes

Real time decision making for autonomous driving vehicles

Compressive environmental feature representation for vehicle behavior prediction

Real time object behavior prediction

Delay decision making for autonomous driving vehicles in response to obstacles based on confidence level and distance

Method for predicting movement of moving objects relative to an autonomous driving vehicle

Machine learning model to fuse emergency vehicle audio and visual detection

In-vehicle acoustic monitoring system for driver and passenger

Comprehensive and efficient method to incorporate map features for object detection with LiDAR

Method for determining ride stability of an autonomous driving system controlling an autonomous driving vehicle

Path planning with a preparation distance for a lane-change

Emergency vehicle audio and visual detection post fusion

Open space planner profiling tool for autonomous vehicle

Neural network with lane aggregation for lane selection prediction of moving objects during autonomous driving

Method for predicting exiting intersection of moving obstacles for autonomous driving vehicles

Method for determining exiting intersection of moving objects for autonomous driving vehicles

Vehicle trajectory prediction model with semantic map and LSTM

Audio logging for model training and onboard validation utilizing autonomous driving vehicle

Sound source detection and localization for autonomous driving vehicle

Audio-based technique to sense and detect the road condition for autonomous driving vehicles

WORCESTER POLYTECH INST

Metal-air battery

Lane-attention: predicting vehicles' moving trajectories by learning their attention over lanes