TY - JOUR
T1 - Multisensor Information Fusion
T2 - Future of Environmental Perception in Intelligent Vehicles
AU - Zhang, Yongsheng
AU - Tu, Chen
AU - Gao, Kun
AU - Wang, Liang
N1 - Publisher Copyright:
© 2018 Tsinghua University Press.
PY - 2024
Y1 - 2024
N2 - As urban transportation increasingly impacts daily life, efficiently utilizing traffic resources and developing public transportation have become crucial for addressing issues such as congestion, frequent accidents, and noise pollution. The rapid advancement of intelligent autonomous driving technologies, particularly environmental perception technologies, offers new directions for solving these problems. This review discusses the application of multisensor information fusion technology in environmental perception for intelligent vehicles, analyzing the components and performance of various sensors and their specific applications in autonomous driving. Through multisensor information fusion, the accuracy of environmental perception is enhanced, optimizing decision support for autonomous driving systems and thereby improving vehicle safety and driving efficiency. This study also discusses the challenges faced by information fusion technology and future development trends, providing references for further research and application in intelligent transportation systems.
AB - As urban transportation increasingly impacts daily life, efficiently utilizing traffic resources and developing public transportation have become crucial for addressing issues such as congestion, frequent accidents, and noise pollution. The rapid advancement of intelligent autonomous driving technologies, particularly environmental perception technologies, offers new directions for solving these problems. This review discusses the application of multisensor information fusion technology in environmental perception for intelligent vehicles, analyzing the components and performance of various sensors and their specific applications in autonomous driving. Through multisensor information fusion, the accuracy of environmental perception is enhanced, optimizing decision support for autonomous driving systems and thereby improving vehicle safety and driving efficiency. This study also discusses the challenges faced by information fusion technology and future development trends, providing references for further research and application in intelligent transportation systems.
KW - autonomous driving
KW - environmental perception
KW - intelligent vehicles
KW - multisensor information fusion
KW - traffic safety
UR - http://www.scopus.com/inward/record.url?scp=85206453856&partnerID=8YFLogxK
U2 - 10.26599/JICV.2023.9210049
DO - 10.26599/JICV.2023.9210049
M3 - Review article
AN - SCOPUS:85206453856
SN - 2399-9802
VL - 7
SP - 163
EP - 176
JO - Journal of Intelligent and Connected Vehicles
JF - Journal of Intelligent and Connected Vehicles
IS - 3
ER -