Publications associées à Data-driven fundamental models for pedestrian movements

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

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 ...

Informs2024

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

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 ...

2024

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

Alain Nussbaumer, Scott Walbridge, Matthew James Sjaarda

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 ...

2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo, Gianluca Botter

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

Pedestrian Crossings as a Means of Reducing Conflicts between Cyclists and Pedestrians in Shared Spaces

Evangelos Paschalidis

One significant and simultaneously interesting problem in urban mobility has to do with the study of shared spaces where various categories of users coexist and act together. This paper aims to examine the behavior and preferences of pedestrians and cyclis ...

2023

Commoning the touristic city. Urban pedestrian routes and the ambiguous politics of exploration

Luca Giovanni Pattaroni

This chapter explores touristic infrastructures as politics of ambiance, paying attention to the way they enable urban environment and engage pedestrians to experience cities critically. This issue will be documented through an ethnographic study of two to ...

Routledge2023

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

Nikolaos Geroliminis, Georgios Anagnostopoulos

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 ...

2023

Modeling and Optimization of Ridesplitting Operations

Caio Vitor Beojone

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. ...

EPFL2023

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

Zhixiong Jin

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

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

David Julian Gonon

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

Global, Passive Detection of Connection Tampering

Louis-Henri Manuel Jakob Merino

In-network devices around the world monitor and tamper with connections for many reasons, including intrusion prevention, combating spam or phishing, and country-level censorship. Connection tampering seeks to block access to specific domain names or keywo ...

Assoc Computing Machinery2023

Imaging radial distribution functions of complex particles by relayed dynamic nuclear polarization

Arthur César Pinon, David Lyndon Emsley, Pierrick Berruyer

Raw data and Matlab scripts from the publication at https://doi.org/10.1021/jacs.3c01279 All codes are provided free of charge and come with no warranty. Future use (original or modified) is required to cite: Zenedo data deposit at DOI 10.5281/zenodo. ...

Zenodo2023

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"

John Martin Kolinski

This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

Zenodo2023

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Felix Schürmann, Armando Romani, Michele Migliore, Luca Leonardo Bologna

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

2023

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

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

Alexandre André Robert Rigal

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 ...

Taylor & Francis Ltd2023

Data for "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis"

Cristina Martin Olmos, Anders Meibom, Stéphane Laurent Escrig, Gaëlle Delphine Toullec, Nils Rädecker, Claudia Isabella Pogoreutz, Guilhem Maurice Louis Banc-Prandi

Raw data associated with the publication "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis". Temperature profile, daily measurements, physiological measurements, element ...

Zenodo2023

E-Scan: Consuming Contextual Data with Model Plugins

Anastasia Ailamaki, Viktor Sanca

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023