As a novel computing paradigm, multiaccess edge computing (MEC) migrates computing
and storage capabilities to edge nodes of the network to meet the requirements of executing …

Facing the requirements of intelligent vehicles for massive data processing, vehicular edge
computing (VEC) utilizes computing resources deployed on the roadside infrastructure to …

Birds-Eye-View (BEV) perception can naturally represent natural scenes, which is conducive
to multimodal data processing and fusion. BEV data contain rich semantics and integrate the …

Autonomous driving related researches require the analysis and usage of massive amounts
of driving scenario data. Compared to raw data collected by sensors, scenario data provide …

In this paper, we systematically study how to use edge computing to monitor the movements
of multiple connected and automated vehicles (CAV) and warn of potential accidents (eg …

Cooperative driving of connected and automated vehicles (CAVs) has attracted extensive
attention and researchers have proposed various approaches. However, existing …

Connected and automated vehicles (CAVs) are expected to play a vital role in the next-
generation intelligent transportation system. In recent years, researchers have proposed …

Intelligent vehicles and autonomous driving systems rely on scenario engineering for
intelligence and index (I&I), calibration and certification (C&C), and verification and …

Unmanned aerial vehicle (UAVs) have the advantages of high flexibility and ease of
deployment, making it possible to provide mobile edge computing services as an aerial …

In the realm of software applications in the transportation industry, Domain-Specific
Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various …