Publications associées à Traffic Message Channel

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 ...

MDPI2023

Influence of outdoor air pollution on European residential ventilative cooling potential

Dusan Licina, Evangelos Belias

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 ...

ELSEVIER SCIENCE SA2023

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 sti ...

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 obtained with DRR were found by Boyer et al. They used a rigorous network calculus approach and characteriz ...

2021

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Nikolaos Geroliminis, Semin Kwak

Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...

IEEE Institute of Electrical and Electronics Engineers2021

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

A Measure of Dynamical Efficiency for Multimodal Interconnected Urban Systems

Nikolaos Geroliminis, Leonardo Bellocchi

Complex network theory describes network performance mostly based on topological characteristics, like betweenness centrality. This work integrates concepts from complex networks and traffic engineering. We propose a new measure for spatial networks and, i ...

2020

Empirical analysis of large-scale multimodal traffic with multi-sensor data

Nikolaos Geroliminis, Nan Zheng, Hui Fu

Recent advances in the network-level traffic flow modelling provide an efficient tool for analyzing traffic performance of large-scale networks. A relationship between density and flow at the network level is developed and widely studied, namely the macros ...

PERGAMON-ELSEVIER SCIENCE LTD2020

MorphIT: Morphing Packet Reports for Internet Transparency

Bryan Alexander Ford, Aikaterini Argyraki, 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 ...

IEEE Institute of Electrical and Electronics Engineers2018

DYNAMIC CLUSTERING AND PROPAGATION OF CONGESTION IN LARGE TRAFFIC NETWORKS

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

The problem of clustering in urban traffic networks has been mainly studied in static framework by only considering traffic conditions at a given time. Nevertheless, it is important to underline here that traffic is a strongly time-variant process and it n ...

2017

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be ...

2017

Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be ...

2017

Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control

Nikolaos Geroliminis, Mohsen Ramezani Ghalenoei, Jack Haddad

Real traffic data and simulation analysis reveal that for some urban networks a well-defined Macroscopic Fundamental Diagram (MFD) exists, which provides a unimodal and low-scatter relationship between the network vehicle density and outflow. Recent studie ...

2015

Tutorial Session in: Large-scale hierarchical control for congested urban networks

Nikolaos Geroliminis

This tutorial describes methodologies to model and understand the collective behavior or different types of urban systems. It highlights under what physical properties the aggregated laws will provide reasonable description of congestion for single- and mu ...

Ieee2014

Cooperative navigation in robotic swarms

Francesco Mondada, Michael Bonani, Stéphane Magnenat, Philippe Rétornaz

We study cooperative navigation for robotic swarms in the context of a general event-servicing scenario. In the scenario, one or more events need to be serviced at specific locations by robots with the required skills. We focus on the question of how the s ...

Springer Verlag2013

Experienced travel time prediction for congested freeways

Nikolaos Geroliminis, Mehmet Yildirimoglu

Travel time is an important performance measure for transportation systems, and dissemination of travel time information can help travelers make reliable travel decisions such as route choice or departure time. Since the traffic data collected in real time ...

Elsevier2013