Publications associées à Mitigating the impact of errors in travel time reporting on mode choice modelling

Sampling of alternatives in migration aspiration models

The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...

2023

Appropriations and Uses of Travel Time

Ludy Juliana González Villamizar

Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...

ISTE Wiley2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Prateek Bansal, Thomas Gasos

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Space allocation for multi-modal urban networks with ridesplitting services and public transport

Nikolaos Geroliminis, Lynn Fayed

The surge of Mobility on Demand (MoD) is largely attributed to advancements in mobile internet and technology. Ridesourcing platforms, among other solution services, offer convenience and flexibility when it comes to pick-up/drop-off time and location, all ...

The National Academies of Sciences, Engineering, and Medicine2022

Representing location choice within activity-based models

Michel Bierlaire, Janody Pougala, Nicolas Jean Salvadé, Timothy Michael Hillel

Since the 70s, there has been a growing interest in activity-based modelling. This approach models the need to travel as a result of performing daily activities (Bowman and Ben-Akiva, 2001). Nevertheless, the activities need to be scheduled which involves ...

2022

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

Counting People by Estimating People Flows

Pascal Fua, Mathieu Salzmann, Weizhe Liu

Modern methods for counting people in crowded scenes rely on deep networks to estimate people densities in individual images. As such, only very few take advantage of temporal consistency in video sequences, and those that do only impose weak smoothness co ...

2022

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Francesca Criscuolo

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021

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

Global maps of travel time to healthcare facilities

Kristina Gligoric

Access to healthcare is a requirement for human well-being that is constrained, in part, by the allocation of healthcare resources relative to the geographically dispersed human population(1-3). Quantifying access to care globally is challenging due to the ...

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

Estimating network travel time reliability with network partitioning

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliabili ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Carbon Footprint of Academic Air Travel: A Case Study in Switzerland

Guillaume Jean Op 't Veld, László Dániel Tóth, Aleksandra Mandic, Joachim Armand Simonne Ciers

Relatively low travel costs and abundant opportunities for research funding in Switzerland and other developed countries allow researchers large amounts of international travel and collaborations, leading to a substantial carbon footprint. Increasing willi ...

2019

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

Nikolaos Geroliminis, Anastasios Kouvelas, Dimitrios Tsitsokas

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

Dealing with Correlations in Discrete Choice Models

Anna Fernández Antolín

The focus of this thesis is to develop methods to address research challenges related to correlation patterns in discrete choice models. In the context of correlations within alternatives, we extend the novel methodology of the multiple indicator solution ...

EPFL2018

Data-driven reduced order modeling for time-dependent problems

Jan Sickmann Hesthaven, Mengwu Guo

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order ...

2018

Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets

Jeffrey Newman, Virginie Janine Camille Lurkin

Network planning models, which forecast the profitability of airline schedules, support many critical decisions, including equipment purchase decisions. Network planning models include an itinerary choice model that is used to allocate air total demand in ...

Pergamon-Elsevier Science Ltd2017

Network design of a transport system based on accelerating moving walkways

Michel Bierlaire, Iliya Dimitrov Markov, Riccardo Scarinci

Pollution, congestion and urbanistic considerations are leading to a change in the use of private vehicles in dense city centers. More frequently, the last-mile is covered with systems such as public transport, car sharing and bike sharing as well as an in ...

Pergamon-Elsevier Science Ltd2017

Intensive travel time: an obligation or a choice?

Stéphanie Vincent

This paper explores what prompts some individuals to spend a significant amount of time travelling. In the literature, travel time tends to be regarded as useless, unproductive time and, in some cases, as the worst time of the day. The actual behaviour of ...

Springer2016

Analyzing time sensitivity in the Paris subway: an interval data model approach

Matthieu Marie Cochon de Lapparent

We analyze individual travel discomfort-time tradeoffs in the Paris subway using stated choice experiments. The survey design allows to set up in a willingness-to-pay space to estimate the distributions of elasticities of values of travel time to crowd den ...

Springer2016