Review of data fusion methods for real-time and multi-sensor traffic flow analysis
SA Kashinath, SA Mostafa, A Mustapha… - IEEE …, 2021 - ieeexplore.ieee.org
Recently, development in intelligent transportation systems (ITS) requires the input of
various kinds of data in real-time and from multiple sources, which imposes additional …
various kinds of data in real-time and from multiple sources, which imposes additional …
Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements
Proactive traffic safety management systems can monitor traffic conditions in real-time,
identify the formation of unsafe traffic dynamics, and implement suitable interventions to …
identify the formation of unsafe traffic dynamics, and implement suitable interventions to …
IoT-enabled social relationships meet artificial social intelligence
With the recent advances of the Internet of Things (IoT), and the increasing accessibility to
ubiquitous computing resources and mobile devices, the prevalence of rich media contents …
ubiquitous computing resources and mobile devices, the prevalence of rich media contents …
Connected vehicle as a mobile sensor for real time queue length at signalized intersections
With the development of intelligent transportation system (ITS) and vehicle to X (V2X), the
connected vehicle is capable of sensing a great deal of useful traffic information, such as …
connected vehicle is capable of sensing a great deal of useful traffic information, such as …
Gap, techniques and evaluation: traffic flow prediction using machine learning and deep learning
The development of the Internet of Things (IoT) has produced new innovative solutions, such
as smart cities, which enable humans to have a more efficient, convenient and smarter way …
as smart cities, which enable humans to have a more efficient, convenient and smarter way …
Incorporating kinematic wave theory into a deep learning method for high-resolution traffic speed estimation
We propose a kinematic wave-based Deep Convolutional Neural Network (Deep CNN) to
estimate high-resolution traffic speed fields from sparse probe vehicle trajectories. We …
estimate high-resolution traffic speed fields from sparse probe vehicle trajectories. We …
ShieldTSE: A privacy-enhanced split federated learning framework for traffic state estimation in IoV
Traffic state estimation (TSE) is attracting significant attention due to its importance to the
Internet of Vehicles (IoV) for various applications, such as vehicle path planning. In classic …
Internet of Vehicles (IoV) for various applications, such as vehicle path planning. In classic …
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 …
sensor network for vehicular clients is used in Internet of Vehicles based solutions for traffic …
Uncertainty estimation of connected vehicle penetration rate
Knowledge of the connected vehicle (CV) penetration rate is crucial for realizing numerous
beneficial applications during the prolonged transition period to full CV deployment. A recent …
beneficial applications during the prolonged transition period to full CV deployment. A recent …
Traffic prediction using multifaceted techniques: A survey
Road transportation is the largest and complex nonlinear entity of the traffic management
system. Accurate prediction of traffic-related information is necessary for an effective …
system. Accurate prediction of traffic-related information is necessary for an effective …