相关论文: Joint Channel Selection using FedDRL in V2X
Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize…
In the rapidly evolving landscape of Internet of Vehicles (IoV) technology, Cellular Vehicle-to-Everything (C-V2X) communication has attracted much attention due to its superior performance in coverage, latency, and throughput. Resource…
Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by line-of-sight and field-of-view constraints. These inherent limitations may cause onboard…
Federated learning (FL) is a popular framework for training an AI model using distributed mobile data in a wireless network. It features data parallelism by distributing the learning task to multiple edge devices while attempting to…
In this article, we develop a decentralized resource allocation mechanism for vehicle-to-vehicle (V2V) communication systems based on deep reinforcement learning. Each V2V link is considered as an agent, making its own decisions to find…
As vehicle intelligence advances, multi-modal sensing-aided communication emerges as a key enabler for reliable Vehicle-to-Everything (V2X) connectivity through precise environmental characterization. As centralized learning may suffer from…
Cellular (C) setups facilitate the connectivity amongst the devices with better provisioning of services to its users. Vehicular networks are one of the representative setups that aim at expanding their functionalities by using the…
In recent decades, both the industry and the academy society are sparing no efforts to develop and standardize the Cellular-Vehicle-to-Everything (C-V2X) communication which is one of the prominent emerging services of the next generation…
Vehicle-to-Everything (V2X) cooperation is reshaping traffic safety from an ego-centric sensing problem into one of collective intelligence. This survey structures recent progress within a unified Sensor-Perception-Decision (SPD) framework…
Content distribution is an application in intelligent transportation system to assist vehicles in acquiring information such as digital maps and entertainment materials. In this paper, we consider content distribution from a single roadside…
Collaborative navigation becomes essential in situations of occluded scenarios in autonomous driving where independent driving policies are likely to lead to collisions. One promising approach to address this issue is through the use of…
Next Generation (NextG) networks are expected to support demanding tactile internet applications such as augmented reality and connected autonomous vehicles. Whereas recent innovations bring the promise of larger link capacity, their…
The rapid advancement of Artificial Intelligence (AI) has introduced Deep Neural Network (DNN)-based tasks to the ecosystem of vehicular networks. These tasks are often computation-intensive, requiring substantial computation resources,…
Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning based…
In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception.…
Existing deep reinforcement learning (DRL) based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with homogeneous vehicle fleet, in which the fleet is assumed as repetitions of a single vehicle. Hence,…
In this paper, we investigate the problem of fast spectrum sharing in vehicle-to-everything communication. In order to improve the spectrum efficiency of the whole system, the spectrum of vehicle-to-infrastructure links is reused by…
In this paper we investigate collision detection and avoidance in a vehicular network of full duplex (FD) operating nodes. Each vehicle in this network senses the energy level of the channel before and during its transmission. The measured…
The research efforts on cellular vehicle-to-everything (V2X) communications are gaining momentum with each passing year. It is considered as a paradigm-altering approach to connect a large number of vehicles with minimal cost of deployment…
Platoon-based driving is an idea that vehicles follow each other at a close distance, in order to increase road throughput and fuel savings. This requires reliable wireless communications to adjust the speeds of vehicles. Although there is…