Concept

Traffic message channel

Related publications (61)

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

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 ...

Basel2023

Multivariate time series forecasting for freeway networks

Semin Kwak

This dissertation introduces traffic forecasting methods for different network configurations and data availability.Chapter 2 focuses on single freeway cases.Although its topology is simple, the non-linearity of traffic features makes this prediction still ...

EPFL2022

L'évaporation du trafic, opportunités et défis pour la mobilité d'aujourd'hui et demain

Pauline Geneviève Thérèse Hosotte

This research is the result of four years of practical and scientific investigation of the phenomenon of traffic evaporation, which was considered and then demonstrated to be the opposite of traffic induction. It has anchored, in practice and in time, an o ...

EPFL2022

Deficit Round-Robin: A Second Network Calculus Analysis

Jean-Yves Le Boudec, Seyed Mohammadhossein Tabatabaee

Deficit Round-Robin (DRR) is a widespread scheduling algorithm that provides fair queueing with variable-length packets. Bounds on worst-case delays for DRR were found by Boyer et al., who used a rigorous network calculus approach and characterized the ser ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Deficit Round-Robin: A Second Network Calculus Analysis

Jean-Yves Le Boudec, Seyed Mohammadhossein Tabatabaee

Deficit Round-Robin (DRR) is a widespread scheduling algorithm that provides fair queueing with variable-length packets. Bounds on worst-case delays obtained with DRR were found by Boyer et al. They used a rigorous network calculus approach and characteriz ...

2021

Collecting Large-Scale Traffic Data with a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

The new era of “big data” requires going past the current conventional methods for gathering traffic information that until now depend either on fixed-area sensors or GPS devices. Unmanned Aerial Systems (UAS) or just "drones" have been proposed as a moder ...

2020

MorphIT: Morphing Packet Reports for Internet Transparency

Bryan Alexander Ford, Georgia Fragkouli

Can we improve Internet transparency without worsening user anonymity? For a long time, researchers have been proposing transparency systems, where traffic reports produced at strategic network points help assess network behavior and verify service-level a ...

Sciendo2019

Dynamic Clustering and Control for Large Scale Urban Networks

Mohammadreza Saeedmanesh

Traffic congestion is a significant issue in all urban areas with concentration of activities for various city topologies and distribution of population and land use around the world. Developing realistic models that are able to replicate congestion spread ...

EPFL2018

Virtual Traffic Lights: System Design and Implementation

Aurélien Pomini, Sami Ben Hassen, Frank Schmutz

Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual Traffic Lights (VTL) has been proposed for mitigating traffic congestion. V ...

IEEE2018

Economic Model Predictive Control of Large-Scale Urban Road Networks via Perimeter Control and Regional Route Guidance

Nikolaos Geroliminis, Isik Ilber Sirmatel

Local traffic control schemes fall short of achieving coordination with other parts of the urban road network, whereas a centralized controller based on the detailed traffic models would suffer from excessive computational burden. State estimation for deta ...

2018

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.