Vehicular edge computing: Architecture, resource management, security, and challenges
Vehicular Edge Computing (VEC), based on the Edge Computing motivation and
fundamentals, is a promising technology supporting Intelligent Transport Systems services …
fundamentals, is a promising technology supporting Intelligent Transport Systems services …
Fusion of engineering insights and emerging trends: Intelligent urban traffic management system
Traffic congestion is a great concern, especially in urban areas where the vehicles' number
on roads continues to intensify significantly against the slow development of road …
on roads continues to intensify significantly against the slow development of road …
Vehicular intelligence in 6G: Networking, communications, and computing
With the deployment of 5G, researchers and experts begin to look forward to 6G. They
predict that 6G will be the key driving force for information interaction and social life after …
predict that 6G will be the key driving force for information interaction and social life after …
A novel framework to avoid traffic congestion and air pollution for sustainable development of smart cities
Traffic management is crucial for the sustainable development of smart cities. There has
been a continuous emphasis from the research community to predict air quality and manage …
been a continuous emphasis from the research community to predict air quality and manage …
[HTML][HTML] Optimization of electric vehicle charging control in a demand-side management context: a model predictive control approach
In this paper, we propose a novel demand-side management (DSM) system designed to
optimize electric vehicle (EV) charging at public stations using model predictive control …
optimize electric vehicle (EV) charging at public stations using model predictive control …
Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene
C Li, X Xu, H Zhu, J Gan, Z Chen, X Tang - Energy, 2024 - Elsevier
To address the comprehensive optimization problem of driving performance and fuel
economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in …
economy in the driving process of hybrid electric vehicles (HEV) in the car-following scene in …
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 …
congestion is also critical to vehicles with high emergencies such as ambulances or police …
Traffic density classification for multiclass vehicles using customized convolutional neural network for smart city
Building a traffic monitoring system for intelligent transportation systems (ITS) in the
develo** smart cities has drawn in a mass of consideration in the latest past. Since the …
develo** smart cities has drawn in a mass of consideration in the latest past. Since the …
Predictive congestion control based on collaborative information sharing for vehicular ad hoc networks
Traffic jams are an essential and continuous challenge in our cities, responsible for
socioeconomic and environmental concerns and an ambitious traffic jams management …
socioeconomic and environmental concerns and an ambitious traffic jams management …
The machine learning framework for traffic management in smart cities
P Tiwari - Management of Environmental Quality: An International …, 2024 - emerald.com
Purpose The objective of this research work is to design a data-based solution for
administering traffic organization in a smart city by using the machine learning algorithm …
administering traffic organization in a smart city by using the machine learning algorithm …