Research

TRANSP-OR: Tim Hillel

Tim Hillel

This page reports only the academic work registered in the databases of the Transport and Mobility Laboratory, and is not necessarily a comprehensive list of the work by Tim Hillel.

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Tim Hillel

International journals

Published

Total: 7

      Papers in conference proceedings

      • Rezvany, N., Hillel, T., and Bierlaire, M. (2023). From domestic energy demand to household activity patterns. Proceedings of the 23rd Swiss Transport Research Conference (STRC) 10-12 May, 2023.
      • Pougala, J., Hillel, T., and Bierlaire, M. (2023). From one-day to multiday activity scheduling: extending the OASIS framework. Proceedings of the 23rd Swiss Transport Research Conference (STRC) 10-12 May, 2023.
      • Rezvany, N., Hillel, T., and Bierlaire, M. (2022). A utility optimization-based framework for joint in- and out-of-home scheduling. Proceedings of the 10th symposium of the European Association for Research in Transportation (hEART) (hEART) 1-3 June 2022, 2022.
      • Pougala, J., Hillel, T., and Bierlaire, M. (2022). Parameter estimation for activity-based models. Proceedings of the 22nd Swiss Transport Research Conference (STRC) 18-20 May, 2022.
      • Rezvany, N., Hillel, T., and Bierlaire, M. (2022). Integrated in- and out-of-home scheduling framework: A utility optimization-based approach. Proceedings of the 22nd Swiss Transport Research Conference (STRC ) 18-20 May, 2022.
      • Salvadé, N., Hillel, T., Pougala, J., Haering, T., and Bierlaire, M. (2022). Representing location choice within activity-based models. Proceedings of the 22nd Swiss Transport Research Conference (STRC) 18-20 May, 2022.
      • Haering, T., Manser, P., Hillel, T., Pougala, J., Krueger, R., and Bierlaire, M. (2021). Resolving time conflicts in activity-based scheduling: A case study of Lausanne. Proceedings of the 21st Swiss Transport Research Conference (STRC) 12-14 September, 2021.
      • Pougala, J., Hillel, T., and Bierlaire, M. (2021). Choice set generation for activity-based models. Proceedings of the 21st Swiss Transport Research Conference (STRC) 12-14 September, 2021.
      • Rezvany, N., Hillel, T., and Bierlaire, M. (2021). Integrated models of transport and energy demand: A literature review and framework. Proceedings of the 21st Swiss Transport Research Conference (STRC ) 12-14 September, 2021.
      • Hillel, T., Pougala, J., Manser, P., Luethi, R., Scherr, W., and Bierlaire, M. (2020). Modelling mobility tool availability at a household and individual level: A case study of Switzerland. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
      • Ortelli, N., Hillel, T., Pereira, F. C., de Lapparent, M., and Bierlaire, M. (2020). Variable Neighborhood Search for Assisted Utility Specification in Discrete Choice Models. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
      • Pougala, J., Hillel, T., and Bierlaire, M. (2020). An optimization framework for daily activity schedules. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
      • Xie, S., Hillel, T., and Jin, Y. (2020). An Early Stopping Bayesian Data Assimilation Approach for improved Mixed Multinomial Logit transferability. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
      • Pougala, J., Hillel, T., and Bierlaire, M. (2020). Scheduling of daily activities: an optimization approach. Proceedings of the 20th Swiss Transport Research Conference (STRC) 13-14 May, 2020.
      • Hillel, T., Jin, Y., Elshafie, M. Z E B, and Bierlaire, M. (2019). Weak teachers: Assisted specification of discrete choice models using ensemble learning. Proceedings of the 8th Symposium of the European Association for Research in Transportation (HEART) 4-6 September, 2019.
      • Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Stochastic optimization with adaptive batch size: Discrete choice models as a case study. Proceedings of the 8th Symposium of the European Association for Research in Transportation (HEART) 4-6 September, 2019.
      • Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Stochastic optimization with adaptive batch size: Discrete choice models as a case study. Proceedings of the 19th Swiss Transport Research Conference (STRC) 15-17 May, 2019.
      • Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y. (2018). Validation of probabilistic classifiers. Proceedings of the 18th Swiss Transport Research Conference (STRC) 16-18 May, 2018.

      Technical reports

      Seminars

      • Hillel, T., Pougala, J., Bierlaire, M., Manser, P., Haering, T., and Luethi, R., Modelling mobility tool availability at a household and individual level: A case study of Switzerland. hEART 2020, 9th Symposium of the European Association for Research in Transportation, February 03, 2021, Lyon, France
      • Hillel, T., Pougala, J., Bierlaire, M., Scherr, W., and Manser, P., Validating disaggregate models at an aggregate scale: A case study of mobility tool ownership in Switzerland. Applied Urban Modelling 2020: Modelling the New Urban World, January 28, 2021, Cambridge, UK
      • Hillel, T., Bierlaire, M., and Jin, Y., Weak teachers: A machine learning approach for assisted specification of Discrete Choice Models. Applied Urban Modelling Workshop, University of Cambridge, September 18, 2019, Cambridge, UK
      • Hillel, T., Pougala, J., Bierlaire, M., Manser, P., and Scherr, W., Activity-based Travel Demand Forecasting: Extensions to the SBB Nationwide Model. nextRail19, International Rail and Mobility Conference, Swiss Federal Institute of Technology - ETH Zurich, September 13, 2019, Zurich, Switzerland
      • Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., Weak teachers: Assisted specification of discrete choice models using ensemble learning. hEART 2019, 8th Symposium of the European Association for Research in Transportation, Budapest University of Technology and Economics, September 04, 2019, Budapest, Hungary
      • Hillel, T., Weak teachers: assisted specification of discrete choice models using ensemble learning algorithms. Workshop on Discrete Choice Models 2019, EPFL, April 26, 2019, Lausanne, Switzerland
      • Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., A new framework for assessing classification algorithms for mode choice prediction. hEART 2018, 7th Symposium of the European Association for Research in Transportation, National Technical University of Athens, September 05, 2018, Athens, Greece
      • Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., Validation of probabilistic classifiers. 18th Swiss Transport Research Conference (STRC), May 18, 2018, Monte Verità, Ascona, Switzerland
      • Hillel, T., Elshafie, M. Z E B, and Jin, Y., A comparison of classification methods for modelling urban mode choice. Workshop on Discrete Choice Models 2017, EPFL, June 22, 2017, Lausanne, Switzerland

      Reviewing

    • Transportation Research Part C: Emerging Technologies (6)
    • Transportation Research Part B: Methodological (3)
    • Applied Soft Computing (1)
    • International Journal of Theoretical and Applied Papers on Economic Modelling (1)
    • Journal of Choice Modelling (1)
    • Journal of Transportation Engineering, Part A (1)
    • Transport Reviews (1)
    • Total: 14 reviews for 7 journals (since 2004). Per year: 2021: 2, 2020: 10, 2019: 2.

      Research projects

      Intelligent digital twins for assessing and predicting bridge road traffic demands
      Sponsor: School of Architecture, Civil and Environmental Engineering (ENAC), École polytechnique fédérale de Lausanne
      Team: Tim Hillel (PI&PM)
      Period: October 01, 2020-April 01, 2022
      Road bridges are a vital part of transportation networks, forming crucial links in natural bottleneck locations and enabling the continual flow of people and goods into, out of, and across cities. However, the analysis used for design and maintenance planning of this community-critical infrastructure is typically carried out using static models and assuming generalized traffic patterns. This analysis represents only peak loading scenarios and does not reflect the spatial and temporal variations in real-world traffic loads. The resulting uncertainty in load prediction can lead to in overengineering in bridge design as well as sub-optimal maintenance planning. Furthermore, as current analysis techniques model only maximal loads, they cannot be used to predict the maintenance condition of bridges due to fatigue from repeated loading and unloading of the bridge over time. This research aims to address these limitations by developing intelligent digital twins which can simulate the response of a bridge to realistic traffic loading scenarios. These digital twin models combine two primary elements: (i) a traffic simulation model which exploits detailed traffic count and weigh-in-motion data to generate time-dependent traffic loadings, and (ii) a detailed structural model which predicts the compliance and maintenance condition of a bridge for different maximal and cyclic loading patterns. The intelligent digital twin is intended to be generalizable to any bridge or network of bridges for which relevant data exists. This will enable these models to be used within an integrated approach to study infrastructure vulnerability and multi-hazard risk management.
      Optimization of individual mobility plans to simulate future travel in Switzerland
      Sponsor: Innosuisse (Swiss Innovation Agency)
      Team: Michel Bierlaire (PI), Tim Hillel (PM), Janody Pougala, Rico Krueger
      Period: September 01, 2020-March 01, 2022
      This project, joint with Swiss Federal Railways (SBB) will develop a new activity-based modelling approach based on optimization of individual daily mobility plans. This approach will be implemented within SBB's existing nationwide model for Switzerland for investment and service planning decisions for future transportation.
      OrgVisionPro: Automated organizational design and optimization
      Sponsor: Innosuisse (Swiss Innovation Agency)
      Team: Michel Bierlaire (PI), Rico Krueger (PM), Tim Hillel (PM), Melvin Wong, Nour Dougui
      Period: October 01, 2019-June 30, 2021
      This project, joint with CLEAP S.A., is will develop advanced analytics algorithms to propose organization design (OD) scenarios based on the existing situation, constraints, and future needs of a business. These scenarios will support organizations in shaping their future by optimizing their structure and operating models.
      Activity based travel demand forecasting
      Sponsor: Swiss Federal Railways (SBB)
      Team: Michel Bierlaire (PI), Tim Hillel (PM), Janody Pougala
      Period: March 01, 2019-March 01, 2020
      This research project aims to update and improve the microscopic activity-based demand model developed and maintained by SBB. Specifically the research intends to address the following questions: 1. Ownership of mobility instruments: Which metrics and specifications can be added to the current model, in order to improve its ability to forecast mid-and long-term ownership of mobility instruments? More specifically, how can the notion of accessibility be integrated to the current model to capture more complex mode interactions? 2. Mode choice model: Can a tour-based approach be used to model mode choice? In addition, how can the processes to estimate destination and mode choice (currently nested) be combined to generate results that are consistent with observed mobility behaviors at different time horizons (short, mid, and long-term)? 3. Tour and activity generation: How can the generation of tours and activity patterns be combined to allow modelling of joint decisions?

      Regular teaching

      Decision-aid methodologies in transportation
      Year: Spring 2022
      Section(s): Civil Engineering
      Lecturers: Tim Hillel, Nour Dougui
      Teaching assistant: Selin Atac, Janody Pougala, Marija Kukic, Negar Rezvany
      Decision-aid methodologies in transportation
      Year: Spring 2021
      Section(s): Civil Engineering
      Lecturers: Tim Hillel, Nour Dougui
      Teaching assistant: Selin Atac, Janody Pougala, Marija Kukic, Negar Rezvany
      Webpage: https://transp-or.epfl.ch/courses/decisionAid2020/index.php
      Decision-aid methodologies in transportation
      Year: Spring 2020
      Section(s): Civil Engineering
      Lecturers: Tim Hillel, Nour Dougui
      Teaching assistant: Stefano Bortolomiol, Gael Lederrey, Selin Atac, Janody Pougala
      Webpage: https://transp-or.epfl.ch/courses/decisionAid2020/index.php
      Mathematical modeling of behavior
      Year: Fall 2019
      Section(s): Mathematics, Master in Financial Engineering
      Lecturer: Michel Bierlaire
      Teaching assistant: Tim Hillel, Meritxell Pacheco, Janody Pougala, Nicola Ortelli
      Webpage: https://moodle.epfl.ch/course/view.php?id=1001
      Decision-aid methodologies in transportation
      Year: Spring 2019
      Section(s): Civil Engineering
      Lecturers: Nikola Obrenovic, Tim Hillel
      Teaching assistant: Stefano Bortolomiol, Gael Lederrey, Selin Atac
      Webpage: http://transp-or.epfl.ch/courses/decisionAid2019/index.php

      Miscellaneous lectures

      Bayesian Estimation; Individual Prediction
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, February 11, 2021
      School: EPFL
      Lecturer: Rico Krueger
      Assistant: Tim Hillel
      Introduction; Logit Estimation and Testing
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, February 08, 2021
      School: EPFL
      Lecturer: Tim Hillel
      Assistant: Cloe Cortes Balcells
      Hybrid Choice Models
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 28, 2019
      School: EPFL
      Lecturer: Yuki Oyama
      Assistant: Tim Hillel
      Bayesian Estimation; Individual Prediction
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 27, 2019
      School: EPFL
      Lecturer: Rico Krueger
      Assistants: Tim Hillel, Selin Atac, Meritxell Pacheco
      Logit Mixtures; Combining RP and SP data
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 26, 2019
      School: EPFL
      Lecturer: Meritxell Pacheco
      Assistants: Tim Hillel, Rico Krueger
      Nested Logit; Aggregate Forecasting
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 25, 2019
      School: EPFL
      Lecturer: Selin Atac
      Assistants: Meritxell Pacheco, Yuki Oyama, Tim Hillel
      Introduction; Logit Estimation; Specification Testing
      Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 24, 2019
      School: EPFL
      Lecturer: Tim Hillel
      Assistants: Meritxell Pacheco, Yuki Oyama, Selin Atac

      Project supervision

      Masters theses

      Nicolas Salvadé
      Section: Civil Engineering
      Representing destination choice sets within activity-based models
      Supervision:Janody Pougala, Tom Haering, Tim Hillel
      Expert: Patrick Manser
      21/09/2021-17/01/2022
      Isabelle Pumford
      Section: Computer science
      Simulating realistic traffic flows to predict bridge loadings
      Supervision:Tim Hillel, Michel Bierlaire
      Expert: Dimitrios Papastergiou, ASTRA
      14/09/2020-15/01/2021
      Sergej Gasparovich
      Section: Civil Engineering
      Generating daily activity schedules using machine learning
      Supervision:Janody Pougala, Tim Hillel, Michel Bierlaire
      Expert: Antonin Danalet
      17/02/2020-19/06/2020
      Jessica Hopkins
      Section: Mathematics
      Evaluation of Bootstrap methods
      Supervision:Tim Hillel, Gael Lederrey, Michel Bierlaire
      Expert: Damon Wischik
      18/02/2019-21/06/2019

      Semester projects

      • Generating choice sets of destinations for activity based applications, Nicolas Salvadé (SGC), January 29, 2021
      • Generating choice sets of transport modes for activity based applications, Benoit Pahud (SGC), January 29, 2021
      • Tour-based mode choice modelling, Adrien Nicolet (SGC), January 31, 2020
      • Investigating daily activity patterns, Sergey Gasparovich (SGC), January 31, 2020
      • Demand forecasting for a novel transportation mode, Denis Steffen (SMA), June 30, 2019
      • Automatic utility specification using machine learning techniques, Nicola Ortelli, June 08, 2018