End-to-End Autonomous Driving through V2X Cooperation
Cooperatively utilizing both ego-vehicle and infrastructure sensor data via V2X
communication has emerged as a promising approach for advanced autonomous driving …
communication has emerged as a promising approach for advanced autonomous driving …
Edge-Assisted Relevance-Aware Perception Dissemination in Vehicular Networks
Vehicles are equipped with various sensors such as LiDAR, which enable them to perceive
the surrounding environment and enhance driver safety through advanced driver assistance …
the surrounding environment and enhance driver safety through advanced driver assistance …
Multi-Intersection Management for Connected Autonomous Vehicles by Reinforcement Learning
The rapid development of connected autonomous vehicles (CAVs) makes it foreseeable that
CAVs will dominate future road traffic. To manage CAV traffic, researchers developed a …
CAVs will dominate future road traffic. To manage CAV traffic, researchers developed a …
RoADTrain: Route-Assisted Decentralized Peer Model Training Among Connected Vehicles
Fully decentralized model training for on-road vehicles can leverage crowdsourced data
while not depending on central servers, infrastructure or Internet coverage. However, under …
while not depending on central servers, infrastructure or Internet coverage. However, under …
Multi-agent Reinforcement Learning-based Capacity Planning for On-demand Vehicular Fog Computing
Fog computing reduces network latency by moving computational resources close to where
the data is generated. Vehicular fog computing (VFC) is an emerging computing paradigm …
the data is generated. Vehicular fog computing (VFC) is an emerging computing paradigm …