A centralized and dynamic network congestion classification approach for heterogeneous vehicular networks

F Falahatraftar, S Pierre, S Chamberland - IEEE Access, 2021 - ieeexplore.ieee.org
Network congestion-related studies consist mainly of two parts: congestion detection and
congestion control. Several researchers have proposed different mechanisms to control …

An intelligent congestion avoidance mechanism based on generalized regression neural network for heterogeneous vehicular networks

F Falahatraftar, S Pierre… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The information generated by safety and traffic efficiency applications needs strict
communication requirements to be smoothly exchanged in intelligent transportation system …

Distributed classification of urban congestion using VANET

R Al Mallah, A Quintero… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Vehicular ad hoc networks (VANETs) can efficiently detect traffic congestion, but detection is
not enough, because congestion can be further classified as recurrent and non-recurrent …

[HTML][HTML] Accurate traffic flow prediction in heterogeneous vehicular networks in an intelligent transport system using a supervised non-parametric classifier

H El-Sayed, S Sankar, YA Daraghmi, P Tiwari… - Sensors, 2018 - mdpi.com
Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks
(VANETs), which allow vehicles to always be connected so as to obtain safety services …

Traffic congestion identification and reduction

BK Chaurasia, WS Manjoro, M Dhakar - Wireless Personal …, 2020 - Springer
Historical data is increasingly becoming more purposeful in the field of intelligent traffic
systems. Traffic congestion is one of the major challenges in most cities around the world. It …

Research and comparison on identification and prediction methods of air traffic network congestion

Z Zhao, J Yuan, Y Liu - 2022 4th International Academic …, 2022 - ieeexplore.ieee.org
Air traffic congestion (ATC) identification and prediction is a prerequisite work for air traffic
flow management (ATFM) and flight delay mitigation. In this paper, we construct the ex-post …

Entropy-based traffic flow labeling for CNN-based traffic congestion prediction from meta-parameters

MZ Mehdi, HM Kammoun, NG Benayed… - IEEE …, 2022 - ieeexplore.ieee.org
Traffic congestion affects quality of life by inducing frustration and wasting time. The
congestion is also critical to vehicles with high emergencies such as ambulances or police …

Fog computing for detecting vehicular congestion, an internet of vehicles based approach: A review

A Thakur, R Malekian - IEEE Intelligent Transportation Systems …, 2019 - ieeexplore.ieee.org
Vehicular congestion is directly impacting the efficiency of the transport sector. A wireless
sensor network for vehicular clients is used in Internet of Vehicles based solutions for traffic …

Traffic congestion prediction using deep reinforcement learning in vehicular ad-hoc networks (vanets)

C Pholpol, T Sanguankotchakorn - International Journal of …, 2021 - papers.ssrn.com
In recent years, a new wireless network called vehicular ad-hoc network (VANET), has
become a popular research topic. VANET allows communication among vehicles and with …

Integrating the traffic science with representation learning for city-wide network congestion prediction

W Zheng, HF Yang, J Cai, P Wang, X Jiang, SS Du… - Information …, 2023 - Elsevier
Recent studies on traffic congestion prediction have paved a promising path towards the
reduction of potential economic and environmental loss. However, at the city-wide scale …