Transport and Mobility Laboratory: Research projects

TRANSP-OR

All topics

We identify new solutions to transportation problems, on the ground, in the air, or on the sea, transport of people or goods, whatever the mode. We focus on technical solutions, but also on their impact on the system as a whole. We are also interested in the interactions of the transportation systems with the land use, the economy, the environment, etc.

Intelligent digital twins for assessing and predicting bridge road traffic demandsTop

Intelligent digital twins for assessing and predicting bridge road traffic demands

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.

Principal investigator
Tim Hillel
Project manager
Tim Hillel
Sponsor
School of Architecture, Civil and Environmental Engineering (ENAC), École polytechnique fédérale de Lausanne
Period
October 01, 2020-April 01, 2022
LaTeX description

Optimization of individual mobility plans to simulate future travel in SwitzerlandTop

Optimization of individual mobility plans to simulate future travel in Switzerland

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.

Principal investigator
Michel Bierlaire
Project manager
Tim Hillel
Sponsor
Innosuisse (Swiss Innovation Agency)
Period
September 01, 2020-March 01, 2022
Collaborators
Janody Pougala, Rico Krueger
External collaboration
Patrick Manser
External collaboration
Wolfgang Scherr
LaTeX description

Activity scheduling an rhythmic style: multi-day modeling of mobility habitsTop

Activity scheduling an rhythmic style: multi-day modeling of mobility habits

A growing body of research shows that the traditional approaches employed to plan and forecast travel behaviors are not equipped to deal with the heterogeneity of behaviors over time, space, and social spheres. Therefore, travel policies struggle to reconcile social inclusivity, sustainability and network efficiency. Two ENAC laboratories propose to join forces, in mathematical modeling and quantitative sociology, to develop a novel multi-day activity-scheduling framework to forecast travel demand. Integrating day-to-day correlations in travel behaviors will lead to a better understanding of the motives behind travel decisions, and will unveil more facets of individual decision making for better predictions of their daily mobility choices. This research uses the MOBIS dataset, a 8-week / 3700-respondent travel survey conducted in Switzerland in 2019. The forecasting model will be applied to the Swiss synthetic population and several scenarios will be considered.

Principal investigator
Janody Pougala
Project manager
Janody Pougala
Sponsor
School of Architecture, Civil and Environmental Engineering (ENAC), École polytechnique fédérale de Lausanne
Period
October 01, 2020-October 01, 2021
Collaborator
Marija Kukic
External collaboration
Marc-Edouard Schultheiss
LaTeX description

OrgVisionPro: Automated organizational design and optimizationTop

OrgVisionPro: Automated organizational design and 
optimization

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.

Principal investigator
Michel Bierlaire
Project managers
Rico Krueger, Tim Hillel
Sponsor
Innosuisse (Swiss Innovation Agency)
Period
October 01, 2019-June 30, 2021
Collaborators
Melvin Wong, Nour Dougui
External collaboration
Laurent Jaquenoud
LaTeX description

Expertise

  • Transportation Research
  • Operations Research
  • Discrete Choice Models

Methods

Modeling, optimization, simulation