… In the foreseeable future, millions of autonomouscars will communicate with … study, we aim to explore and investigate the recent solutions and advances made in autonomousdriving …
… network research, deep convolutional and temporal networks became feasible for automated driving tasks… Vehicle-to-vehiclecommunication is still in its infancy, while centralized, cloud-…
… hardware devices; the network module provides the abstraction communication interface; the … collected by survey fleet vehiclesdriving on the road, which provides the training data for …
… high-processing GPU and TPU devices for AD that can efficiently run DL models as the ones addressed in this study. … Kato, “Networking and communications in autonomousdriving: A …
… We focus on convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep reinforcement learning (DRL), which are the most common deep learning …
… the existing surveys either consider applications of DRL for computer vision and natural language processing or discuss applications of deep learning for networking. There is no survey …
D Omeiza, H Webb, M Jirotka… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
… a convolutional neural network end-to-end from images to the vehicle control commands (… study to get insights into interface designs that explicitly communicateautonomousvehicle …
… communication modules, multiple networking schemes and utilization of the internet of things in various aspects of drone communication … used in drone networks is presented in Table 2. …
PK Singh, SK Nandi, S Nandi - Vehicular Communications, 2019 - Elsevier
… Soon, coexistence/inter-networking of existing and other radio access … and automated vehiclenetwork. In this section, we discuss RATs for the connected and autonomousvehicle. …