Multi-Modal Fusion Technology Based on Vehicle Information: A Survey

Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' attention in recent years. The current multi-modal fusion methods mainly focus on camera data and LiDAR data, but pay little attention to the kinematic information provided by the sens...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on intelligent vehicles 2023-06, Vol.8 (6), p.1-16
Main Authors: Zhang, Xinyu, Gong, Yan, Lu, Jianli, Wu, Jiayi, Li, Zhiwei, Jin, Dafeng, Li, Jun
Format: Article
Language:English
Subjects:
Acceleration
autonomous driving
Autonomous vehicles
Cameras
Kinematics
Laser radar
Meteorology
Multi-modal fusion
perception
Roads
Sensors
Task analysis
Traffic speed
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' attention in recent years. The current multi-modal fusion methods mainly focus on camera data and LiDAR data, but pay little attention to the kinematic information provided by the sensors of the vehicle, such as acceleration, vehicle speed, angle of rotation. These information are not affected by complex external scenes, so it is more robust and reliable. In this paper, we introduce the existing application fields of vehicle information and the research progress of related methods, as well as the multi-modal fusion methods based on information. We also introduced the relevant information of the vehicle information dataset in detail to facilitate the research as soon as possible. In addition, new future ideas of multi-modal fusion technology for autonomous driving tasks are proposed to promote the further utilization of vehicle information.
ISSN:2379-8858
2379-8904
DOI:10.1109/TIV.2023.3268051