Publications by Michel Bierlaire

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Smartphones collect a wealth of information about their users' environment and activities. This includes GPS (global positioning system) tracks and the MAC (media access control) addresses of devices around the user, and it can go as far as taking visual and acoustic samples of the user's environment. We present a Bayesian framework for the identification of the current activity type of a smartphone user. As the prior information, we use a random utility model that predicts the type of activity a user is li

The SARS-CoV-2 outburst in March 2020 has led to the lockdown of several countries across the world. Mobility restrictions have been constantly put into action and reversed to find the trade-off between minimizing the number of infections and death and mitigating the inevitable damage to the economy and the societal systems. These emergency measures lead to collateral effects that prove the need for robust and dynamic models for policymakers to make efficient and targeted decisions in short amounts of time.

We consider the school bus routing and scheduling problem, where transportation demand is known and bus scheduling can be planned in advance. We present a comprehensive methodology designed to support the decision of practitioners. We first propose a modeling framework where the focus is on optimizing the level of service for a given number of buses. Then, we describe an automatic procedure generating a solution to the problem. It first builds a feasible solution, which is subsequently improved using a heur

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

We introduce a unified modeling and solution framework for various classes of rich vehicle and inventory routing problems as well as other probability-based routing problems with a time-horizon dimension. Demand is assumed to be stochastic and non-stationary, and is forecast using any forecasting model that provides expected demands over the planning horizon, with error terms from any empirical distribution. We discuss possible applications to various problems from the literature and practice: from health c

Departure time choice modeling has been part of main stream travel behavior research for more than three decades. Congestion management schemes are based on the assumption that travelers optimize their departure time choice. Ever since Vickrey, in the late 1960's and later updated by Small in the 1970's, the concept of schedule-delays (early and late) has been the focus of most modeling endeavors. The main idea is that travelers organize their departure time based on a preferred arrival time (PAT). The main

Non-parametric probabilistic classification models are increasingly being investigated as an alternative to Discrete Choice Models (DCMs), e.g. for predicting mode choice. There exist many strategies within the literature for model selection between DCMs, either through the testing of a null hypothesis, e.g. likelihood ratio, Wald, Lagrange Multiplier tests, or through the comparison of information criteria, e.g. Bayesian and Aikaike information criteria. However, these tests are only valid for parametric m

When using random utility models for a route choice problem, a critical issue is the significant correlation among alternatives. There are basically two types of models proposed in the literature to address it: (i) a deterministic correction of the path ut ...

Electric mobility is now a reality, and services based on electric vehicles, such as electric car-sharing and electric buses, are becoming part of urban mobility. These new modes bring new challenges for the design and operations of the systems that require specific decision support tools for the evaluation of the service performance. In order to pave the way toward integrated electrified urban mobility, we need operational tools that enable the technology to be successfully implemented in practice. In thi

We propose a new modelling approach for daily activity scheduling which integrates the different daily scheduling choice dimensions (activity participation, location, schedule, duration and transportation mode) into a single optimisation problem. The funda ...

Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraints (maybe nonlinear) on the parameters in order to obtain meaningful values or to overcome model overspecification which can lead to singularity in the objective function. These difficulties especially arise when estimating advanced discrete choice models.

We propose a framework to find optimal price-based policies to regulate markets characterized by oligopolistic competition and in which consumers make a discrete choice among a finite set of alternatives. The framework accommodates general discrete choice ...

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

Moving walkways (MW) have been imagined as a possible means of transport since the late 19th century, and this system has fascinated urban planners and engineers ever since. Contrary to what has been imagined, moving walkways are only used in transportation hub corridors, and not as a main transport mode in city centers. Today however, MWs are receiving increasing attention as a possible solution to congestion and pollution, as well as a catalyst for soft mobility. This paper explores the role of moving wal

A navigation process is to start from a known (initial) position and to ensure a continued localisation of the user during the movement. Consider a pedestrian navigation system which contains a GPS receiver and a set of inertial sensors connected with the map database. The problem to solve is to determine the users location using the map database and measurements of the inertial sensors. Indoors the position of each step is determined as a function of the previous position and inertial measurements. Thus th

Various countries and communities are defining strategic energy plans driven by concerns for climate change and security of energy supply. Energy models can support this decision-making process. The long-term planning horizon requires uncertainty to be acc ...

Route guidance refers to information provided to travelers in an attempt to facilitate their decisions relative to departure time, travel mode and route. We are specifically interested in consistent anticipatory route guidance, in which real-time traffic measurements are used to make short-term predictions, involving complex simulation tools, of future traffic conditions. These predictions are the basis of the guidance information that is provided to users. By consistent, we mean that the anticipated traffi

Choice-based optimization problems are the family of optimization problems that incorporate the stochasticity of individual preferences according to discrete choice models to make planning decisions. This integration brings non-convexity and nonlinearity t ...

Lausanne-Morges agglomeration will experiment strong increases in the number of inhabitants and jobs until 2020. The additional trips generated by these increases will have to be carried out in a larger proportion by soft mobility and transit. There are many projects aiming at facilitating this orientation, in particular projects of important transit lines. As these projects are very expensive, it is important to evaluate their impact before making a choice. This must not be delayed, in order to get Federal

Michel Bierlaire

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Inferring the activities of smartphone users from context measurements using Bayesian inference and random utility models

Activity-based modeling and simulation of epidemics

Decision-aid Methodology for the school Bus Routing and Scheduling Problem

Robust discrete choice models with t-distributed kernel errors

A general framework for routing problems with stochastic demands

A behavioral departure time choice model with latent arrival time preference and rewards for peak-hour avoidance

Validation of probabilistic classifiers

Capturing correlation with subnetworks in route choice models

Electrification of urban mobility: the case of catenary-free buses

Capturing trade-offs between daily scheduling choices

Solving issues in the estimation of econometric models

Solving singularity issues in the estimation of econometric models

Price-based regulation of oligopolistic markets under discrete choice models of demand

Integrating advanced discrete choice models in mixed integer linear optimization

An exploration of moving walkways as a transport system in urban centers

Map-matching for pedestrians via Bayesian inference

Characterization of input uncertainties in strategic energy planning models

Solving the anticipatory route guidance generation problem using a generalization of secant methods

A Lagrangian decomposition scheme for choice-based optimization

Tools to evaluate future actions on the traffic in Lausanne