Z Wu, Z Yang, C Yang, J Lin, Y Liu… - … of Communications and …, 2021 - ieeexplore.ieee.org
As the general mobile edge computing (MEC) scheme cannot adequately handle the emergency communication requirements in vehicular networks, unmanned aerial vehicle …
CM Huang, MS Chiang, DT Dao, WL Su, S Xu… - IEEE …, 2018 - ieeexplore.ieee.org
Data offloading plays an important role for the mobile data explosion problem that occurs in cellular networks. This paper proposed an idea and control scheme for offloading vehicular …
Q Luo, C Li, TH Luan, W Shi - IEEE Transactions on Services …, 2021 - ieeexplore.ieee.org
The development of autonomous driving poses significant demands on computing resource, which is challenging to resource-constrained vehicles. To alleviate the issue, Vehicular …
W Feng, N Zhang, S Li, S Lin, R Ning… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Cooperative Vehicle-Infrastructure System (CVIS) can provide innovative services for traffic management and enable trips to be safer, more coordinated, and smarter. In the CVIS, the …
Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels …
Y Zhu, B Mao, N Kato - IEEE Open Journal of Vehicular …, 2022 - ieeexplore.ieee.org
The applications of Intelligent Transportation System (ITS) and autonomous driving in the 6G era heavily rely on the massive information exchange of ultra-wide bandwidth, high …
Y Zhu, B Mao, N Kato - IEEE Transactions on Emerging Topics …, 2022 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) has played an important role in realizing intelligent beyond 5G (B5G) vehicular networks. The computation tasks of intelligent applications can …
Q Luo, C Li, TH Luan, W Shi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
With the fast development of Internet of Vehicles (IoV), various types of computation- intensive vehicular applications pose significant challenges to resource-constrained …
Autonomous Vehicles (s) take advantage of Machine Learning (ML) for yielding improved experiences of self-driving. However, large-scale collection of s' data for training will …