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Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems
The Intelligent Transportation System (ITS) is an important part of modern transportation infrastructure, employing a combination of communication technology, information processing and control systems to manage transportation networks.
Topics in Deep Learning and Optimization Algorithms for IoT Applications in Smart Transportation
As one of the most important vertical domains for IoT applications, smart transportation system has played a key role for providing real-world information and services to citizens by making their access to transport facilities easier and thus it is one of the key application areas to be explored in this thesis.
Lane-GNN: Integrating GNN for Predicting Drivers' Lane Change Intention
In this paper, we focus on the detection of traffic flow anomaly due to drivers' lane change intention on the highway traffic networks after a VSL system.
A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes
Accurately forecasting transportation demand is crucial for efficient urban traffic guidance, control and management.
An ADMM-based Optimal Transmission Frequency Management System for IoT Edge Intelligence
In this paper, we investigate a key problem of Internet of Things (IoT) applications in practice.
