Vehicular edge computing (VEC) is emerging as a novel computing paradigm to meet low
latency demands for computation-intensive vehicular applications. However, most existing …

Multi-access edge computing provides a low-latency and high-performance network
environment for the Internet of Vehicle services by migrating computing and storage …

Environmental perception is a key element of autonomous driving because the information
received from the perception module influences core driving decisions. An outstanding …

The large-scale deployment of autonomous vehicles is yet to come, and one of the major
remaining challenges lies in urban dense traffic scenarios. In such cases, it remains …

Autonomous vehicles use multiple sensors, large deep-learning models, and powerful
hardware platforms to perceive the environment and navigate safely. In many contexts …

With the development of autonomous driving, the surging demand for data communications
as well as computation offloading from connected and automated vehicles can be expected …

As the rapid growth of connected and autonomous vehicles (CAVs) and 5G intensifies, more
third-party applications are increasingly being deployed on CAVs. They not only improve …

Connected and automated vehicles currently rely on on-board resources to implement
autonomous functions, leaving the mobile network for non-mission-critical applications. At …

Vehicular edge computing (VEC) is expected as a promising technology to improve the
quality of innovative applications in vehicular networks through computation offloading …

Since local sensing system is inherently limited, it is a trend to combine Cooperative Vehicle
Infrastructure System (CVIS) and autonomous driving technologies to address the limitations …