Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

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Enhancing discrete choice models with representation learning

Alexandre Massoud Alahi, Virginie Janine Camille Lurkin

In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...

2020

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Zhenzhu Meng, Yating Hu, Chenfei Shao

Both numerical simulations and data-driven methods have been applied in dam's displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and ...

2020

A general framework for the integration of complex choice models into mixed integer optimization

Meritxell Pacheco Paneque

The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...

EPFL2020

Improve the Model Stability of Dam's Displacement Prediction Using a Numerical-Statistical Combined Model

Zhenzhu Meng, Yating Hu, Chenfei Shao

In most studies of dam's displacement prediction based on monitoring data, emphasis was given on improving the prediction accuracy, while the model stability was merely considered. This study proposed a numerical-statistical combined model which aims to im ...

2020

Cognitive workload monitoring in virtual reality based rescue missions with drones

David Atienza Alonso, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Niloofar Momeni

The use of drones in search and rescue (SAR) missions can be very cognitively demanding. Since high levels of cognitive workload can negatively affect human performance, there is a risk of compromising the mission and leading to failure with catastrophic o ...

2020

On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment

Nikolaos Geroliminis, Emmanouil Barmpounakis

The new era of sharing information and "big data" has raised our expectations to make mobility more predictable and controllable through a better utilization of data and existing resources. The realization of these opportunities requires going beyond the e ...

2020

Optimization-based Control, Estimation, and Identification of Urban Road Transport Systems

Isik Ilber Sirmatel

Urbanization intensifies as a global trend, exposing transportation networks to ever increasing levels of congestion. As network usage increases with available infrastructure, building new roads is not a solution. Design of intelligent transportation syste ...

EPFL2020

Human-friendly solutions for last-centimeter drone delivery

Przemyslaw Mariusz Kornatowski

The popularity of delivery drones is constantly increasing due to their ability to deliver packages more rapidly and economically than current transportation methods. Consequently, drones have been employed by logistics companies for delivering payloads to ...

EPFL2020

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

Charlotte Marie Bürki

The emission parameterization is a crucial part of numerical pollen dispersion models. This paper shows that Artificial Neural Networks (ANNs) can substantially improve the performance of the Ambrosia pollen emission in numerical pollen dispersion models s ...

Elsevier2019

An optimization framework for exclusive bus lane allocation in large networks with dynamic congestion

Nikolaos Geroliminis, Dimitrios Tsitsokas, Anastasios Kouvelas

Road space distribution among multiple modes of transport in urban networks has attracted the interest of several researchers and policy planners. Traditionally, these problems are solved by ignoring operational and dynamic characteristics of multi-modal c ...

2019

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