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.

• Prof. Yousef Maknoon, Faculty of Technology, Policy, and Management, TU Delft
  • Context-Aware Assortment Optimization in Platform-Based Urban Mobility
  • Oct 12, 2023, 11:30, TBD
  • bio
    Yousef Maknoon is a faculty member at the Faculty of Technology, Policy, and Management (TPM) at TU Delft. He is also the director of Orbit Lab, a research group specializing in Operations Research and Behavioral Informatics in Transportation. His research takes a multidisciplinary approach, firmly rooted in operations research, to tackle emerging challenges in the transport and logistics domain. In recent years, his primary focus has been on the design and operational strategies for on-demand and instant logistics services, driving the evolution of this dynamic field.
  • abstract
    This study delves into the role of context effects in assortment optimization for platform-based urban mobility services, challenging the assumptions of classical Random Utility Maximization (RUM) models. We employ the Random Regret Minimization (RRM) model and introduce a novel 'Marginal Decoy Policy' specifically designed to capture behavioral anomalies arising from context effects. Through comparative analyses with established models such as Multinomial Logit (MNL) and Generalized Random Regret Minimization (G-RRM), we demonstrate the efficacy of our approach. The findings elucidate new strategies for dynamic service menu optimization, significantly enhancing customer satisfaction and retention by taking context effects into account.

• Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, EPFL, Lausanne, Switzerland, Feb 11, 2024 - Feb 15, 2024
  • Role: Founder, organizer and lecturer
• Winter School on Optimization and Operations Research, Hotel Europe, Zinal, Jan 14, 2024 - Jan 19, 2024
  • Role: Organizer

2023

• Bierlaire M. (2023). A short introduction to Biogeme. Report TRANSP-OR 230620bibtex

  
  @TechReport{Bier23,
    author = {Michel Bierlaire},
    title = {A short introduction to Biogeme},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 230620},
    address = {Lausanne, Switzerland}}}
  

• Kukic M., Bierlaire M. (2023). Divide-and-conquer one-step simulator for the generation of synthetic households. Report TRANSP-OR 230408bibtex

  
  @TechReport{KukicLiBierlaire2023,
    author = {Marija Kukic and Michel Bierlaire},
    title = {Divide-and-conquer one-step simulator for the generation of synthetic households},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 230408},
    address = {Lausanne, Switzerland}}}
  

• Ortelli N., de Lapparent M., Bierlaire M. (2023). Resampling estimation of discrete choice models. Report TRANSP-OR 230330bibtex

  
  @TechReport{OrteLappBier2023,
    author = {Nicola Ortelli and Matthieu {de Lapparent} and Michel Bierlaire},
    title = {Resampling estimation of discrete choice models},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 230330},
    address = {Lausanne, Switzerland}}}
  

• Bierlaire M., Ortelli N. (2023). Assisted specification with Biogeme 3.2.12. Report TRANSP-OR 230816bibtex

  
  @TechReport{BierOrte23,
    author = {Michel Bierlaire and Nicola Ortelli},
    title = {Assisted specification with Biogeme 3.2.12},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    number = {TRANSP-OR 230816},
    address = {Lausanne, Switzerland}}}
  

• Rezvany N., Bierlaire M., Hillel T. (2023). Simulating intra-household interactions for in- and out-of-home activity scheduling. Report bibtex

  
  @TechReport{RezHilBie2023,
    author = {Negar Rezvany and Michel Bierlaire and Tim Hillel},
    title = {Simulating intra-household interactions for in- and out-of-home
  
  activity scheduling},
    institution = {Transport and Mobility Laboratory, Ecole Polytechnique F\'ed\'erale de Lausanne},
    year = {2023},
    type = {Technical Report},
    address = {Lausanne, Switzerland}}}
  

2023

• Pougala J., Hillel T., Bierlaire M. Modelling the impact of activity duration on utility-based scheduling decisions: a comparative analysis September 06, 2023. 11th Symposium of the European Association for Research in Transportation, ETHZ, Zurich, Switzerland.bibtex

  
  @Misc{Pougala_hEART2023,
    author = {Janody Pougala and Tim Hillel and Michel Bierlaire},
    title = {Modelling the impact of activity duration on utility-based scheduling decisions: a comparative analysis},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/Pougala_hEART2023.pdf}},
    year = {2023},
    note = {Presented at 11th Symposium of the European Association for Research in Transportation, ETHZ, Zurich, Switzerland}}}
  

• Pougala J., Hillel T., Bierlaire M. Modelling the impact of activity duration on utility-based scheduling decisions September 05, 2023. MatSIM User Meeting, ETHZ, Zurich, Switzerland.bibtex

  
  @Misc{Pougala_MUM2023,
    author = {Janody Pougala and Tim Hillel and Michel Bierlaire},
    title = {Modelling the impact of activity duration on utility-based scheduling decisions},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/Pougala_MUM2023.pdf}},
    year = {2023},
    note = {Presented at MatSIM User Meeting, ETHZ, Zurich, Switzerland}}}
  

• Rezvany N., Hillel T., Bierlaire M. Simulating multiple intra-household interactions in ABMs July 20, 2023. World Conference on Transport Research (WCTR), Montreal, Canada.bibtex

  
  @Misc{Rezvany_WCTR2023,
    author = {Negar Rezvany and Tim Hillel and Michel Bierlaire},
    title = {Simulating multiple intra-household interactions in ABMs },
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/Rezvany_WCTR2023.pdf}},
    year = {2023},
    note = {Presented at World Conference on Transport Research (WCTR), Montreal, Canada}}}
  

• Bierlaire M. Solving a pricing problem under irrational behavior July 18, 2023. Seminar of the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making, Polytechnique Montréal, Montréal, Canada.bibtex

  
  @Misc{montreal2023,
    author = {Michel Bierlaire},
    title = {Solving a pricing problem under irrational behavior},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/montreal2023.pdf}},
    year = {2023},
    note = {Presented at Seminar of the Canada Excellence Research Chair in Data Science for Real-Time Decision-Making, Polytechnique Montr\éal, Montr\éal, Canada}}}
  

• Haering T., Ljubic I., Bierlaire M. A Spatial Branch and Benders Decomposition Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling June 29, 2023. Network Optimization Workshop, CIRRELT, Montréal, La Spezia, Italy.bibtex

  
  @Misc{2023NOW,
    author = {Tom Haering and Ivana Ljubic and Michel Bierlaire},
    title = {A Spatial Branch and Benders Decomposition Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling},
    howpublished = {\url{https://transp-or.epfl.ch/documents/talks/2023NOW.pdf}},
    year = {2023},
    note = {Presented at Network Optimization Workshop, CIRRELT, Montr\éal, La Spezia, Italy}}}
  

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 Technologiesabstract

  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},
    note = {Accepted on Sep 26, 2023}}}
  

• Pougala J., Hillel T., Bierlaire M. (2023). OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions. Transportation Research Part C: Emerging Technologies 155 bibtex

  
  @Article{PougHillBier23,
    author = {Janody Pougala and Tim Hillel and Michel Bierlaire},
    title = {OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions},
    journal = {Transportation Research Part C: Emerging Technologies},
    year = {2023},
    volume = {155},
    DOI = {10.1016/j.trc.2023.104291
  
  }}}
  

• Mastora C., Paschalidis E., Nikiforiadis A., Basbas S. (2023). Pedestrian Crossings as a Means of Reducing Conflicts between Cyclists and Pedestrians in Shared Spaces. Sustainability 15 (12)bibtex

  
  @Article{MastPaschNikifBas,
    author = {Chrysanthi Mastora and Evangelos Paschalidis and Andreas Nikiforiadis and Socrates Basbas},
    title = {Pedestrian Crossings as a Means of Reducing Conflicts between
  
  Cyclists and Pedestrians in Shared Spaces},
    journal = {Sustainability},
    year = {2023},
    volume = {15},
    number = {12},
    DOI = {https://doi.org/10.3390/su15129377}}}
  

• 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}}}
  

• Gerzinic N., Cats O., van Oort N., Hoogendoorn-Lanser S., Bierlaire M., Hoogendoorn S. (2023). An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability. Travel Behaviour and Society 33 (100616)abstract

  Understanding user’s perception of service variability is essential to discern their overall perception of any type of (transport) service. We study the perception of waiting time variability for ride-hailing services. We carried out a stated preference survey in August 2021, yielding 936 valid responses. The respondents were faced with static pre-trip information on the expected waiting time, followed by the actually experienced waiting time for their selected alternative. We analyse this data by means of an instance-based learning (IBL) approach to evaluate how individuals respond to service performance variation and how this impacts their future decisions. Different novel specifications of memory fading, captured by the IBL approach, are tested to uncover which describes the user behaviour best. Additionally, existing and new specification of inertia (habit) are tested. Our model outcomes reveal that the perception of unexpected waiting time is within the expected range of 2–3 times the value-of-time. Travellers seem to place a higher reward on an early departure compared to a penalty for a late departure of equal magnitude. A cancelled service, after having made a booking, results in significant disutility for the passenger and a strong motivation to shift to a different provider. Considering memory decay, our results show that the most recent experience is by far the most relevant for the next decision, with memories fading quickly in importance. The role of inertia seems to gain importance with each additional consecutive choice for the same option, but then resetting back to zero following a shift in behaviour.

  bibtex

  
  @Article{GerzCatsVanOHoogBierHoog23,
    author = {Nejc Gerzinic and Oded Cats and Niels {van Oort} and Sascha Hoogendoorn-Lanser and Michel Bierlaire and Serge Hoogendoorn},
    title = {An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability},
    journal = {Travel Behaviour and Society},
    year = {2023},
    volume = {33},
    number = {100616},
    DOI = {10.1016/j.tbs.2023.100616},
    note = {Accepted on Feb 04, 2023}}}