DYNAMIC CLUSTERING AND PROPAGATION OF CONGESTION IN LARGE TRAFFIC NETWORKS
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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 ...
Time to collision (TTC) is a key indicator of human locomotion, encompassing both pedestrian and vehicular traffic. Applications of the TTC concept span a wide spectrum from safety to traffic flow dynamics. However, there exists no generic formulation for ...
Recent surveys by the Mobile Lives Forum show that around 30% of the French population live locally, yet many trips under 5 km are made by car. There is therefore huge potential for a modal shift to active modes of transport (Kaufmann et al. 2020, Héran 20 ...
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 ...
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 ...