Directed by Michel Bierlaire, the Transport and Mobility Laboratory is active in modeling, optimization and simulation of transportation systems, with a specific emphasis on the mobility of individuals.

This webpage contains the academic output of the laboratory. We are committed to open science. Links to the specific documents are available. Also, if you click on the bibtex button next to a reference, it gives you access to the reference in bibtex format, that you can copy and paste to your bibliography file.

2024

• Ilinov P., Matveenko A., Senkov M., Starkov E. (2024). Optimally Biased Expertise. Report TRANSP-OR 240223bibtex

  
  @TechReport{IlinMatvSenkStar24,
    author = {Pavel Ilinov and Andrei Matveenko and Maxim Senkov and Egor Starkov},
    title = {Optimally Biased Expertise},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240223},
    address = {Lausanne, Switzerland}}}
  

• Ortelli N., de Lapparent M., Varotto S., Bierlaire M. (2024). An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior. Report TRANSP-OR 240101bibtex

  
  @TechReport{OrteLappVaroBier2024,
    author = {Nicola Ortelli and Matthieu {de Lapparent} and Silvia Varotto and Michel Bierlaire},
    title = {An integrated ordered logit and latent variable model for accident injury severity and risk-taking behavior},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 240101},
    address = {Lausanne, Switzerland}}}
  

• Ricard L., Bierlaire M. (2024). 50 years of behavioral models for transportation and logistics. Report TRANSP-OR 220408bibtex

  
  @TechReport{RicaBier24,
    author = {L\'ea Ricard and Michel Bierlaire},
    title = {50 years of behavioral models for transportation and logistics},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2024},
    type = {Technical Report},
    number = {TRANSP-OR 220408},
    address = {Lausanne, Switzerland}}}
  

2023

• Bierlaire M., Paschalidis E. (2023). Estimating MEV models with samples of alternatives. Report TRANSP-OR 231225bibtex

  
  @TechReport{BierPasc24,
    author = {Michel Bierlaire and Evangelos Paschalidis},
    title = {Estimating MEV models with samples of alternatives},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 231225},
    address = {Lausanne, Switzerland}}}
  

• Haering T., Legault R., Torres F., Ljubic I., Bierlaire M. (2023). Exact Algorithms for Continuous Pricing with Advanced Discrete Choice Demand Models. Report TRANSP-OR 231211bibtex

  
  @TechReport{HaerLegaTorrLjubBier2023,
    author = {Tom Haering and Robin Legault and {Fabian Alejandro} Torres and Ivana Ljubic and Michel Bierlaire},
    title = {Exact Algorithms for Continuous Pricing with Advanced Discrete Choice Demand Models},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 231211},
    address = {Lausanne, Switzerland}}}
  

2024

• Rezvany N., Hillel T., Bierlaire M. Intra-household interactions in ABMs: Household-level choice set generation and parameter estimation June 19, 2024. 12th symposium of the European Association for Research in Transportation (hEART) , Espoo, Finland.bibtex

  
  @Misc{2024Rezvany_hEART,
    author = {Negar Rezvany and Tim Hillel and Michel Bierlaire},
    title = {Intra-household interactions in ABMs: Household-level choice set generation and parameter estimation},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Rezvany_hEART.pdf}},
    year = {2024},
    note = {Presented at 12th symposium of the European Association for Research in Transportation (hEART) , Espoo, Finland}}}
  

• Bierlaire M. Combining behavioral models and optimization to assess climate change actions June 13, 2024. Action Inaction Climate Change Symposium, Munster, France.bibtex

  
  @Misc{2024AICC,
    author = {Michel Bierlaire},
    title = {Combining behavioral models and optimization to assess climate change actions},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024AICC.pdf}},
    year = {2024},
    note = {Presented at Action Inaction Climate Change Symposium, Munster, France}}}
  

• Haering T., Legault R., Torres F., Bierlaire M. Fast algorithms for (capacitated) continuous pricing with discrete choice demand models June 07, 2024. 16th workshop on Discrete Choice Models, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.bibtex

  
  @Misc{2024Haering_DCM,
    author = {Tom Haering and Robin Legault and {Fabian Alejandro} Torres and Michel Bierlaire},
    title = {Fast algorithms for (capacitated) continuous pricing with discrete choice
  
  demand models},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Haering_DCM.pdf}},
    year = {2024},
    note = {Presented at 16th workshop on Discrete Choice Models, Ecole Polytechnique F\éd\érale de Lausanne, Lausanne, Switzerland}}}
  

• Kukic M., Bierlaire M. Hybrid Simulator for Projecting Synthetic Households in Unforeseen Events June 07, 2024. 16th workshop on Discrete Choice Models, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.bibtex

  
  @Misc{2024Kukic_DCM,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Hybrid Simulator for Projecting Synthetic Households in Unforeseen Events},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Kukic_DCM.pdf}},
    year = {2024},
    note = {Presented at 16th workshop on Discrete Choice Models, Ecole Polytechnique F\éd\érale de Lausanne, Lausanne, Switzerland}}}
  

• Rezvany N., Hillel T., Bierlaire M. An application of DCM in household scheduling: Choice set generation and parameter estimation June 07, 2024. 16th workshop on Discrete Choice Models, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.bibtex

  
  @Misc{2024Rezvany_DCM,
    author = {Negar Rezvany and Tim Hillel and Michel Bierlaire},
    title = {An application of DCM in household scheduling: Choice set generation and parameter estimation},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2024Rezvany_DCM.pdf}},
    year = {2024},
    note = {Presented at 16th workshop on Discrete Choice Models, Ecole Polytechnique F\éd\érale de Lausanne, Lausanne, Switzerland}}}
  

Accepted for publication

• Beine M., Bierlaire M., Docquier F. (to appear). New York, Abu Dhabi, London or Stay at Home? Using a Cross-Nested Logit Model to Identify Complex Substitution Patterns in Migration. Journal of Economic Geography (accepted for publication on Jan 16, 2024)bibtex

  
  @Article{BeinBierDocq24,
    author = {Michel Beine and Michel Bierlaire and Fr\'ed\'eric Docquier},
    title = {New York, Abu Dhabi, London or Stay at Home? Using a Cross-Nested Logit Model to Identify Complex Substitution Patterns in Migration},
    journal = {Journal of Economic Geography},
    year = {to appear},
    note = {Accepted on Jan 16, 2024}}}
  

2024

• Obrenovic N., Atac S., Bierlaire M. (2024). Light electric vehicle sharing systems: Functional design of a comprehensive decision making solution. Transportation Research Part A: Policy and Practice 182 (104043)abstract

  The functional design of a decision support system for a state-of-the-art vehicle sharing system (VSS) inevitably includes the selection or definition of methodologies for planning and managing the observed VSS. In this paper, our focus is on an innovative VSS that utilizes light electric vehicles. Our goal is to specify the functions of a comprehensive decision making solution for such a VSS through a qualitative and systematic literature and system analysis. To achieve this goal, we rely on the holistic VSS management framework developed in our previous research. As a result of our study, we identify possible solution methodologies or algorithms for implementing functions of the designed decision making solution, and propose the necessary adjustments for their application in the case of light electric vehicles, or note any research gap. With these findings, we provide justified guidance to practitioners in creating these solutions, with the aim of reducing development time.

  bibtex

  
  @Article{ObreAtacBier24,
    author = {Nikola Obrenovic and Selin Atac and Michel Bierlaire},
    title = {Light electric vehicle sharing systems: Functional design of a comprehensive decision making solution},
    journal = {Transportation Research Part A: Policy and Practice},
    year = {2024},
    volume = {182},
    number = {104043},
    DOI = {10.1016/j.tra.2024.104043},
    note = {Accepted on Mar 09, 2024}}}
  

• Ortelli N., de Lapparent M., Bierlaire M. (2024). Resampling Estimation of Discrete Choice Models. Journal of Choice Modelling 50 (100467)abstract

  In the context of discrete choice modeling, the extraction of potential behavioral insights from large datasets is often limited by the poor scalability of maximum likelihood estimation. This paper proposes a simple and fast dataset-reduction method that is specifically designed to preserve the richness of observations originally present in a dataset, while reducing the computational complexity of the estimation process. Our approach, called LSH-DR, leverages locality-sensitive hashing to create homogeneous clusters, from which representative observations are then sampled and weighted. We demonstrate the efficacy of our approach by applying it on a real-world mode choice dataset: the obtained results show that the samples generated by LSH-DR allow for substantial savings in estimation time while preserving estimation efficiency at little cost.

  bibtex

  
  @Article{OrteLappBier2024,
    author = {Nicola Ortelli and Matthieu {de Lapparent} and Michel Bierlaire},
    title = {Resampling Estimation of Discrete Choice Models},
    journal = {Journal of Choice Modelling},
    year = {2024},
    volume = {50},
    number = {100467},
    DOI = {10.1016/j.jocm.2023.100467},
    note = {Accepted on Dec 20, 2023}}}
  

2023

• Rezvany N., Bierlaire M., Hillel T. (2023). Simulating intra-household interactions for in- and out-of-home activity scheduling. Transportation Research Part C: Emerging Technologies 157 (104362)abstract

  Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly based on the individual decision-making process, which are limited in their demonstration of behaviour. We simulate multiple intra-household interaction dimensions within the same framework and capture the coordination of the activity scheduling decisions among all household members. Our approach adopts the Optimisation-based Activity Scheduling Integrating Simultaneous choice dimensions (OASIS) framework, which is at the level of isolated individuals and focuses on out-of-home activity schedules. We jointly simulate in- and out-of-home activities and incorporate interactions into the framework. Our framework contributes to the state-of-the-art in activity-based modelling by explicitly capturing multiple interactions within the same model, such as the allocation of the private vehicle to household members, dividing household maintenance responsibilities, escorting, joint activity participation, and sharing rides. We operationalise the model using time-use-survey data from the United Kingdom. The simulation results demon- strate the ability of the framework to capture complex intra-household interactions. We then demonstrate how these interactions can cause individuals to deviate from their schedules planned in isolation. This is a general framework applicable to different household compositions and available resources.

  bibtex

  
  @Article{RezBieHil23,
    author = {Negar Rezvany and Michel Bierlaire and Tim Hillel},
    title = {Simulating intra-household interactions for in- and out-of-home activity scheduling},
    journal = {Transportation Research Part C: Emerging Technologies},
    year = {2023},
    volume = {157},
    number = {104362},
    DOI = {10.1016/j.trc.2023.104362},
    note = {Accepted on Sep 26, 2023}}}
  

• Krueger R., Bierlaire M., Bansal P. (2023). A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections . Transportation Research Part C: Emerging Technologies 152 (104180)abstract

  Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical models for ride-sourcing demand estimation at an aggregate level due to limited data availability. These models lack foundations in microeconomic theory, ignore competition of ride-sourcing with other travel modes, and cannot be seamlessly integrated into existing individual-level (disaggregate) activity-based models to evaluate system-level impacts of ride-sourcing services. In this paper, we present and apply an approach for estimating ride-sourcing demand at a disaggregate level using discrete choice models and multiple data sources. We first construct a sample of trip-based mode choices in Chicago, USA by enriching household travel survey with publicly available ride-sourcing and taxi trip records. We then formulate a multivariate extreme value-based discrete choice model with sampling and endogeneity corrections to account for the construction of the estimation sample from multiple data sources and endogeneity biases arising from supply-side constraints and surge pricing mechanisms in ride-sourcing systems. Our analysis of the constructed dataset reveals insights into the influence of various socio-economic, land use and built environment features on ride-sourcing demand. We also derive elasticities of ride-sourcing demand relative to travel cost and time. Finally, we illustrate how the developed model can be employed to quantify the welfare implications of ride-sourcing policies and regulations such as terminating certain types of services and introducing ride-sourcing taxes.

  bibtex

  
  @Article{KrueBierBans23,
    author = {Rico Krueger and Michel Bierlaire and Prateek Bansal},
    title = {A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections },
    journal = {Transportation Research Part C: Emerging Technologies},
    year = {2023},
    volume = {152},
    number = {104180},
    DOI = {10.1016/j.trc.2023.104180},
    note = {Accepted on May 17, 2023}}}