DYNAMIC CLUSTERING AND PROPAGATION OF CONGESTION IN LARGE TRAFFIC NETWORKS

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Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures wil ...

pNEUMA is an open large-scale dataset of naturalistic trajectories of half a million vehicles that have been collected by a one-of-a-kind experiment by a swarm of drones in the congested downtown area of Athens, Greece. A unique observatory of traffic cong ...

The fatigue provisions for bridge design in North America and Europe are highly simplified for the sake of practical implementation, in comparison with the state of the art in understanding of the true fatigue behavior. Historically, one significant simpli ...

Plant cells harness osmotic pressures to stiffen their leaves through strong turgor pressures. Key to this osmosisdriven stiffening is the confinement of liquids within semipermeable membranes that can regulate the transport of water molecules and ions. In ...

Urban proximity planning is foreseen as a solution to foster a “sustainable” city, including economic viability, environmental soundness and social inclusivity. This paper focuses on the inclusivity aspects by questioning the adoption of urban proximities: ...

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

Ridesourcing has driven a lot of attention in recent years with the expansion of companies like Uber, Lift, and many others around the world. Companies use mobile applications connected through the internet to match drivers and their passengers real-time. ...

We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are neglected in lane-based traffic. In cities, as opposed to highways, this is an o ...

In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

Time-sensitive networks, as in the context of IEEE Time-Sensitive Networking (TSN) and IETF Deterministic Networking (DetNet), offer deterministic services with guaranteed bounded latency in order to support safety-critical applications. In this thesis, we ...

ObjectiveWall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance ...

Residential ventilative cooling via natural ventilation is influenced by outdoor air pollution. However, relative to climate, outdoor air pollution is not comprehensively considered in determining the ventilative cooling potential of buildings. To assess t ...

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

Mobility scholars have long been interested in challenging the automobile's hegemony in the street, particularly by highlighting how to develop urban cycling. The article contributes to this task by explaining how one type of conflict between the bike and ...

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

DYNAMIC CLUSTERING AND PROPAGATION OF CONGESTION IN LARGE TRAFFIC NETWORKS

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Social-Transmotion: Promptable Human Trajectory Prediction

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

GreenEVT: Greensboro Electric Vehicle Testbed

pNEUMA dataset

A WIM-Based Assessment of Multiple Vehicle Presence Effects on Fatigue Damage of Highway Bridges

Osmosis-driven stiffening of structured hydrogels

Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

Modeling and Optimization of Ridesplitting Operations

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

A hybrid microscopic model for multimodal traffic with empirical observations from aerial footage

Fairness and Explainability in Clustering Problems

Worst-Case Delay Analysis of Time-Sensitive Networks with Network Calculus

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI

Influence of outdoor air pollution on European residential ventilative cooling potential

Why is the winner the best?

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Cycling Interaction Rituals in the Conflict against the Car. From the Bike Subculture to the City Scale and Beyond

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining