Transport and Mobility Laboratory: presentations

TRANSP-OR

    Presentations (last year: 13)

  • Changes in activity-travel behaviour of London Underground users during and after the COVID-19 pandemic, Bansal, P., Kessels, R., Krueger, R., and Graham, D. J
    Rico Krueger
    ICMC Mini Online Event
    May 28, 2021,
    [Download PDF][XML Marc]
  • Reconstructing daily schedules of individuals: a utility maximization approach, Pougala, J., Hillel, T., and Bierlaire, M.
    Michel Bierlaire
    Online
    Lunch Seminar in Economics, Department of Economics and Management, University of Luxembourg
    May 05, 2021, Luxembourg
    [Abstract][Download PDF][XML Marc]
  • Bayesian machine learning and spatial count data models: Advances in estimation and specification, Krueger, R.
    Rico Krueger
    Research seminar, Transport Division at DTU Management, Technical University of Denmark
    February 03, 2021, Copenhagen, Denmark
    [Download PDF][XML Marc]
  • Modelling mobility tool availability at a household and individual level: A case study of Switzerland, Hillel, T., Pougala, J., Bierlaire, M., Manser, P., Haering, T., and Luethi, R.
    Tim Hillel
    hEART 2020, 9th Symposium of the European Association for Research in Transportation
    February 03, 2021, Lyon, France
    [Download PDF][XML Marc]
  • A New Spatial Count Data Model with Bayesian Additive Regression Trees for Accident Hot Spot Identification, Krueger, R., Bansal, P., and Buddhavarapu, P.
    Rico Krueger
    hEART 2020: 9th Symposium of the European Association for Research in Transportation, LAET (ENTPE, University Lyon2)
    February 03, 2021, Lyon, France
    [Download PDF][XML Marc]
  • Synthetic population generation using GANs and expert knowledge, Lederrey, G., Hillel, T., and Bierlaire, M.
    Gael Lederrey
    AUM2020: Online Global Workshop
    January 28, 2021, Home
    [Download PDF][XML Marc]
  • Validating disaggregate models at an aggregate scale: A case study of mobility tool ownership in Switzerland, Hillel, T., Pougala, J., Bierlaire, M., Scherr, W., and Manser, P.
    Tim Hillel
    Applied Urban Modelling 2020: Modelling the New Urban World
    January 28, 2021, Cambridge, UK
    [Download PDF][XML Marc]
  • Activity-based models: an optimization perspective, Pougala, J., Hillel, T., and Bierlaire, M.
    Applied Urban Modelling: Urban modelling and the planning of the built environment, The Martin Centre for Architectural and Urban Studies, University of Cambridge
    November 23, 2020, online
    [Download PDF][XML Marc]
  • Activity-based models: an optimization perspective, Pougala, J., Hillel, T., and Bierlaire, M.
    Michel Bierlaire
    Applied Urban Modelling Symposium 2020, The Martin Centre for Architectural and Urban Studies, University of Cambridge
    November 23, 2020, Cambridge, UK
    [Download PDF][XML Marc]
  • Demystifying out-of-sample discrete choice prediction: What can we learn from machine learning?, Wong, M.
    Melvin Wong
    CMC Online Seminar Series 2020, Choice Modelling Centre (CMC), University of Leeds
    November 17, 2020, Leeds, UK
    [Abstract][Download PDF][XML Marc]
  • Variational Bayesian Inference for Spatial Negative Binomial Count Data Models with Unobserved Heterogeneity, Bansal, P., Krueger, R., Bierlaire, M., and Graham, D. J
    Bridging Transportation Researchers Online Conference
    August 12, 2020,
    [Download PDF][XML Marc]
  • A New Spatial Count Data Model with Bayesian Additive Regression Trees for Accident Hot Spot Identification, Krueger, R., Bansal, P., and Buddhavarapu, P.
    Rico Krueger
    Bridging Transportation Researchers Online Conference
    August 12, 2020,
    [Download PDF][XML Marc]
  • A Lagrangian decomposition scheme for the choice-based optimization framework, Pacheco, M., Gendron, B., Bierlaire, M., and Sharif Azadeh, S.
    Meritxell Pacheco
    OR seminar, Erasmus University Rotterdam
    June 26, 2020,
    [Abstract][Download PDF][XML Marc]

Expertise

  • Transportation Research
  • Operations Research
  • Discrete Choice Models

Methods

Modeling, optimization, simulation