Recent Advances in Machine Learning and Deep Learning in Vehicular Ad-hoc Networks: A Comparative Study

Taib, Chaymae; Elkhatir, Haimoudi; Abdoun, Otman

doi:10.1007/978-981-19-0039-6_1

Cited by 7 publications

(1 citation statement)

References 26 publications

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“…An interested low latency protocol is called “DUBHE” and is used to transport information of the firefighting UGVs to the infrastructure. The protocol consists from the delay, path, and broadcast parameters [ 24 ]. The IGRP is a V2X routing system, based on the efficient road intersection selections, in terms of the network connectivity, latency, error rate, and capacity [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Enhanced QoS Routing Protocol for an Unmanned Ground Vehicle, Based on the ACO Approach

Ali

Ngadi

Sham

et al. 2023

Sensors

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Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage area size, frequent network connection failures, and quick network structure changes. The research aims to improve the communication network of self-driving firefighting unmanned ground vehicles by determining the best routing track to the desired fire area. The suggested new model intends to improve the RS regarding the optimum tracking route for firefighting unmanned ground vehicles by employing the ant colony optimization technique. This optimization method represents one of the swarm theories utilized in vehicles ad–hoc networks and social networks. According to the results, the proposed model can enhance the navigation of self-driving firefighting unmanned ground vehicles towards the fire region, allowing firefighting unmanned ground vehicles to take the shortest routes possible, while avoiding closed roads and traffic accidents. This study aids in the control and management of ad–hoc vehicle networks, vehicles of everything, and the internet of things.

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Section: Methodsmentioning

confidence: 99%