Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 28 for “"Traffic Prediction"”.
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Development and evaluation of traffic prediction systems
Developing real-time traffic diversion strategies is a major issue of Advanced Traffic Management Systems (ATMS), a component of Intelligent Vehicle Highway Systems (IVHS). Traffic diversion utilizes available capacity in the urban network during a congestion-causing event. If an alternative route …
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Incorporating neural network traffic prediction into freeway incident detection
… Neural network models have been applied to traffic prediction frequently and even repeatedly because of its superior capability in emulating nonlinear systems. However, these traffic prediction models have not been utilized for incident detection. On the other hand, it is expected that the …
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Traffic prediction and navigation using historical and current information
We developed a traffic prediction and navigation system that deals with uncertainty of road traffic conditions by stochastic modeling of road networks. Our system consists of a data collecting system, a data management system, and a path planning system. First, the data collecting system gathers …
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A novel spatiotemporal framework for efficient traffic prediction and visualization
This thesis proposes an efficient traffic prediction framework to estimate congestion at intersections depending on neighboring road links. The framework encompasses three major components, data extraction, Bayesian Linear Regression-based traffic prediction model, and an interactive map-based …
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Deep Learning Models for Traffic Prediction in Urban Transport Networks.
… long travel time, increasingly persistent traffic congestion, accidents and road safety concerns. The research work in this thesis aims to predict traffic in urban transport networks which are capable of solving those issues. Understanding and control of traffic patterns are fundamental …
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Machine-Learning based Ship Traffic Prediction in the Suez Canal
… for predicting the average annual daily ship traffic (AADT) of ships within the Suez Canal with a focus on evaluating how deep-learning techniques can be leveraged for both approaches. The first approach is a novel method that utilizes both satellite imagery and AIS technology to predict the …
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A Framework for Generalizing Uncertainty in Mobile Network Traffic Prediction
… infrastructure. One such algorithm is network traffic prediction, playing a crucial role in the efficient operation of real-time and near-real-time network management. The contributions of this thesis are twofold. The first introduces a novel cluster-train-predict framework that leverages …
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Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction
Short-term vehicle traffic forecasting is about predicting how traffic indicators are going to be in the near future. The main traffic parameters are: traffic volume, traffic speed, and congestion state. In this thesis, we propose a convolutional neural net-work model that performs traffic …
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Large scale urban patterns in NYC: traffic prediction and analysis via clustering and low rank approximation
Traffic management is one of the persistent challenges of the modern industrialized world.It simultaneously reflects both a critical infrastructural necessity and a problem involving a wide range of scales and interactions. Like many sectors and spaces, transportation systems can benefit from novel …
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A Comparative Study of Machine Learning Models for Multivariate NextG Network Traffic Prediction with SLA-based Loss Function
… the need to develop a robust, reliable network traffic prediction framework for intelligent network management increases. This study compares the performance of machine learning models in network traffic prediction using a custom Service-Level Agreement (SLA) - based loss function to ensure SLA …
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Detection of network anomalies and novel attacks in the internet via statistical network traffic separation and normality prediction
… which relies on the analysis of network traffic and the characterization of the dynamic statistical properties of traffic normality, in order to accurately and timely detect network anomalies. Anomaly detection is based on the concept that perturbations of normal behavior suggest the …
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Dynamic bandwidth management with service differentiation over ethernet passive optical networks
… facilitate statistical multiplexing among local traffics. This dissertation addresses the upstream bandwidth allocation over EPONs. An efficient mechanism, i.e., limited sharing with traffic prediction (LSTP), has been proposed to arbitrate the upstream bandwidth among ONUs. The MultiPoint …
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QoS provisioning in multimedia streaming
… and challenging problem. When multimedia traffic is transported over a network, video traffic, though usually compressed/encoded for bandwidth reduction, still consumes most of the bandwidth. In addition, compressed video streams typically exhibit highly variable bit rates as well as long …
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Road Traffic Flow Prediction Using Aerial Imagery
… networks. Among other tasks, monitoring road traffic flow is a task well-suited for such networks. While real-time traffic flow estimation systems have been explored at length and exist as commercial services, these systems have limited spatial reasoning and suffer in accuracy when predicting …
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Traffic impact assessment and mitigation strategies for disruptions
… This dissertation research focuses on modeling traffic conditions affected by disruptive events such as work zones, incidents, and hurricanes. Using a combination of field data and simulation experiments, this research tried to address the relationship between disruptive events and their impact …
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Modeling And Dynamic Resource Allocation For High Definition And Mobile Video Streams
Video streaming traffic has been surging in the last few years, which has resulted in an increase of its Internet traffic share on a daily basis. The importance of video streaming management has been emphasized with the advent of High Definition: HD) video streaming, as it requires by its nature …
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Dynamic graph neural network framework for real-time multi-modal data analysis and predictive modeling
… through extensive use cases. For instance, in traffic prediction, experiments using datasets such as Performance Measurement System Bay Area (PEMS-BAY), Metropolitan Traffic Los Angeles (METR-LA), and other PeMS Performance Measurement System datasets demonstrate the framework’s superior …
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A framework for smart traffic management using heterogeneous data sources
Traffic congestion constitutes a social, economic and environmental issue to modern cities as it can negatively impact travel times, fuel consumption and carbon emissions. Traffic forecasting and incident detection systems are fundamental areas of Intelligent Transportation Systems (ITS) that have …
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Constrained extended Kalman filter : an efficient improvement of calibration for dynamic traffic assignment models
… of inputs and parameters) for dynamic traffic assignment (DTA) systems is a crucial process for traffic prediction accuracy, and thus critical to global traffic management applications to reduce traffic congestion. In support of the real-time traffic management, the DTA calibration …
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Studies of Dynamic Bandwidth Allocation for Real-Time VBR Video Applications
Variable bit rate (VBR) compressed video traffic, such as live video news, is expected to account for a large portion of traffic in future integrated networks. This real-time video traffic has strict delay and loss requirements, and exhibits burstiness over multiple time scales, thus imposing a …
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