Research projects

The Elevator Dispatching Problem with Destination Control We propose developing a Branch-and-Price (BP) exact method that can provide optimal solutions to instances. The size of the instances that BP can solve has to be determined with computational experiments once the method is implemented and cannot be known beforehand. BP is known to provide good lower bounds that can also be used to evaluate heuristic solutions. The aim of this study is to provide optimal solutions to the deterministic-static EDPDC where we have perfect information and compare with Schindler�s heuristic solution.

This project has the following content: Transport policy is currently not finding a way out of its dilemma; the imminent need to decarbonize a sector fast which has barely moved in the recent past and the social requirement to maintain and increase accessibility across all modes, but not to encourage sprawl while still allowing further decreases in the generalised cost of travel by new technologies and business models. We propose to use a radical departure from previous proposed ideas to enable the policy and transport industry to begin thinking from a different starting point. The design idea is to reallocate 50% of the existing urban road space to e-bikes, bicycles, and other micromobility modes and to assess what this change could achieve in terms of accessibility, generalised costs of travel, changes in daily life and reductions in emissions and CO2. The project will integrate careful involvement of the various stakeholders from citizens, cities, firms to interest groups, but will also provide the materials needed to communicate the ideas and their equity impacts visually and verbally at the required levels of complexity.

International migration is at the forefront of policy debates in most countries around the world. In industrialized nations, the proportion of foreigners in total population increased from 4.5 to 12 percent between 1960 and 2019, stirring up fears about economic costs for natives, loss of national identity, and integration issues. In poor countries, international migration raises concerns about the brain drain of highly-skilled workers, as college and university graduates have a much greater propensity to emigrate internationally than the less educated. Hence, the questions of how many people migrate (i.e., migration intensity}, which people migrate first or are more likely to migrate (i.e., migrants' selection), and where migrants choose to settle (i.e., migrants' sorting) have been analyzed from all possible angles in recent literature. Specifically, understanding how people revise their decisions about whether to emigrate, and where to, when facing changes in the global environment is of crucial importance for decision-makers.

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.

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.

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.

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.

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?

In this project, Schindler and TRANSP-OR imagine a revolution of urban mobility focused on pedestrians. The Personal Autonomous Moving (PAM) platforms are similar to hoverborads or segways, and move from a point A (origin) to a point B (destination) on their own and carry the user with minimum interaction. They are a �light� mode of transport that does not require large space or infrastructural investment for the installation. This innovative mode of transport is ideal for short distance trip in large pedestrian facilities such as university campuses, larger business districts and airports as well as city centers. A great advantage is the possibility to directly access elevators with PAM platforms. This could lead to a real three-dimensional mobility taking advantage of elevators already installed in buildings. A possible deployment of this system generates several scientific and technological challenges. TRANP-OR focuses on the research questions that are related to the algorithms and mathematical models used by decision support tools needed for the planning and operation of the system.

This project is conducted on a fellowship "The EuroTech Postdoc Programme". A car-free city center is a valuable solution for decreasing traffic congestion and CO2 emissions, and improving active mobility and quality of life. To achieve these goals, one of the biggest challenges is the relocation of parking places scattered in the inner district, which cause cruising for available parking as well as car inflows. A possible solution is a �fringe parking� system, which groups parking into a limited number of spots on the border of the district. However, this may decrease the level of accessibility moving the parking away from the final destinations. The key idea of this research is to use �accelerated moving walkway� (AMW), a novel transport system, in combination with a fringe parking system to design a car-free city center with high accessibility. The goal of the research is to propose and identify the optimal configuration of a fringe parking system with AMWs, as a solution to city centers. The main methodologies are network design optimization and traffic assignment.

The aim of this project is to propose a methodology to assess and optimize educational infrastructure networks based on accessibility. In 2014, the World Bank launched the Global Program for Safer Schools (GPSS) with a focus on integrating risk reduction considerations into education infrastructure policies and investments. The GPSS aims to boost and facilitate informed, large-scale investments for the safety and resilience of new and existing school infrastructure at risk from natural hazards, contributing to high-quality learning environments. Understanding accessibility of school infrastructure networks is an important element to optimize risk reduction interventions as well as to improve the quality and efficiency of the educational service. To support this goal, the Transportation and Mobility Laboratory proposes a methodology to assess and optimize educational infrastructure networks based on accessibility; and proposes solutions to improve the performance of educational infrastructure networks. In other words, researchers will evaluate the risks based on the school network, including parameters like transportation network, home location of the students, mobility patterns... They will then provide a methodology in order to help direct investments to reduce the risks in case of disaster.

The starting point of this research project is the general framework developed in the SNF research project 200021_165636 entitled �Incorporating advanced behavioral models in mixed integer linear optimization�. The project aims at formulating explicitly the complex interaction between the supply and demand actors. We hypothesize that the decisions of supply actors (such as capacity, assortment, and price) are highly influenced by the decisions of other actors, through competition within the market. In this project, we will therefore explicitly consider multiple operators that compete for the same pool of customers. Each operator will take the supply-side decisions that optimize its performance function (e.g., maximization of revenue). Non-cooperative game theory is commonly used to model such oligopolistic competition. We plan to investigate how to integrate these games in the already developed framework. In this context, the objective will be to analyze the concept of equilibrium, that is, stationary states of the system where no actor has an incentive to change his/her decisions.

Modern smartphones are more than just calling devices. They harbor a wealth of information that provides the transportation field with a new potential. In this project, researchers will create a transportation mode detection model based on telecommunication data from smartphone users combined with public transport-related data sources. The researchers are provided with anonymized telecommunication traces. As those data remain scarce, additional data will be identified from external sources including network infrastructure, route maps, time schedules in static or real-time form, microcensus, weather, etc. A probabilistic model will be developed to infer the transportation modes from those various data sources. The project lasts one year, and will be carried out by the Transport and Mobility Laboratory, directed by Prof. Michel Bierlaire. It is sponsored by Swisscom.

This project aims at developing an algorithm for the overall design of SBB cargo�s network of bundling points. SBB Cargo operates a network of 2 marshaling yards, 65 shunting yards and about 350 of small bundling points. The operation as such is costly and the network might contain redundant bundling points. The overall interest of SBB Cargo is to minimize the operating cost of their network and to compare its performance to a better network, completely designed from scratch. The resulting framework is then planned to be used to improve the current network of SBB cargo and its future development. The main research challenge of this project is to incorporate the SBB Cargo needs into one model while taking into account the specifics of the railway network and its operation. The researchers from the Transport and Mobility Laboratory (TRANSP-OR) will develop a heuristic algorithm that gives as an output a complete network design based on the inputs (cargo demand, capacity, types and costs of different bundling points). The algorithm can be further adjusted by entering the already existing bundling points. The effectiveness of the proposed algorithm will be tested thorough comparison with existing solutions. TRANSP-OR, led by prof. Michel Bierlaire, has a track record of successful projects of solving highly complex problems arising in industrial sector. This one-year project is sponsored by SBB-CFF-FFS.

To design their timetables, train-operating companies mostly focus on operational aspects and cost. In Switzerland, a paradigm of transportation planning is to create regular-interval timetables (a.k.a. cyclic timetables) which aim for maximal transfer connections, simplicity and hence user friendlyness. SBB uses travel simulation models to predict the impact of timetable changes on travel demand and revenue. Mathematical timetable optimization methods are not yet used by SBB. But a recent EPFL thesis (2016) shows that the timetable itself has a significant impact on the performance of the operator in terms of the number of transported passengers: a timetable design that considers the behavior of passengers leads to higher revenue(s), market share(s), higher value of passenger-km etc. In this project, the aim is to use the optimization methods developed by the TRANSP-OR Lab consisting in combining cyclic and non-cyclic timetables and apply it to the Swiss Federal Railways� timetable design. The goal is to evaluate the performance of the current Swiss interval timetable and to compare it to the optimal one. Suitability of hybrid timetables for the Swiss railway network will be investigated. This one-year project is carried out by the Transport and Mobility Laboratory, led by prof. Michel Bierlaire. TRANSP-OR has vast competence in modeling, optimization and simulation of transportation systems. The project is sponsored by SBB CFF FFS.

The purpose of this project is to develop graduate curriculum in urban mobility and transportation. The relevant courses of this curriculum will be available in MOOC format. This program is a collaborative project between Kwame Nkrumah University of Science and Technology (KNUST) and Urban Transport Systems Laboratory (LUTS) and Transport and Mobility Laboratory (TRANSP-OR) at EPFL.

Discrete choice models are used for detailed representation of the "demand". However, their complexity makes mathematical formulations highly non convex in the explanatory variables. On the other hand, Mixed Integer Linear Programs (MILP) are optimization problems with discrete variables that are used in many applications to design and configure the "supply". In this project, we propose a new modeling framework that allows to include any random utility model in a mixed integer optimization formulation. The heterogeneity of demand is captured within the general choice model framework and the offers are tailored in a way that is beneficial for users as wells as providers. The main objective of the project is to obtain a framework that is both general, so that it can be applied in many applications, and operational, so that it can be used in practice.

TRANS-FORM, a cooperation between universities, industrial partners, public authorities and private operators, will develop, implement and test a data driven decision making tool that will support smart planning, and proactive and adaptive operations. The objective of the project is to better understand transferring dynamics in multi-modal public transport systems and develop insights, strategies and methods to support decision makers in transforming public transport usage to a seamless travel experience by using smart data. The tool will integrate new concepts and methods of behavioral modelling, passenger flow forecasting and network state predictions into real-time operations. TRANS-FORM is funded under the European Commission Horizon 2020 ERA-NET program.

The TOSA catenary-free electric bus system is the ABB response to the challenge of decreasing the environmental impact of public transportation. The project builds on the previous CTI project - myTOSA - and it aims to introduce new business analytics features and to improve the fidelity of the simulation and (robust) optimization modules used for a cost-optimal deployment of the TOSA charging infrastructure and component sizing.

The project aims at integrating demand models in a state-of-the-art mathematical model for Location-Routing Problem (LRP) in the context of energy. We are investigating different assumptions about the representation of the demand in the context of facility location and routing problem.

This project aims to develop an onboard pedestrian tracking system to assist the driver detect them and, ultimately, to increase security. The project, with a duration of four years, will focus on pedestrians detection, tracking and trajectory prediction, and will be will be closely related to vehicle command strategies. The project is part of the automated driving research Chair "Drive for you" led by MINES ParisTech in partnership with French industrialists and three prestigious academic institutions the Ecole Polytechnique F�d�rale de Lausanne EPFL (Switzerland), the University of Shanghai Jiao Tong (China) and the University of Berkeley (USA). Supported by the Foundation MINES ParisTech, with Valeo industrial, PSA Peugeot Citro�n and Safran contributing 3.7 million euros in funds, the Chair will work for five years on the subject of automated driving. The three main objectives are expand knowledge of self-driving vehicles, develop intelligent onboard systems, get self-driving vehicles on the road in Asia, Europe and the United States.

This project proposes innovative methods to identify the determinants of acceptance of alternative vehicles and their impact on everyday mobility. The greatest challenge faced by the promoters of the transition towards this low carbon engine technology lies in understanding how consumers accept the financial and lifestyle investments associated with the leap from traditional to electric powertrains. This project proposes innovative methods to identify the determinants of acceptance of alternative vehicles and their impact on everyday mobility. A deeper understanding of adoption dynamics is critical to predict who will opt for EVs when and under which conditions. This project will focus on innovative data-collection and modelling methodologies to uncover the acceptance of EVs at different stages of market-penetration (considering inexperienced/experienced users, early pioneers/late-adopters). A thorough analysis of the consumer decision-making process will lead to uncovering the barriers and success factors related to EV uptake and to forecast buying and usage behaviours related to new vehicle classes.

Flying safer, cheaper, faster are keywords of this new service. This project aims at integrating an automatic route planning system, tightly coupled with the real-time meteorological data, taking into account energy consumption of the mobile device hosting the application. The route will be computed in real time on mobile devices using the information of weather forecast and respecting to the constraints such as airspace/airport restriction and terrain avoidance, etc. The energy efficient implementation of the routing application is crucial, to provide routing information to the pilot during the entire trip. This becomes challenging, as automatic route planning often requires complex algorithms. In this project, we will target at a three-dimensional flight route-planning problem and design an efficient but robust algorithm to solve the problem. The project will last 18 months. It is conducted by TRANSP-OR in collaboration with the Xample S�rl, ICARE Institut de recherche and Haute Ecole Sp�cialis�e de Suisse Occidentale (HES-SO).

The goal of this project is to explore the future of mobility through the role of the car. The main originality of this research is to raise the following problem: �What, if the world were a post-car world�. The basic idea is to define a hypothetical situation where the place of the car would have been dramatically reduced and to use qualitative and quantitative simulation methods to examine the consequences of this initial hypothesis. The research is based on the idea that by simulating the future through scenarios we can understand the present better. This project is fully interdisciplinary and trans-disciplinary. It brings together social sciences, engineering sciences, urban planning and urban design in six different laboratories associated to three different universities. The role of TRANSP-OR in this project is to study and optimize an innovative transport system based on accelerated moving walkways (AMW). Differently from constant moving walkways, AMW can reach speeds up to 15km/h thanks to an acceleration section. The project aims to identify the optimal design of a network of AMW using optimization. A network of accelerated moving walkway in a car-free urban environment may present an innovative solution, and this project could delineate the system feasibility.

This project aims at developing behavioral models integrating the latent constructs that drive travel behavior. The objective of the project is to set the foundations of an innovative framework that facilitates the analysis and prediction of route choice behavior. Motivated by the complexity of the route choice models, we build on solid ground of the current state of the art and add on it by proposing a new approach that reduces model complexity and brings great flexibility to the analysis. The approach is inspired by the fact that people break down the complexity of the environment by forming representations of their surrounding space. Following this reasoning, we replace the conventional representation of routes which is based on paths, i.e. link-by-link sequences on the network model, with more aggregate elements that we denote as mental representation items. This key feature of the framework allows us to reduce the complexity of the model and at the same time is more behaviorally realistic.

The objective is to achieve the first genuine contribution to the development of intercontinental logistics at the European level, in close coordination with North America partners and the international Physical Internet Initiative. The goal of the project is to enable operations with developed iso-modular logistics units of size adequate for real modal and co-modal flows of fast-moving consumer goods, providing a basis for an interconnected logistics system for 2030.

The aim of this collaborative research project between the Swiss Federal Railways (SBB-CFF-FFS) and EPFL's transportation center is to analyze, model and optimize pedestrian flows in train stations. In recent years, the growing number of passengers has led to difficulties related to pedestrian flows in major train stations. Congestion of pedestrian walkways is increasingly becoming a problem during peak hours, but also due to clustering of people caused by major events or the beginning or end of holiday season. When capacity limits for pedestrian facilities are reached, normal operation of train schedules can be significantly impaired. Since train stations are important nodes within the multimodal public transportation system, it is of major importance that they are operated as efficiently as possible. In addition to the increase in passenger numbers, train stations have been undergoing a profound transformation from simple transit nodes towards versatile hubs that provide interface to short and long-distance train connections, to other modes including private transport by foot, bike and car, as well as to the city offering public space for shopping, eating and alike. This transformation leads to a further increase in pedestrian numbers and additionally introduces new behavior patterns. A sound understanding of pedestrian flows within a train station can help improve overall level of service, customer experience and safety. The main focus of this study lies on the development of a methodology allowing to estimate pedestrian origin-destination (OD) demand within a train station. Specifically, train time table, customer survey data and flow observations from an exhaustive camera system are used as sources of information in this process. Subsequently, the modeling frame work is applied to several case studies in Switzerland.

The aim of this research project is to develop a dynamic model framework to forecast car demand. The model-system jointly accounts for behavioural variables (e.g. household evolution, individual motivations), institutional factors (e.g. incentives and taxation) and market features (e.g. new fuel or vehicle technology launches) to forecast vehicle acquisition. The project benefits from a large-scale, longitudinal dataset on vehicle transactions from major European markets. Methodologically the framework consists of a system of aggregate, disaggregate and duration-based choice models, accounting for dynamic features of the decision at each stage. Importantly, the proposed dynamic framework enhances realism by representing the durability of possession, rapid changes in value across product and ownership cycles and uncertainty about future market developments and institutional factors. The proposed framework sheds light on the timing and type of vehicle ownership, illustrating the benefits of taking the first steps away from a static approach. The findings will aid the prediction of consumer behaviour in response to critical policy variables, such as incentives, alongside market dynamics, such as the appearance and diffusion of novel technologies. A deeper understanding of future vehicle choice behaviour is critical given sizable institutional and industrial investments to promote alternative vehicle technologies with a final aim to improve energy efficiency in the transportation sector. More information http://transport.epfl.ch/car-market-structure

This project aims at developing mathematical models of pedestrian dynamics, both at aggregate and disaggregate levels. Integrated and holistic mathematical models will handle the complexity of this unique transport mode and help us to answer open research questions. in the future, such foundations will also allow to create the tools society needs to better understand pedestrian dynamics.

myTOSA is a simulation tool for the dimensioning, commercial promotion and case study set-up for ABB's revolutionary "catenary-free" 100% electric urban public mass-transportation system TOSA 2013. The objective of the project is to provide a simulation tool that will allow ABB to perform the proper dimensioning, promote the commercial idea and allow for specific study cases for the implementation of ABB's new public electric transportation concept, namely TOSA 2013.

In the framework of a 9-month collaboration with CFF, pedestrian flows in Lausanne train station are estimated and modeled. Specifically, an estimation methodology for pedestrian origin-destination demand is developed and applied to predict a demand scenario for 2030. By means of a pedestrian flow simulator, several infrastructure scenarios are quantitatively evaluated, the result of which helps CFF to design and dimension pedestrian underpasses of Gare de Lausanne for the future.

The role of local authorities in reaching climate and energy goals is important. Consolidated data about energy at the local scale is necessary in order to fully measure the effects of policies and to adapt action-plans. The goal of this project is to evaluate the feasibility of a single platform with all the relevant energy data for a local authority, in particular statistics about mobility.

The ACTUM research collaboration project involves development of an activity-based modelling framework for Copenhagen that is aimed at handling the future requirements for transport policy evaluations in Denmark.

The primary objective of this research is to develop large scale robust optimization algorithms providing sustainable solutions for bulk port operations accounting for uncertainties and disruptions in operations. While significant contributions have been made for container terminals, relatively little attention has been directed to the use of operations research methods and techniques to optimize bulk port operations. In this research we aim to develop large scale mathematical models for bulk port operations, with emphasis on integrated planning; furthermore, we plan to include robustness to account for uncertainties in operations. A broader objective of our work is to study how the methodologies developed for bulk ports can be extended to multi-modal transport operations, including other domains such as container ports, airlines and railways, with a view to optimize the usage and operations of existing infrastructure to achieve sustainability in the mobility of goods and people. The devised models and algorithms will be tested and validated in a real-world context using as a case study, the SAQR port in Ras Al Khaimah, UAE.

Sustainability has become a key topic in transportation in the last decades where the aim is to reduce the impact of transportation on the environment. One of the most important paths toward sustainability in this sector is to optimize transportation operations required in several dimensions to fulfill a given transport demand. To achieve this goal in the context of multimodal transport, there is a clear need for flexibility in capacity. This flexibility is adequately provided by a new concept developed at EPFL, named Clip-Air, for air transport. Clip-Air is a modular innovative aircraft with detachable load units which enable to adjust at best capacity according to demand. The decoupling of the load (capsules) and carrying units (wings) allows for simplified fleet management and maintenance operations for airlines and is expected to improve the ground operations for airports. Clip-Air also provides effective possibility of combining commercial freight and passengers on the same flight without any compromise in comfort. Besides, Clip-Air is designed to operate in a multi-modal context and is expected to improve the multi-modality concept by allowing a better integration between air transport and other transport modes. The objective of this research is to assess the actual impact of Clip-Air�s modularity on demand satisfaction, operational costs and environmental issues at the system level. The contributions will consist of models and algorithms designed to perform comparative analysis of operations of airlines and airports in various scenarios.

This project aims at developing methodologies for the integration of qualitative an quantitative tools for land use planning and urban project-evaluation . The methodology will allow the interaction between urban design experts and land use modelers, developing techniques to use the description of urban projects and policies as inputs for land use models like UrbanSim and transport models like MATSim. The modeling effort output is used as input for the experts, generating an iterative feedback.

Smart phones are able to collect a great wealth of information about the mobility patterns of individuals, including their itinerary. In addition to GPS tracks, smart phones contain several sensors and software revealing various aspects of the user's behavior (nearby Bluetooth devices, WiFi antenna, media players, etc.) Route choice models rely on the knowledge of the origin and the destination of the trip, and the transportation mode. They may also benefit from other contextual data, such as the trip purpose or the chain of subsequent activities. We plan to investigate how to infer this information from the smart phone data.

Minimizing operating costs for maintaining ground personnel at airports is a complex problem due to uneven flight activities, passenger service expectations and staffing inflexibilities due to shift durations. In this work, we would use the flight schedule and service criteria to develop a method to find optimal shift timings that considers non-productive time due to activity changeovers, the mix of full-time and part-time workers and passenger waiting time criteria.

Locomotive assignment at Railway companies is a complex problem that must optimally assign a set of locomotives to known, scheduled trains. Each train has a power and traction requirement and locomotives may be available in groups known as "consist". There is a cost involved in breaking or adding a locomotive to a consist. Determining an optimal locomotive assignment that would also be robust to handle delays, maintenance requirements and other unknown factors is a complex problem. We are inspired from the research in a similar, closely related subject in the airline industry and would explore the possibilities of extending the same to railways. This project would be a part of the larger concept of "Flexible Transportation Systems"

Evaluation de la demande des consommateurs pour des v�hicules �lectriques en vue du lancement d'une telle gamme par Renault

This problem corresponds to refueling locomotives at different station yards during the course of its journey. Locomotive tanks have a fixed fuel capacity and prices of fuel vary across yards. In addition, there is a fixed cost for hiring a refueling truck at a yard and every refueling stop that the locomotive makes. Locomotives can power different train sets during a cyclical planning horizon running 14 days. The objective of this exercise is to minimize the total fuel costs � fixed and operational � for a given set of locomotives, trains and yards. In addition, there are numerous constraints relating to refueling, locomotive tank capacity, refueling truck capacity etc. This problem has similarity to the network flow problem. We formulate this problem as a Mixed Integer Program (MIP) and present our experience in this project.

Equity effects of congestion charges and intra-individual variation in preferences. A joint research initiative between: Royal Institute of Technology (KTH), Sweden (lead), The Swiss Federal Institute of Technology, Z�rich, Switzerland and Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland

The goal of this project is to address the modelling and computational issues of integrating modern mobility simulations with the latest micro-simulation land use models. The project intends to advance the state-of-the-art in the field of the micro-simulation of prospective integrated models of Land-Use and Transport (LUTI). On the modelling side, the main challenges are to integrate a demographic evolution module, to add an environmental module, to improve the overall consistency and, last but not least, to deal with the multi-scale aspects of the problem: several time horizons and spatial resolutions are involved.

Des axes forts de transport public urbain sont � l'�tude dans l'agglom�ration de Lausanne-Morges. Ce projet vise � fournir, � partir du logiciel Emme, des crit�res d'�valuation des diverses variantes de desserte de la partie nord de Lausanne

We develop new strategies to tackle large scale problems and their optimization. We focus in particular applications arising in the optimization of container terminal operations.

Examens des comportements de transport des usagers des Hautes Ecoles sur la base d'enq�tes de mobilit� r�guli�res.

The main objective of this Action is to develop, implement and promote methodologies and procedures to support the use of traffic simulations, especially on the topics of calibration and validation. To this aim, the sharing and exchanging of available traffic datasets will also be a key task of the Action.

The CATS project aims to develop a new urban transport service based on a new generation vehicle. Its major innovation is the utilisation of a single type of vehicle for two different usages: individual use or collective transport. This new transport service is aimed at filling the gap between public mass transport and private individual vehicles. It is based on two operating principles: the self service concept where small and clean urban vehicles are offered on a short term rental basis, and the flexible shuttle service where a variable length of vehicles convoy, driven by a professional driver, operates at fixed hours along a line on a permanent basis or on a case by case basis. Four Cristal vehicles and two stations will be made available by Lohr Industrie to the project for experiments. The CATS project will investigate through an in depth mobility needs analysis, on-site demonstration and showcases, the environmental impact and social acceptance of the introduction of such a new system in three different European cities (Strasbourg FR, Ploeisti, RO, Formello, IT). CATS will complement the design and manufacture of the Cristal vehicle via a detailed definition of its operating principles and by a design of its urban settings (stations, infrastructures,) in accordance with cities and citizens needs.

Swiss Post and PostBus have launched a research project to optimize mobility in cooperation with the Federal Institute of Technology in Lausanne (EPFL), represented by EPFL Transportation Center, under Professor Michel Bierlaire. This will show the market potential for combined mobility. Among other things it will look at the factors that influence travellers in their choice of transport. At a later stage, target group-specific new transport offerings and services will be developed and tested, which will have a lasting influence on this choice. The three years research project is conducted by Professors Vincent Kaufmann (LASUR) and Michel Bierlaire (TRANSP-OR).

The projects aims at investigating how to perform an appropriate fusion of data from smartphones in order to predict the mobility behavior of a given individual.

Simulation-based optimization of the operations of Vale's railroad yards.

NEARCTIS (Network of Excellence: Advanced Road Cooperative Traffic management in the Information Society) is an academic network involving teams working on the field of traffic management and optimization, with a particular focus on cooperative systems. The main objective of the project is to constitute what could be considered as a virtual research institute.

Design of algorithms to extract invariant features from images captured by omnidirectional cameras.

Development of a prototype integrated transportation land-use model for the region of Lausanne.

Design an optimization framework combining macroscopic and microscopic models, with applications in hospital management and urban road traffic.

Robust planning and recovery from disruptions for airlines operations

Modelling the global appraisal process of experts in the context of scene analysis.

Apr�s avoir retenu certaines variantes d'axes forts de transport en commun dans l'agglom�ration Lausanne-Morges lors d'une �tude pr�c�dente, il s'agissait de choisir une variante pr�rentielle et un axe fort prioritaire. L'�tude a �t� men�e en s'aidant du logiciel EMME.

Etudes TL diverses : comparaison entre 2 variantes de futur r�seau, tapis roulant Gare-Flon, prolongation de lignes vers le Mont-sur-Lausanne. en fournissant des indicateurs de qualit� gr�ce � une mod�lisation Emme

L�Observatoire de la Mobilit� r�alise r�guli�rement des enqu�tes sur les d�placements des �tudiants et collaborateurs en direction des Hautes Ecoles. Actuellement ces personnes entrent l�origine de leur d�placement en donnant le num�ro postal, la localit� et le cas �ch�ant une indication suppl�mentaire (quartier). Ce projet a creus� la possibilit� de donner l�origine en pointant sur une carte, compte tenu � la fois des aspects techniques et de facilit� d�usage par les utilisateurs.

Evaluation � l'aide du logiciel Emme de divers projets d'action sur les transports � l'int�rieur de l'agglom�ration Lausanne-Morges : nouvelles jonctions autorouti�res, nouvelles routes d'�vitement, restrictions de vitesse, nouvelles lignes de transport en commun, renforcement du r�seau ferroviaire.

A l'aide du programme Emme, tester l'opportunit� d'implanter certains axes forts de transport en commun dans l'agglom�ration Lausanne-Morges

Design and development of models and algorithms for the optimization of operations in seaport container terminals.

Previsions of OD matrices and modal split for 2020 in the Lausanne region

To understand consumer behavior in his or her path to purchase.

Development of a software product dedicated to airlines and providing solutions to recover from schedule disruptions with minimum cost.

Optimization of the location of distribution centres for Postlogistics, Switzerland

Design an optimization framework for the operation suites in hospitals, using simulation tools

Development of route choice models from RP and SP data

Design new discrete choice models capturing route choice behavior

Develop appropriate case studies for teaching optimization to mechanical engineers

Develop forecasting models for sales of various products, such as printers

Development of optimization algorithms designed for the maximum likelihood estimation of advanced discrete choice models where the objective function is singular, and non-trivial constraints are imposed on the parameters

Develop a prototype of a decision-aiding system for the bus scheduling problem

Develop a simulation tool to assess dynamic pricing and yield management strategies in ski resorts

Use of GPS-based data to address three fundamental behavioural questions: (i) size, structure and orientation of the individual activity spaces, (ii) frequency and amplitude of the rythms of visits to different locations, including their competition and (iii) form of the rules of route choice behaviour

We investigate methodological developments designed to handle discrete choice models with a large number of alternatives

Development of operational disaggregate demand models for efficient dynamic traffic managment systems

Develop a model-based detection system where the scene analysis is supported by a crowd simulator

We develop models of pedestrian movements based on discrete choice analysis.

Development of disaggregate behavior model for scene analysis in the context of video surveillance

Design and implement a model to simulate the operations of the surgery block in the Geneva Hospital

Design of a new class of derivative-free algorithms exploiting some derivative information, customized for the image registration problem

Development of new algorithms to solve the route guidance generation problem, based on several formulations of the problem, combining a fixed-point approach with an optimization approach

Development and adaptations of efficient optimisation algorithms dedicated to brain images registration

Implementation and evaluation of a real-time traffic prediciton model for the Western Switzerland highway network

Evaluation of a traffic control system in Lausanne, using MITSIM laboratory, a state-of-the-art simulation tool developed by the Intelligent Transportation Systems Program, MIT

Develop a new research track in large-scale derivative-free optimization

Collaborate with MIT for the development and evaluation of DynaMIT, a Dynamic Traffic Assignment System (DTA) that supports real-time applications such as synamic route guidance and adaptative traffic control