Antonin Danalet

Appel à contribution pour Environnement Urbain

Voici un appel à contribution pour un numéro spécial sur la marche codirigé par Emmanuel Ravalet :

Environnement Urbain / Urban Environment, Numéro thématique 2015

Marche, environnements urbains et santé. Perspectives internationales et interdisciplinaires.

L'appel à articles en PDF

Posted by Antonin Danalet at 17:27
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Les comportements piétons dans les pôles d'échange intermodaux : Une collaboration avec les CFF

Je viens de donner une présentation à l'Association québécoise du transport intermunicipal et municipal (AQTIM) dans le cadre d'une visite du Centre de transport (TraCE) de l'EPFL. Mon intervention a porté sur les projets relatifs à la gare de Lausanne pour les CFF réalisés par le laboratoire Transport et Mobilité (TRANSP-OR).

Les comportements piétons dans les pôles d'échange intermodaux : Une collaboration avec les CFF
Antonin Danalet, Marija Nikolic, Flurin Hänseler et Michel Bierlaire

Projets relatifs à la gare de Lausanne pour les CFF réalisés par le laboratoire Transport et Mobilité

Lire les slides

Posted by Antonin Danalet at 15:33
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Student project: Data fusion in purchasing behavior

We propose a student project for next semester with Matteo Sorci (nViso), most likely for an IC student:

Data fusion in purchasing behavior

This project aims at fusing data from WiFi traces and from cameras detecting facial expressions in a purchase context. The student will have to understand the different data outputs from the two techniques, manage the data, provide joint analysis of the results and input results in a given format. Programming skills are required. Curiosity and opening mind on the problem are welcome.

Posted by Antonin Danalet at 13:41
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Choice set generation for activities using importance sampling

I will give a talk next week in the Workshop on Discrete Choice models 2014. Here is the abstract:

Choice set generation for activities using importance sampling

In spatiotemporal choices, such as destination choice, the number of alternatives is very large. Our model decomposes the choice of destinations in time into a first model of choice of activity type in time, aggregating destinations into activity types, and into a second model of choice of destinations, conditional on the activity type and time of day. This decomposition is motivated both behaviorally (people tend to choose first the "pattern" of their day, and then only the specific destination) and computationally (in order to manage the large cardinality of the choice set).

The choice set for the first model is still very large: the sequence of activity types in time is combinatorial. Traditional approaches usually propose an ad-hoc and deterministic list of assumptions on the size, composition and variability of the choice set (modeling the consideration set). We propose to consider the universal choice set, containing all possible sequences of activities in time, and to sample sequences of activity types in time according to a given distribution. By performing importance sampling, the goal is to avoid misspecification of choice sets in choice models. We assume that the bias of including unconsidered alternatives is smaller than the bias of forgetting important alternatives for the decision maker. The unconsidered alternatives just have a very low choice probability, while forgetting an important alternative generates endogeneity.

The importance sampling is performed by representing each sequence as a path in a network and by using a Metropolis-Hastings sampling of paths algorithm.

The full program is here.

More details about this model can be found in:

Danalet, A., and Bierlaire, M. (2014). A path choice approach to activity modeling with a pedestrian case study. Proceedings of the 14th Swiss Transport Research Conference (STRC) May 14-16, 2014. On STRC website / TRANSP-OR website

Posted by Antonin Danalet at 15:56
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A path choice approach to activity modeling with a pedestrian case study

The 14th Swiss Transport Research Conference (STRC) took place from May 14 to May 16, 2014 in Monte Verità, in Ascona, Switzerland. Our paper in the conference proceedings is now available online:

A path choice approach to activity modeling with a pedestrian case study
Antonin Danalet, Michel Bierlaire

In Switzerland, the largest railway stations are called "RailCities" by the Swiss Railways. It emphasizes their transformation into places to perform different activities, similar to a small-scale city. Concerns are similar than in urban areas: costs of new infrastructure, traffic congestion, land scarcity.

The activity-based approach models the activity participation patterns. Traveling is seen as a derived demand from the need to pursue activities. In the pedestrian context, postulate rules, such as the home-based structure with tours from home, do not hold. The large dimensionality of the problem implies aggregation or hierarchy of dimensions, with priorities of activity types.

We develop a modeling framework based on path choice. The activity-episode sequence is seen as a path in an activity network. The sequence is not home-based nor tour-based. The model can be applied in different contexts, both urban and pedestrian. The large dimensionality is managed through an importance sampling based on Metropolis-Hastings algorithm for the generation of the choice set. The time is discretized. The utility of an activity-episode sequence is the sum of individual trips and activities, including the time-of-day preferences and the satiation effects.

First results of a case study on campus are presented, based on data from WiFi traces.

Read the report on STRC website / on TRANSP-OR website

The corresponding presentation has been published in a previous article.

Posted by Antonin Danalet at 11:13
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Activity pattern modeling: A path choice approach

I've just given a talk in the 14th Swiss Transport Research Conference (STRC) in Monte Verità, in Ascona.

Activity pattern modeling: A path choice approach

In Switzerland, the largest railway stations are called "RailCities" by the Swiss Railways. It emphasizes their transformation into place to live and perform several different activities, similar to a small-scale city. Similar concerns than in urban areas are increasing: escalating costs of new infrastructure, increasing concerns regarding traffic congestion, scarcity of land use. Pedestrian demand management strategies would allow to modify individual travel behavior.

The activity-based approach models the interactions shaping the activity participation patterns. Traveling is seen as a derived demand from the need to pursue activities. Several models have been proposed. Activity scheduling model in an entire-day framework is a mix of rule-based algorithm, duration models and discrete choice structures. The biggest drawback of most of these models is the postulated rules: they are structured on home and tours from home, with models applied sequentially according to priorities of activity types. Very often, the large dimensionality of the problem (activity types, continuous time, number of episodes in the day) implies aggregation (broad periods of time, mandatory vs non mandatory, primary vs secondary) or hierarchy of dimensions.

We are developing a modeling framework based on path choice. The activity-episode sequence is seen as a path in an activity network. The sequence is not home-based nor tour-based, so that the model can be applied in different contexts, both urban and pedestrian. The large dimensionality is managed through an importance sampling based on Metropolis-Hastings algorithm for the generation of the choice set. The time is discretized in regular intervals. The utility of an activity-episode sequence is the sum of individual trips and activities, including the time-of-day preferences and the satiation effects.

First estimation results are presented based on data from WiFi traces.

Look at the slides

Posted by Antonin Danalet at 12:35
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A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures

Our paper "A Bayesian Approach to Detect Pedestrian Destination-Sequences from WiFi Signatures" by myself, Bilal Farooq and Michel Bierlaire, in Transportation Research Part C: Emerging Technologies, is online:

A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures

In this paper, we propose a methodology to use the communication network infrastructure, in particular WiFi traces, to detect the sequence of activity episodes visited by pedestrians. Due to the poor quality of WiFi localization, a probabilistic method is proposed that infers activity-episode locations based on WiFi traces and calculates the likelihood of observing these traces in the pedestrian network, taking into account prior knowledge. The output of the method consists of candidates of activity-episodes sequences associated with the likelihood to be the true one. The methodology is validated on traces generated by a known sequence of activities, while the performance being evaluated on a set of anonymous users. Results show that it is possible to predict the number of episodes and the activity-episodes locations and durations, by merging information about the activity locations on the map, WiFi measurements and prior information about schedules and the attractivity in pedestrian infrastructure. The ambiguity of each activity episode in the sequence is explicitly measured.

Read the paper

Its DOI is 10.1016/j.trc.2014.03.015.

Posted by Antonin Danalet at 14:19
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EMaHP in South Africa

EPFL Mathematical Humanitarian Project (EMaHP) is a project by math students, partially supported by EPFL Alumni. It was already mentioned in EPFL Alumni magazine, in a video before their departure and on EPFL homepage with an article a video. They visited South Africa for an educational humanitarian project. They have just released the full movie of their trip:

Posted by Antonin Danalet at 21:46
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Workshop on pedestrian models 2014

The slides I presented during the Workshop on pedestrian models are available on TRANSP-OR webpage:

WiFi-Based Marauder's Map, or where are members of a campus and why?

Similarly to the Marauder's Map in Harry Potter, we tracked employees and students on campus. We model this output in terms of choice of activity type in time. By discretizing time, this choice is represented as a path in a network. The choice set is generated using a Metropolis-Hasting algorithm based on attractivity measures, and the utility function describes satiation effects and time-of-day preferences. Such a methodology is useful to build an activity-based model for pedestrian infrastructure, estimate the demand and its drivers, and forecast it for different scenarios.

The presentation [PDF]

Moreover, all presentations by the participants are available on the webpage of the workshop.

Posted by Antonin Danalet at 15:16
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Pedestrian and Evacuation Dynamics 2012

The proceedings of the 6th International Conference on Pedestrian and Evacuation Dynamics conference (PED2012) are now available. The conference took place in Zurich in June 2012. The book is available on Springer website (print ISBN: 978-3-319-02446-2, online ISBN: 978-3-319-02447-9).

In particular, we published a paper in this book (DOI: 10.1007/978-3-319-02447-9_111):

Estimating Pedestrian Destinations Using Traces from WiFi Infrastructures

Antonin Danalet, Michel Bierlaire, Bilal Farooq

Gathering data about pedestrian origin, destination and route is difficult, particularly indoor and on a large scale. These data are important for route choice modeling, description of congestion, and flow estimation. Most data collection techniques are device-centric. In this paper, we focus on the communication network infrastructure and propose to use WiFi traces to generate pedestrian destinations. Due to the poor quality of WiFi localization, a probabilistic method is proposed that infers visited destinations based on WiFi traces and calculates the likelihood of observing these traces in the pedestrian network, taking into account prior knowledge. The output of the method consists in generating several candidate lists of destinations, and assigning the probability of each list being the true one. Results show that it is possible to predict the number of destinations, the time spent at it and the localization of it, discriminating intermediary signals from signals generated at destination.

Read the article

Posted by Antonin Danalet at 11:09
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