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1. Smartphone-based Ecological Momentary Intervention for secondary prevention of suicidal thoughts and behaviour: protocol for the SmartCrisis V.2.0 randomised clinical trial

Author

Maria Luisa Barrigon, Antonio Artes, Mercedes Perez-Rodriguez, Philippe Courtet, Enrique Baca-Garcia, Sofian Berrouiguet, Jorge Lopez-Castroman, Alejandro Porras-Segovia, María-Mercedes Pérez-Rodríguez, Antonio Artes-Rodríguez, Romain Billot, Juan José Carballo-Belloso, David Delgado-Gomez, Marta Migoya-Borja, Nora Palomar-Ciria, Alba Sedano-Capdevila, Sofía Abascal-Peiró, Susana Amodeo-Escriban, Ana de Granda, Rodrigo Carmona, Elena Gil-Benito, Laura Mata-Iturralde, Laura Muñoz-Lorenzo, Rocío Navarro-Jiménez, Santiago Ovejero, Sergio Sánchez-Alonso, Ezequiel Di Stasio, José Luis Palomo, Pedro Martín-Calvo, Ana José Ortega, Marta Segura-Valverde, María Luisa Martin-Calvo, Raquel Álvarez-García, Pablo Portillo-de Antonio, Pablo Puras-Rico, and Eva María Romero-Gómez

Subjects
Medicine
Abstract

Introduction Suicide is one of the leading public health issues worldwide. Mobile health can help us to combat suicide through monitoring and treatment. The SmartCrisis V.2.0 randomised clinical trial aims to evaluate the effectiveness of a smartphone-based Ecological Momentary Intervention to prevent suicidal thoughts and behaviour.Methods and analysis The SmartCrisis V.2.0 study is a randomised clinical trial with two parallel groups, conducted among patients with a history of suicidal behaviour treated at five sites in France and Spain. The intervention group will be monitored using Ecological Momentary Assessment (EMA) and will receive an Ecological Momentary Intervention called ‘SmartSafe’ in addition to their treatment as usual (TAU). TAU will consist of mental health follow-up of the patient (scheduled appointments with a psychiatrist) in an outpatient Suicide Prevention programme, with predetermined clinical appointments according to the Brief Intervention Contact recommendations (1, 2, 4, 7 and 11 weeks and 4, 6, 9 and 12 months). The control group would receive TAU and be monitored using EMA.Ethics and dissemination This study has been approved by the Ethics Committee of the University Hospital Fundación Jiménez Díaz. It is expected that, in the near future, our mobile health intervention and monitoring system can be implemented in routine clinical practice. Results will be disseminated through peer-reviewed journals and psychiatric congresses. Reference number EC005-21_FJD. Participants gave informed consent to participate in the study before taking part.Trial registration number NCT04775160.

Published
2022
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2. Exact Zoning Optimization Model for Marine Spatial Planning (MSP)

Author

Mohadese Basirati, Romain Billot, Patrick Meyer, and Erwan Bocher

Subjects
marine spatial planning, multi-objective integer linear optimization, buffering, interest, compactness, raster data, Science, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract

Marine spatial planning (MSP) has recently attracted more attention as an efficient decision support tool. MSP is a strategic and long-term process gathering multiple competing users of the ocean with the objective to simplify decisions regarding the sustainable use of marine resources. One of the challenges in MSP is to determine an optimal zone to locate a new activity while taking into account the locations of the other existing activities. Most approaches to spatial zoning are formulated as non-linear optimization models involving multiple objectives, which are usually solved using stochastic search algorithms, leading to sub-optimal solutions. In this paper, we propose to model the problem as a Multi-Objective Integer Linear Program. The model is developed for raster data and it aims at maximizing the interest of the area of the zone dedicated to the new activity while maximizing its spatial compactness. We study two resolution methods: first, a weighted-sum of the two objectives, and second, an interactive approach based on an improved augmented version of the ϵ-constraint method, AUGMECON2. To validate and study the model, we perform experiments on artificially generated data. Our experimental study shows that AUGMECON2 represents the most promising approach in terms of relevance and diversity of the solutions, compactness, and computation time.

Published
2021
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3. A Review of Data Cleaning Approaches in a Hydrographic Framework with a Focus on Bathymetric Multibeam Echosounder Datasets

Author

Julian Le Deunf, Nathalie Debese, Thierry Schmitt, and Romain Billot

Subjects
data cleaning algorithms, hydrographic surveying, MBES bathymetric datasets, outlier detection, taxonomy, Geology, QE1-996.5
Abstract

Automatic cleaning of MultiBeam EchoSounder (MBES) bathymetric datasets is a critical issue in data processing especially with the objective of nautical charting. A number of approaches have already been investigated in order to provide solution in views of operationally reaching this still challenging problem. This paper aims at providing a comprehensive and structured overview of existing contributions in the literature. For this purpose, a taxonomy is proposed to categorize the whole set of automatic and semi-automatic methods addressing MBES data cleaning. The non-supervised algorithms that compose the majority of the methods developed in the hydrographic field, are mainly described according to both the features of the bathymetric data and the type of outliers to detect. Based on this detailed review, past and future developments are discussed in light of both implementation and test on datasets and metrics used for performances assessment.

Published
2020
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4. Developing a Novel Exact Model of Zoning Optimization for Marine Spatial Planning

Author

Mohadese Basirati, Patrick Meyer, Romain Billot, Erwan Bocher, Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Equipe DECIDE (Lab-STICC_DECIDE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Centre National de la Recherche Scientifique (CNRS), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)

Subjects
Optimization, Decision Support Systems, [INFO]Computer Science [cs], Linear Programming
Abstract

International audience; Marine spatial planning (MSP) as an efficient planning tool simplifies decisions on the sustainable use of marine resources. Determining an optimal zone for one marine user, considering the other users' activities, represents one challenge in MSP. We propose modeling the problem as an Exact Multi-Objective Integer Linear Program. We developed the raster data model to maximize the interest of the zone dedicated to a single actor and to maximize its spatial compactness. We are studying two approaches for resolution: first, a weighted sum, and second, an improved augmented version of the ε-constraint method, AUGMECON2. We validate the model by performing experiments on artificially generated data.

Published
2021

5. Seabed prediction from airborne topo-bathymetric lidar point cloud using machine learning approaches

Author

Julian Le Deunf, Rudresh Mishra, Yves Pastol, Romain Billot, Steve Oudot, Service Hydrographique et Océanographique de la Marine (SHOM), Ministère de la Défense, Equipe DECIDE (Lab-STICC_DECIDE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Understanding the Shape of Data (DATASHAPE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
supervised machine learning methods, topo-bathymetric lidar data, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [SDE]Environmental Sciences, [INFO]Computer Science [cs], data processing, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography
Abstract

International audience; Predicting the seabed from unfiltered bathymetric lidar data is a very complex task and a critical issue in bathymetric data processing especially with the objective of nautical charting. This is challenging to ensure a high level of quality and security for the needs of a national hydrographic office. This paper proposes a methodology to predict the seabed based on machine learning, which could be useful to automate outlier detection and control the topo-bathymetric lidar point cloud datasets. Several predictive methods have been investigated to predict the seabed from our 2D + 1D data structure. A characteristic dataset of Corsica region was used as a case study for this predictive workflow.

Published
2021

6. Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Author

Romain Billot, Philippe Lenca, Michel Walter, Jordan E. DeVylder, Yannis Haralambous, Taylor C. Ryan, Deok-Hee Kim-Dufor, Jonathan Marsh, Sofian Berrouiguet, Christophe Lemey, Aziliz Le Glaz, Lenca, Philippe, Hopital de Bohars - CHRU Brest (CHU - BREST ), Département Informatique (IMT Atlantique - INFO), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Equipe DECIDE (Lab-STICC_DECIDE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Fordham University Graduate School of Social Service, Soins Primaires, Santé Publique, Registre des cancers de Bretagne Occidentale (SPURBO), Université de Brest (UBO)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Laboratoire de Traitement de l'Information Medicale (LaTIM), Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Brestois Santé Agro Matière (IBSAM), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), and Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)

Subjects
[INFO.INFO-RO] Computer Science [cs]/Operations Research [cs.RO], Computer science, [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, PsycINFO, Review, computer.software_genre, Field (computer science), [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Unique identifier, MESH: Santé mentale, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 030212 general & internal medicine, Data Management, education.field_of_study, Medical record, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], artificial intelligence, psychiatry, 3. Good health, Systematic review, machine learning, MESH: Intelligence artificielle, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Public aspects of medicine, RA1-1270, Natural language processing, mental health, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], MESH: Traitement du langage naturel, Population, Computer applications to medicine. Medical informatics, R858-859.7, Health Informatics, MESH: Apprentissage machine, Machine learning, 03 medical and health sciences, Humans, Social media, natural language processing, education, [SDV.IB] Life Sciences [q-bio]/Bioengineering, business.industry, MESH: Data Mining, data mining, Mental health, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], MESH: Service hospitalier de psychiatrie, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Artificial intelligence, business, computer, 030217 neurology & neurosurgery
Abstract

Background Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides good performance in statistical tasks, such as text classification or sentiment mining. Objective The primary aim of this systematic review was to summarize and characterize, in methodological and technical terms, studies that used machine learning and NLP techniques for mental health. The secondary aim was to consider the potential use of these methods in mental health clinical practice Methods This systematic review follows the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) guidelines and is registered with PROSPERO (Prospective Register of Systematic Reviews; number CRD42019107376). The search was conducted using 4 medical databases (PubMed, Scopus, ScienceDirect, and PsycINFO) with the following keywords: machine learning, data mining, psychiatry, mental health, and mental disorder. The exclusion criteria were as follows: languages other than English, anonymization process, case studies, conference papers, and reviews. No limitations on publication dates were imposed. Results A total of 327 articles were identified, of which 269 (82.3%) were excluded and 58 (17.7%) were included in the review. The results were organized through a qualitative perspective. Although studies had heterogeneous topics and methods, some themes emerged. Population studies could be grouped into 3 categories: patients included in medical databases, patients who came to the emergency room, and social media users. The main objectives were to extract symptoms, classify severity of illness, compare therapy effectiveness, provide psychopathological clues, and challenge the current nosography. Medical records and social media were the 2 major data sources. With regard to the methods used, preprocessing used the standard methods of NLP and unique identifier extraction dedicated to medical texts. Efficient classifiers were preferred rather than transparent functioning classifiers. Python was the most frequently used platform. Conclusions Machine learning and NLP models have been highly topical issues in medicine in recent years and may be considered a new paradigm in medical research. However, these processes tend to confirm clinical hypotheses rather than developing entirely new information, and only one major category of the population (ie, social media users) is an imprecise cohort. Moreover, some language-specific features can improve the performance of NLP methods, and their extension to other languages should be more closely investigated. However, machine learning and NLP techniques provide useful information from unexplored data (ie, patients’ daily habits that are usually inaccessible to care providers). Before considering It as an additional tool of mental health care, ethical issues remain and should be discussed in a timely manner. Machine learning and NLP methods may offer multiple perspectives in mental health research but should also be considered as tools to support clinical practice.

Published
2021

7. Crowdfunding platform and inter-project social network: example of Ulule

Author

Inna Lyubareva, Laurent Brisson, Cécile Bothorel, Romain Billot, Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Economie et de Gestion de l'Ouest (LEGO), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Université de Brest (UBO)-Université de Brest (UBO)-Université de Bretagne Sud (UBS)-Université Bretagne Loire (UBL), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)

Subjects
[QFIN]Quantitative Finance [q-fin], [SHS.INFO]Humanities and Social Sciences/Library and information sciences, [INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]
Abstract

International audience

Published
2019

8. An Approach for Data Mining of Electronic Health Record Data for Suicide Risk Management: Database Analysis for Clinical Decision Support

Author

Michel Walter, Romain Billot, Philippe Lenca, Philippe Courtet, Enrique Baca-García, Jorge Lopez-Castroman, Mark E. Larsen, Isabelle Jaussent, Sofian Berrouiguet, Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), CHRU Brest - Psychiatrie Adulte (CHU - Brest- Psychiatrie), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Black Dog Institute [Sydney, Australia], University of New South Wales [Sydney] (UNSW), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Montpellier (UM), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Department of Psychiatry (Hospital Universitario Fundacion Jimenez Diaz ), This study was funded partially by Instituto de Salud Carlos III (ISCIII PI13/02200, PI16/01852), Delegación del Gobierno para el Plan Nacional de Drogas (20151073), and the American Foundation for Suicide Prevention (LSRG-1-005-16)., UAM. Departamento de Psiquiatría, École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), IMT Atlantique (IMT Atlantique), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), and Lenca, Philippe

Subjects
Computer science, [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Clinical decision support system, [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], computer.software_genre, Suicide prevention, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 0302 clinical medicine, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, prevention, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Electronic health, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], [INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing, 3. Good health, [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], Suicide, Psychiatry and Mental health, clinical decision support system, Data mining, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Medicina, Automatic identification and data capture, MEDLINE, Sample (statistics), Context (language use), [INFO] Computer Science [cs], [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing, 03 medical and health sciences, [INFO.INFO-MC]Computer Science [cs]/Mobile Computing, [INFO]Computer Science [cs], suicide attempts, Cluster analysis, suicide, Original Paper, mobile phone, Prevention, data mining, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], 030227 psychiatry, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Mobile phone, Dynamic decision-making, computer, Suicide attempts, 030217 neurology & neurosurgery, electronic health
Abstract

Background: In an electronic health context, combining traditional structured clinical assessment methods and routine electronic health-based data capture may be a reliable method to build a dynamic clinical decision-support system (CDSS) for suicide prevention. Objective: The aim of this study was to describe the data mining module of a Web-based CDSS and to identify suicide repetition risk in a sample of suicide attempters. Methods: We analyzed a database of 2802 suicide attempters. Clustering methods were used to identify groups of similar patients, and regression trees were applied to estimate the number of suicide attempts among these patients. Results: We identified 3 groups of patients using clustering methods. In addition, relevant risk factors explaining the number of suicide attempts were highlighted by regression trees. Conclusions: Data mining techniques can help to identify different groups of patients at risk of suicide reattempt. The findings of this study can be combined with Web-based and smartphone-based data to improve dynamic decision making for clinicians., This study received a Hospital Clinical Research Grant (PHRC 2009) from the French Health Ministry. None of the funding sources had any involvement in the study design; collection, analysis, or interpretation of data; writing of the report; or the decision to submit the paper for publication. This study was funded partially by Instituto de Salud Carlos III (ISCIII PI13/02200; PI16/01852), Delegación del Gobierno para el Plan Nacional de Drogas (20151073), and the American Foundation for Suicide Prevention (LSRG-1-005-16).

Published
2019

9. A comment on 'what makes a VRP solution good? The generation of problem-specific knowledge for heuristics'

Author

Marc Sevaux, Flavien Lucas, Romain Billot, Lab-STICC_UBS_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Lab-STICC_TB_CID_DECIDE, École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), and Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Optimization, 0209 industrial biotechnology, General Computer Science, Computer science, media_common.quotation_subject, 0211 other engineering and technologies, Principal component analysis, 02 engineering and technology, Management Science and Operations Research, Specific knowledge, Machine learning, computer.software_genre, 020901 industrial engineering & automation, Vehicle routing problem, Quality (business), Data mining, ComputingMilieux_MISCELLANEOUS, media_common, Complement (set theory), 021103 operations research, business.industry, [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO], Vehicle routing, Random forest, Modeling and Simulation, Artificial intelligence, Heuristics, business, computer
Abstract

International audience; We propose a comment about the article “What makes a VRP solution good? The generation of problem-specific knowledge for heuristics” (Arnold and Sörensen, 2019) by Florian Arnold and Kenneth Sörensen. In the original contribution, the authors implemented several Machine Learning (ML) algorithms in order to predict good vs. not good solutions. Then, some outcomes of the algorithms were discussed in terms of the predictive power of the solutions features. The purpose was then to use the extracted knowledge to improve existing heuristics. The first contribution of our comment is to validate and complement some of the conclusions of the authors. Then, we argue than most of the extracted knowledge can be retrieved by classical data reduction methods such as Principal Component Analysis (PCA). Hence, instead of ML-based predictions, a factorial analysis provides a powerful and synthetic view of the variables inter-dependencies in the light of solution quality. Thanks to the datasets provided by the authors in the original article, new experimental results are conducted. Finally, the integration of these results into future “boosted” heuristics is discussed.

Published
2019

10. Clinicians’ Concerns About Mobile Ecological Momentary Assessment Tools Designed for Emerging Psychiatric Problems: Prospective Acceptability Assessment of the MEmind App

Author

Philippe Courtet, Christophe Lemey, Mark E. Larsen, Sofian Berrouiguet, Philippe Lenca, Jordan E. DeVylder, Michel Walter, Enrique Baca-García, Romain Billot, Hopital de Bohars - CHRU Brest (CHU - BREST ), Black Dog Institute, University of New South Wales, Sydney, Fordham University [New York], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Department of Psychiatry (Hospital Universitario Fundacion Jimenez Diaz ), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), UAM. Departamento de Psiquiatría, and Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD)

Subjects
Decision support system, Prodromal symptoms, 020205 medical informatics, decision support systems, clinical, 02 engineering and technology, clinical, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Feasibility studies, Acceptability, Mobile applications, Outpatients, 0202 electrical engineering, electronic engineering, information engineering, Prospective Studies, Ecological momentary assessment, media_common, Ecology, feasibility studies, Mental Disorders, prodromal symptoms, ecological momentary assessment, Middle Aged, mobile applications, 3. Good health, Feeling, young adult, Mental health, The Internet, Female, Psychology, decision support systems, mental health, Adult, medicine.medical_specialty, Medicina, media_common.quotation_subject, MEDLINE, Health Informatics, [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing, acceptability, medicine, Web application, Humans, Mobile technology, Psychiatry, Decision support systems, clinical, Internet, Original Paper, business.industry, Readability, outpatients, Young adult, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, internet, business
Abstract

International audience; Background: Many mental disorders are preceded by a prodromal phase consisting of various attenuated and unspecific symptoms and functional impairment. Electronic health records are generally used to capture these symptoms during medical consultation. Internet and mobile technologies provide the opportunity to monitor symptoms emerging in patients' environments using ecological momentary assessment techniques to support preventive therapeutic decision making.Objective: The objective of this study was to assess the acceptability of a Web-based app designed to collect medical data during appointments and provide ecological momentary assessment features.Methods: We recruited clinicians at 4 community psychiatry departments in France to participate. They used the app to assess patients and to collect data after viewing a video of a young patient’s emerging psychiatric consultation. We then asked them to answer a short anonymous self-administered questionnaire that evaluated their experience, the acceptability of the app, and their habit of using new technologies.Results: Of 24 practitioners invited, 21 (88%) agreed to participate. Most of them were between 25 and 45 years old, and greater age was not associated with poorer acceptability. Most of the practitioners regularly used new technologies, and 95% (20/21) connected daily to the internet, with 70% (15/21) connecting 3 times a day or more. However, only 57% (12/21) reported feeling comfortable with computers. Of the clinicians, 86% (18/21) would recommend the tool to their colleagues and 67% (14/21) stated that they would be interested in daily use of the app. Most of the clinicians (16/21, 76%) found the interface easy to use and useful. However, several clinicians noted the lack of readability (8/21, 38%) and the need to improve ergonometric features (4/21, 19%), in particular to facilitate browsing through various subsections. Some participants (5/21, 24%) were concerned about the storage of medical data and most of them (11/21, 52%) seemed to be uncomfortable with this.Conclusions: We describe the first step of the development of a Web app combining an electronic health record and ecological momentary assessment features. This online tool offers the possibility to assess patients and to integrate medical data easily into face-to-face conditions. The acceptability of this app supports the feasibility of its broader implementation. This app could help to standardize assessment and to build up a strong database. Used in conjunction with robust data mining analytic techniques, such a database would allow exploration of risk factors, patterns of symptom evolution, and identification of distinct risk subgroups.

Published
2019

11. Comparison of traffic forecasting methods in urban and suburban context

Author

Julien Salotti, Christine Solnon, Nour-Eddin El Faouzi, Romain Billot, Serge Fenet, Data Mining and Machine Learning (DM2L), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon, Geometry Processing and Constrained Optimization (M2DisCo), ANR-11-IDEX-0007,Avenir L.S.E.,PROJET AVENIR LYON SAINT-ETIENNE(2011), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)

Subjects
SVR, Computer science, Context (language use), Time Series, ARIMA, Machine learning, computer.software_genre, 01 natural sciences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 010104 statistics & probability, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 0502 economics and business, 11. Sustainability, Graphical model, Autoregressive integrated moving average, 0101 mathematics, Time series, 050210 logistics & transportation, business.industry, 05 social sciences, k-NN, Traffic flow, Traffic Forecasting, Variable Selection, Artificial intelligence, VAR, Lasso, business, computer
Abstract

International audience; In the context of Connected and Smart Cities, the need to predict short term traffic conditions has led to the development of a large variety of forecasting algorithms. In spite of various research efforts, there is however still no clear view of the requirements involved in network-wide traffic forecasting. In this paper, we study the ability of several state-of-the-art methods to forecast the traffic flow at each road segment. Some of the multivariate methods use the information of all sensors to predict traffic at a specific location, whereas some others rely on the selection of a suitable subset. In addition to classical methods, we also study the advantage of learning this subset by using a new variable selection algorithm based on time series graphical models and information theory. This method has already been successfully used in natural science applications with similar goals, but not in the traffic community. A contribution is to evaluate all these methods on two real-world datasets with different characteristics and to compare the forecasting ability of each method in both contexts. The first dataset describes the traffic flow in the city center of Lyon (France), which exhibits complex patterns due to the network structure and urban traffic dynamics. The second dataset describes inter-urban freeway traffic on the outskirts of the french city of Marseille. Experimental results validate the need for variable selection mechanisms and illustrate the complementarity of forecasting algorithms depending on the type of road and the forecasting horizon.

Published
2018

12. A clustering approach to infer Wikipedia contributors' profile

Author

Nicolas Jullien, Romain Billot, Shubham Krishna, Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Economie et de Gestion de l'Ouest (LEGO), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Mines-Télécom [Paris] (IMT)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), Université de Brest (UBO)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Môle Armoricain de Recherche sur la SOciété de l'information et des usages d'INternet (MARSOUIN), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI)-Université de Brest (UBO)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Nicolas Jullien, ACM, ANR-14-CE29-0013,CAPACITY,CAPACITES NUMERIQUES(2014), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), IMT Atlantique (IMT Atlantique), Université de Brest (UBO)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Université de Rennes (UR)-Université de Bretagne Sud (UBS)-Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] (ENSAI)-Université de Brest (UBO)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 2 (UR2)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS), and Université de Brest (UBO)-Université de Brest (UBO)-Université de Bretagne Sud (UBS)-Université Bretagne Loire (UBL)

Subjects
FOS: Computer and information sciences, Casual, Computer science, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Stability (learning theory), user proole, Computer Science - Human-Computer Interaction, 02 engineering and technology, Statistics - Applications, Human-Computer Interaction (cs.HC), Computer Science - Computers and Society, Online communities, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], 020204 information systems, 0502 economics and business, Computers and Society (cs.CY), 0202 electrical engineering, electronic engineering, information engineering, Applications (stat.AP), ACM: C.: Computer Systems Organization, Cluster analysis, User profile, 05 social sciences, Data science, Replication (computing), JEL: J - Labor and Demographic Economics/J.J5 - Labor–Management Relations, Trade Unions, and Collective Bargaining/J.J5.J54 - Producer Cooperatives • Labor Managed Firms • Employee Ownership, [SHS.GESTION]Humanities and Social Sciences/Business administration, 050211 marketing, JEL: L - Industrial Organization/L.L8 - Industry Studies: Services/L.L8.L86 - Information and Internet Services • Computer Software, JEL: O - Economic Development, Innovation, Technological Change, and Growth/O.O3 - Innovation • Research and Development • Technological Change • Intellectual Property Rights/O.O3.O31 - Innovation and Invention: Processes and Incentives, clustering, Wikipedia
Abstract

In online communities, recent studies have strongly improved our knowledge about the different types or profiles of contributors, from casual to very involved ones, through focused people. However they do so by using very complex methodologies (qualitative-quantitative mix, with a high workload to manually codify/characterize the edits), making their replication for the practitioners limited. These studies are on the English Wikipedia only. The objective of this paper is to highlight different profiles of contributors with clustering techniques. The originality is to show how using only the edits, and their distribution over time, allows to build these contributors profiles with a good accuracy and stability amongst languages. The methodology is validated with both Romanian and Danish wikis. The highlighted profiles are identifiable early in the history of involvement, suggesting that light monitoring of newcomers may be sufficient to adapt the interaction with them and increase the retention rate.

Published
2018

13. Introduction to Big Data and Its Applications in Insurance

Author

Philippe Lenca, Cécile Bothorel, Romain Billot, Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Innovation, Entrepreneurship and Management, École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], [STAT.AP]Statistics [stat]/Applications [stat.AP], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], business.industry, Computer science, 05 social sciences, Big data, Insurance industry, 050801 communication & media studies, 02 engineering and technology, Data science, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 0508 media and communications, Parallel processing (DSP implementation), [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Data_FILES, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Architecture, business
Abstract

International audience; We present an introduction to big data and its application in insurance (impact of big data, 5V and others, tools and architecture for big data, example of application in insurance).

Published
2018

14. Ecological Assessment of Clinicians' Antipsychotic Prescription Habits in Psychiatric Inpatients: A Novel Web- and Mobile Phone-Based Prototype for a Dynamic Clinical Decision Support System

Author

Sara A. Brandt, George C. Nitzburg, Juliette Ropars, Sofian Berrouiguet, Philippe Lenca, María Luisa Barrigón, Enrique Baca-García, Raquel Álvarez-García, Philippe Courtet, Ivan de la Calle Gonzalez, David Delgado-Gómez, Santiago Ovejero, Romain Billot, Juan J. Carballo, Michel Walter, Soins Primaires, Santé Publique, Registre des cancers de Bretagne Occidentale (SPURBO), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Department of Psychiatry (Hospital Universitario Fundacion Jimenez Diaz ), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Hopital de Bohars - CHRU Brest (CHU - BREST ), Departamento de Estadistica (Universidad Carlos III de Madrid), Laboratoire de Traitement de l'Information Medicale (LaTIM), Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Brestois Santé Agro Matière (IBSAM), Cabaro Soluciones SA (Entreprise), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), and Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)

Subjects
Adult, Male, medicine.medical_specialty, Adolescent, Antipsychotic agents, medicine.medical_treatment, Pilot Projects, Health Informatics, Off-label use, Drug Prescriptions, Clinical decision support system, Electronic Prescribing, Young Adult, 03 medical and health sciences, [INFO.INFO-MC]Computer Science [cs]/Mobile Computing, 0302 clinical medicine, Mobile applications, [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY], Electronic prescribing, medicine, Humans, 030212 general & internal medicine, Practice Patterns, Physicians', Medical prescription, Medical diagnosis, Antipsychotic, Psychiatry, Aged, Polypharmacy, Inpatients, Internet, Original Paper, business.industry, [INFO.INFO-WB]Computer Science [cs]/Web, Middle Aged, Decision Support Systems, Clinical, 030227 psychiatry, 3. Good health, Defined daily dose, Prescriptions, Psychotic Disorders, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Feasibility Studies, Female, business, Cell Phone, Clinical decision-making, Software
Abstract

Background: Electronic prescribing devices with clinical decision support systems (CDSSs) hold the potential to significantly improve pharmacological treatment management. Objective: The aim of our study was to develop a novel Web- and mobile phone–based application to provide a dynamic CDSS by monitoring and analyzing practitioners’ antipsychotic prescription habits and simultaneously linking these data to inpatients’ symptom changes. Methods: We recruited 353 psychiatric inpatients whose symptom levels and prescribed medications were inputted into the MEmind application. We standardized all medications in the MEmind database using the Anatomical Therapeutic Chemical (ATC) classification system and the defined daily dose (DDD). For each patient, MEmind calculated an average for the daily dose prescribed for antipsychotics (using the N05A ATC code), prescribed daily dose (PDD), and the PDD to DDD ratio. Results: MEmind results found that antipsychotics were used by 61.5% (217/353) of inpatients, with the largest proportion being patients with schizophrenia spectrum disorders (33.4%, 118/353). Of the 217 patients, 137 (63.2%, 137/217) were administered pharmacological monotherapy and 80 (36.8%, 80/217) were administered polytherapy. Antipsychotics were used mostly in schizophrenia spectrum and related psychotic disorders, but they were also prescribed in other nonpsychotic diagnoses. Notably, we observed polypharmacy going against current antipsychotics guidelines. Conclusions: MEmind data indicated that antipsychotic polypharmacy and off-label use in inpatient units is commonly practiced. MEmind holds the potential to create a dynamic CDSS that provides real-time tracking of prescription practices and symptom change. Such feedback can help practitioners determine a maximally therapeutic drug treatment while avoiding unproductive overprescription and off-label use. [J Med Internet Res 2017;19(1):e25]

Published
2017

15. A constructivist approach for a self-adaptive decision-making system: application to road traffic control

Author

Nour-Eddin El Faouzi, Romain Billot, Salima Hassas, Maxime Gueriau, Frédéric Armetta, Systèmes Cognitifs et Systèmes Multi-Agents (SyCoSMA), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon, Lab-STICC_TB_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Département Logique des Usages, Sciences sociales et Sciences de l'Information (LUSSI), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Systèmes Multi-Agents ( SMA ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Laboratoire d'Ingénierie Circulation Transport ( LICIT UMR TE ), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux ( IFSTTAR ) -École Nationale des Travaux Publics de l'État ( ENTPE ) -Université de Lyon, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance ( Lab-STICC ), École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ) -École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Département Logique des Usages, Sciences sociales et Sciences de l'Information ( LUSSI ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], and Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT)

Subjects
Road traffic control, Traffic control, Computer science, Population, Context (language use), 02 engineering and technology, Constructivism, Machine learning, computer.software_genre, Constructivist teaching methods, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Reinforcement learning, education, [ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI], 050210 logistics & transportation, education.field_of_study, business.industry, Multi-agent system, 05 social sciences, Multi-agent systems, Representation (systemics), Reinforcement Learning, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], Connected vehicle, Unsupervised learning, [ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA], 020201 artificial intelligence & image processing, Artificial intelligence, business, computer, Decision making
Abstract

International audience; The relevance of decision making in autonomous systems is intrinsically related to the system capacity to discriminate its perception-action states. This is particularly challenging in unknown and changing complex environments, where providing a complete a priori representation to the system is not possible. To illustrate the problem, let us consider a decentralized control of road traffic, where a control device of the distributed infrastructure locally controls traffic, by learning to construct a precise representation (perception-action states) of the traffic state. In this context, it is challenging to define from prior knowledge a relevant representation of the traffic state that enables an efficient recommendation-based control. Without considering a prior domain-knowledge representation, we propose an approach able to combine a set of existing traditional unsupervised learning methods that collaborate as a population of agents in order to build an efficient representation. Our approach follows a constructivist learning perspective, where each agent produces a possible discretization of the raw sensed data. Thanks to a multi-agent reinforcement learning process, the population is able to collectively build a representation that combines the good capacities of the individual ones.

Published
2016

16. How to assess the benefits of connected vehicles? A simulation framework for the design of cooperative traffic management strategies

Author

Romain Billot, Nour-Eddin El Faouzi, Frédéric Armetta, Salima Hassas, Julien Monteil, Maxime Gueriau, Laboratoire d'Ingénierie Circulation Transport ( LICIT UMR TE ), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux ( IFSTTAR ) -École Nationale des Travaux Publics de l'État ( ENTPE ) -Université de Lyon, Systèmes Multi-Agents ( SMA ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Département Logique des Usages, Sciences sociales et Sciences de l'Information ( LUSSI ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Lab-STICC_TB_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance ( Lab-STICC ), École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ) -École Nationale d'Ingénieurs de Brest ( ENIB ) -Université de Bretagne Sud ( UBS ) -Université de Brest ( UBO ) -Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques ( IBNM ), Université de Brest ( UBO ) -Université européenne de Bretagne ( UEB ) -ENSTA Bretagne-Institut Mines-Télécom [Paris]-Centre National de la Recherche Scientifique ( CNRS ), Trinity College Dublin, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), School of Computer Science and Statistics [Dublin], Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), and Université de Lyon-Université Lumière - Lyon 2 (UL2)

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, Traffic conflict, Poison control, Transportation, Advanced driver assistance systems, Intelligent Transportation System (ITS), 010501 environmental sciences, 01 natural sciences, Advanced Traffic Management System, SYSTEME DE TRANSPORT INTELLIGENT, Transport engineering, MODELING, 0502 economics and business, CONGESTION (TRAFIC), Intelligent transportation system, Data mining, 0105 earth and related environmental sciences, Civil and Structural Engineering, InSync adaptive traffic control system, 050210 logistics & transportation, Transport network, business.industry, 05 social sciences, C-ITS, MODELISATION, TRAFFIC MANAGEMENT, Computer Science Applications, GESTION DU TRAFIC, [ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY], Traffic congestion, Traffic management, COOPERATIVE VEHICLES, Automotive Engineering, SIMULATION, business, SIMULATEUR (CONDUITE)
Abstract

International audience; Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee dramatic improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state estimation and traffic control. C-ITS refers to three levels of cooperation between vehicles and infrastructure: (i) equipped vehicles with Advanced Driver Assistance Systems (ADAS) adjusting their motion to surrounding traffic conditions; (ii) information exchange with the infrastructure; (iii) vehicle-to-vehicle communication. Therefore, C-ITS makes it possible to go a step further in providing real time information and tailored control strategies to specific drivers. As a response to an expected increasing penetration rate of these systems, traffic managers and researchers have to come up with new methodologies that override the classic methods of traffic modeling and control. In this paper, we discuss some potentialities of C-ITS for traffic management with the methodological issues following the expansion of such systems. Cooperative traffic models are introduced into an open-source traffic simulator. The resulting simulation framework is robust and able to assess potential benefits of cooperative traffic control strategies in different traffic configurations.

Published
2016

17. Power and Exponential Functions Relating Accidents to Traffic and Rain. Calibration on a French Network

Author

Maurice Aron, Neila Bhouri, Romain Billot, Nour-Eddin El Faouzi, Régine Seidowsky, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Lab-STICC_IMTA_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-Institut Mines-Télécom [Paris] (IMT)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL), Département Logique des Usages, Sciences sociales et Sciences de l'Information (IMT Atlantique - LUSSI), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon, Communauté Université Paris-Est-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), and Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Occupancy, Operations research, Calibration (statistics), Accident risk, ACCIDENT DE LA ROUTE, URBAN MOTORWAY, 01 natural sciences, Advanced Traffic Management System, Transport engineering, 010104 statistics & probability, Power model, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 11. Sustainability, 0502 economics and business, 0101 mathematics, SAFETY PERFORMANCE FUNCTION, RISQUE, 050210 logistics & transportation, [STAT.AP]Statistics [stat]/Applications [stat.AP], POWER MODEL, 05 social sciences, Tailgating, TRAFFIC INDICATOR, Power (physics), [STAT]Statistics [stat], Variable (computer science), Geography, LOGISTIC REGRESSION, PLUIE, SURROGATE DATA, TRAFFIC DATA
Abstract

Relations between the occurrence of road accidents, traffic and rainfall conditions are valuable in setting safety objectives for traffic management, and in assessing the safety impacts of new traffic management systems, prior to their implementation. Based on traffic, road accidents and rain data collected over one year, on a French urban motorway network, a set of safety performance functions were estimated; each of them provides the accident risk per vehicle-kilometer for a certain type of accident, according to the occurrence of rain, and to the level of a traffic variable (average speed, occupancy, percentage of tailgating...). Analyses were carried out separately by lane and for two types of accidents: single-vehicle accidents and multiple-vehicle accidents.The relationships, although statistically significant, have yet to be validated by the treatment of another set of accidents.

Published
2016

18. Traffic indicators, accidents and rain: some relationships calibrated on a French urban motorway network

Author

Maurice Aron, Romain Billot, Nour-Eddin El Faouzi, Régine Seidowsky, Cadic, Ifsttar, Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), and Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, ACCIDENT, Traffic data, Occupancy, Injury accident, ACCIDENT DE LA ROUTE, ZONE URBAINE, AUTOROUTE URBAINE, rain, surrogate data, Transport engineering, Kilometer, 0502 economics and business, 11. Sustainability, TRAFIC ROUTIER, Single vehicle, 0501 psychology and cognitive sciences, RELATION VITESSE-ACCIDENT, Crash data, SECURITE, 050107 human factors, 050210 logistics & transportation, RELATION CONCENTRATION-ACCIDENT, VITESSE, [SPI.OTHER] Engineering Sciences [physics]/Other, logistic regression, 05 social sciences, traffic indicators, BASE DE DONNEES, AUTOROUTE, safety performance function, PLUIE, Traffic conditions, Environmental science, urban motorway, risk
Abstract

EWGT 2015-Euro Working Group on Transportation, DELFT, PAYS-BAS, 14-/07/2015 - 16/07/2015; The purpose of this paper is to study the link between the occurrence of injury road accidents, the prevailing traffic conditions, and the occurrence of rain. This is useful for assessing, before its implementation, the safety impact of a new traffic management. Traffic conditions were extracted from a one year traffic database which covers 150 kilometres of two or three lanes urban motorways near the city of Marseille, in the south of France. 208 loop detectors provide the individual speeds, headways, arrival times and lengths of vehicles. Based on this information, thirteen aggregated traffic variables were constituted every six minutes, such as the average speed, occupancy, short time headways and a few combinations of speed, relative speed and time gaps. 292 injuries or fatal accidents occurred on the network during the same year. The French accident database provides their characteristics - location, time and type of accidents, meteorological conditions and other parameters addressing the infrastructure, the driver and the vehicle. The rain occurrence is provided, every six minutes, from a meteorological station. A set of safety performance functions were estimated, each one giving the risk of injury accident by vehicle-kilometre according to the level of one traffic variable and according to the occurrence of rain. Generally based on logistic regression models, analyses were carried out separately by lane and for two types of accidents -single vehicle accidents and crashes between vehicles. Some relations linking accidents with traffic variables are significant: the occurrence of single vehicle accidents is related to the speed on the fast lane; the occurrence of multiple vehicle accidents is related to occupancy.

Published
2015

19. Spatiotemporal Analysis of Bluetooth Data: Application to a Large Urban Network

Author

Nour-Eddin El Faouzi, Alfredo Nantes, Romain Billot, Pierre-Antoine Laharotte, Etienne Côme, Latifa Oukhellou, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Génie des Réseaux de Transport Terrestres et Informatique Avancée (IFSTTAR/COSYS/GRETTIA), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, and Queensland University of Technology [Brisbane] (QUT)

Subjects
LATENT DIRICHLET ALLOCATION LDA, BLUETOOTH, Computer science, ZONE URBAINE, Urban area, computer.software_genre, SPATIO TEMPORAL CLUSTERING, Latent Dirichlet allocation, law.invention, SYSTEME DE TRANSPORT INTELLIGENT, Bluetooth, symbols.namesake, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], law, FORECASTING, 11. Sustainability, Cluster analysis, K-MEAN, geography, Data processing, geography.geographical_feature_category, Mechanical Engineering, Detector, k-means clustering, Mode (statistics), Computer Science Applications, PREVISION, DEPLACEMENT (TRAJET), Automotive Engineering, symbols, TRAFFIC TYPOLOGY, Data mining, RESEAU URBAIN, computer
Abstract

The emergence of new technologies allows better monitoring of traffic conditions and understanding of urban network dynamics. Bluetooth technology is becoming widespread, as it represents a cost-effective means for capturing road traffic in both arterials and motorways. Although the extraction of travel time from Bluetooth data is fairly straightforward, data reliability and processing is still challenging with the issues of penetration rate, mode discrimination, and detection quality. This paper presents a methodological contribution to the use of Bluetooth data for the spatiotemporal analysis of a large urban network (Brisbane, Australia). It introduces the concept of the Bluetooth origin–destination (B-OD) matrix, which is built from a network of 79 Bluetooth detectors located within the Brisbane urban area. The B-OD matrix describes the dynamics of a subpopulation of vehicles, between pairs of detectors. The results show that the characteristics of urban networks can be effectively represented through B-OD matrices. A comparison with loop detector data enables an assessment of the results' significance. Then, the spatiotemporal structure of the network is analyzed with two different clustering analyses, namely, latent Dirichlet allocation (LDA) and $K$ -means. While LDA is used to detect a temporal pattern, the $K$ -means algorithm highlights Bluetooth fundamental diagram (BFD) classes. The results show that Bluetooth data has the potential to be a reliable data source for traffic monitoring. By highlighting hidden structures of a large area, the algorithm outputs allow us to provide the road operators with a fine spatiotemporal analysis of their network, in terms of traffic conditions.

Published
2015

20. An extension of MovSim for Multi-Agent Cooperative Vehicles Modeling

Author

Maxime Gueriau, Nour-Eddin El Faouzi, Salima Hassas, Frédéric Armetta, Romain Billot, Systèmes Cognitifs et Systèmes Multi-Agents (SyCoSMA), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire d'Ingénierie Circulation Transport (LICIT), and Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon

Subjects
050210 logistics & transportation, Engineering, business.industry, Multi-agent system, 05 social sciences, Traffic simulation, 020206 networking & telecommunications, Control engineering, 02 engineering and technology, Extension (predicate logic), Traffic engineering, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], Mobile communication systems, business
Abstract

International audience; We present a multi-agent based extension of a microscopic time continuous lane-based simulator designed to develop cooperative vehicle behaviors within a connected environment.We have chosen to extend the Multi-model Open-source Vehicular-traffic SIMulator (MovSim) which offers a complete traffic simulation platform. By integrating concepts coming from artificial intelligence and related intelligent distributed systems such as multi-agent systems, we aim to model complex individual interactions (including sensors measurements, communication between vehicles and with the infrastructure).

Published
2014

21. Electric Vehicle Green Routing with Possible En-Route Recharging

Author

Fouad Baouche, Romain Billot, Rochdi Trigui, Nour-Eddin El Faouzi, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Laboratoire Transports et Environnement (IFSTTAR/AME/LTE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon, and Cadic, Ifsttar

Subjects
Battery (electricity), [SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, business.product_category, ELECTRIC VEHICLE, 0211 other engineering and technologies, DUREE DU TRAJET, ROUTING, 02 engineering and technology, 7. Clean energy, Automotive engineering, Hardware_GENERAL, 0502 economics and business, Electric vehicle, BATTERIE, Simulation, 050210 logistics & transportation, 021103 operations research, SHORTEST PATH PROBLEM, [SPI.OTHER] Engineering Sciences [physics]/Other, Location model, business.industry, 05 social sciences, Software deployment, Shortest path problem, Graph (abstract data type), Routing (electronic design automation), business, Energy (signal processing), VEHICULE ELECTRIQUE
Abstract

IEEE 17th International Conference on Intelligent Transportation Systems ITSC, Qingdao, CHINE, 08-/10/2014 - 11/10/2014; The deployment of Electric Vehicles (EVs) is constrained mainly by the restricted autonomy, the lack of charging stations, the battery recharge time and recuperation capability (e.g. braking phases or downhill). In this study we aim to develop a green routing tool to encourage the use of EV. To overcome the autonomy limitation we propose a methodology for the EV that includes a charging stations location model, an energy graph construction for EV routing and a resolution scheme for the routing problem with recharging stage(s) along the way on the available charging stations.

Published
2014

22. Electric Vehicle Shortest Path Problem with Replenishment Constraint

Author

Rochdi Trigui, Romain Billot, Nour-Eddin El Faouzi, Fouad Baouche, Cadic, Ifsttar, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Laboratoire Transports et Environnement (IFSTTAR/AME/LTE), and Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, Mathematical optimization, business.product_category, ELECTRIC VEHICLE, 0211 other engineering and technologies, STATION DE CHARGE, 02 engineering and technology, 7. Clean energy, Charging station, Hardware_GENERAL, 0502 economics and business, Electric vehicle, BATTERIE, CHARGING STATION, Simulation, 050210 logistics & transportation, 021103 operations research, SHORTEST PATH PROBLEM, business.industry, [SPI.OTHER] Engineering Sciences [physics]/Other, 05 social sciences, Energy consumption, Battery capacity, Constraint (information theory), Software deployment, Shortest path problem, Routing (electronic design automation), business, VEHICULE ELECTRIQUE
Abstract

ICCVE 2014, International Conference on Connected Vehicles and Expo, VIENNE, AUTRICHE, 03-/11/2014 - 07/11/2014; The deployment of Electric Vehicles (EVs) is constrained mainly by the limited battery capacity, the limited number of charging stations and the recharging time. Our goal is to promote the use of EV by developing energy-efficient routing tools. To overcome the autonomy limitation we propose a methodology for the EV routing problem with recharging stage(s) along the way on the available charging stations.

Published
2014

23. Real-Time Queue-End Detection on Freeways with Floating Car Data : Practice-Ready Algorithm

Author

Eric Pillet, Tu-Uyen Justine Dinh, Nour-Eddin El Faouzi, Romain Billot, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), and APRR Motorway

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, QUEUE END DETECTION, 02 engineering and technology, Bottleneck, DETECTION, [SPI.AUTO]Engineering Sciences [physics]/Automatic, PROBE DATA, 0203 mechanical engineering, 11. Sustainability, 0502 economics and business, Segmentation, DETECTION D'INCIDENT, FREEWAY, Queue, Civil and Structural Engineering, Data source, 050210 logistics & transportation, business.industry, Mechanical Engineering, 05 social sciences, Detector, 020302 automobile design & engineering, Floating car data, AUTOROUTE, INCENDIE, TRAITEMENT EN TEMPS REEL, Safety risk, Network characterization, business, Algorithm
Abstract

This paper is a contribution towards an operational use of large floating car data (FCD) in traffic 47 management. The work focuses on a practice-ready approach on highways. The goal is to detect 48 in real-time the end of a perturbation. As an entire highway network is not fully equipped with 49 cameras or loop detectors, FCD have the potential to help better detect the end of a moving 50 bottleneck. This specific zone represents a significant road safety risk and there is a need for 51 better real-time detection of the end of congestion. To address this issue, real world data are 52 analyzed from a French freeway with recurrent congestion patterns. After discussing the quality 53 and precision of FCD, a dynamic spatial segmentation of the network highlights the relevance of 54 this data source from an operational standpoint. Further to the empirical network 55 characterization, a systematic detection algorithm is introduced, which is able to detect the 56 queue-end in real-time with a 500m precision. Based on the assumption of a growing penetration 57 rate of FCD in the coming years, the algorithm uses only FCD with very simple detection rules 58 and few parameters. The method is validated on real congestion cases and the results prove the 59 accuracy of the detection. A discussion about the precision of FCD and recommendations for 60 road operators are introduced.

Published
2014

24. The Root Locus Method: Application to Linear Stability Analysis and Design of Cooperative Car Following Models

Author

Nour-Eddin El Faouzi, Romain Billot, Julien Monteil, Jacques Sau, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), and Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, VEHICULE, ROOT LOCUS METHOD, INGENIERIE DU TRAFIC, Phase (waves), Stability (learning theory), Transportation, SYSTEME DE TRANSPORT INTELLIGENT, SYSTEME COOPERATIF, Control theory, Order (exchange), TRAFIC ROUTIER, INTERACTION ENTRE LES VEHICULES, CAR FOLLOWING MODELS, Design methods, Class (computer programming), business.industry, LINEAR STABILITY, Root locus, COOPERATIVE VEHICLES, Modeling and Simulation, Focus (optics), business, Software, Linear stability
Abstract

A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car following models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviors, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative car following models.

Published
2014

25. Efficient Allocation of Electric Vehicles Charging Stations: Optimization Model and Application to a Dense Urban Network

Author

Romain Billot, Rochdi Trigui, Nour-Eddin El Faouzi, Fouad Baouche, Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE), Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Laboratoire Transports et Environnement (IFSTTAR/AME/LTE), and Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université de Lyon

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Decision support system, Engineering, business.product_category, ELECTRIC VEHICLE, Real-time computing, LOCATION MODELS, 7. Clean energy, Charging station, Transport engineering, 11. Sustainability, Electric vehicle, BATTERIE, CHARGING STATION, Integer programming, Location model, business.industry, Mechanical Engineering, Computer Science Applications, Network planning and design, Automotive Engineering, AUTOPARTAGE, Routing (electronic design automation), business, Fleet management, VEHICULE ELECTRIQUE
Abstract

The deployment of Electric Vehicles (EVs) needs an optimized and cost-effective implementation of charging stations. As a decision support tool for network design, we define a methodology to allocate charging stations in a real network. This study uses trip OD matrix information from household travel survey coupled with a dynamic vehicle model to evaluate EVs consumption based on realistic trips (urban drive cycles). These trips are computed based on routing tools and supplied with elevation information. This enables an accurate characterization of energy needs in the Lyon Metropolitan Area. All these parameters are used as inputs of an integer linear optimization program for the location of charging stations. The methodology is based on an adaption of the classic fixed charge location model with a p-dispersion constraint. The results indicate that this methodology can help the future implementation of charging stations at an urban scale.

Published
2014

26. Integrating the impact of rain into traffic management online traffic state estimation using sequential Monte Carlo techniques

Author

Romain Billot, Nour-Eddin El Faouzi, Florian De Vuyst, Jacques Sau, Laboratoire de Mecanique des Fluides et d'Acoustique (LMFA), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Estimation, 050210 logistics & transportation, 0209 industrial biotechnology, Computer science, Rain intensity, Mechanical Engineering, 05 social sciences, Monte Carlo method, Traffic simulation, 02 engineering and technology, Traffic flow, computer.software_genre, 020901 industrial engineering & automation, 0502 economics and business, Key (cryptography), INRETS, State (computer science), Data mining, Particle filter, computer, Simulation, ComputingMilieux_MISCELLANEOUS, Civil and Structural Engineering
Abstract

This paper consists in a new step toward the integration of the effects of inclement weather into traffic management strategies. It is well recognized that adverse weather conditions are a critical factor impacting traffic operations and safety. In a previous work (1), a methodology for the analysis of the rain impact has been put forward and this impact on key traffic indicators (e.g. free-flow speed, capacity) has been quantified. Thanks to these quantification studies, a first parameterization of the fundamental diagram according to the rain intensity is proposed. Next, since the fundamental diagram represents the basis of many simulation tools, the goal is to develop weather-responsive traffic state estimation tools, which can be useful for control applications and traffic management. More precisely, the online traffic state estimation takes place within a Bayesian framework with particle filtering techniques (i.e. sequential Monte Carlo simulations) in combination with a parameterized first-order macroscopic model. This approach has already been validated for sensor diagnosis and accident detection. Here, the goal is to show how the integration of the weather effects can improve this efficient tool. The approach is validated with real world data from the Lyon's ring road section (8sensors from a homogeneous section). The results from different scenarios show the benefits of the integration of the rain impact for traffic state estimation. Strategies to detect a rain event in time and in space are also suggested.

Published
2010

27. Motorway travel time prediction based on toll data and weather effect integration

Author

N.-E. El Faouzi, Romain Billot, Salim Bouzebda, Laboratoire de Mathématiques Appliquées de Compiègne (LMAC), and Université de Technologie de Compiègne (UTC)

Subjects
Operations research, Computer science, 020209 energy, Transportation, 02 engineering and technology, [MATH.MATH-FA]Mathematics [math]/Functional Analysis [math.FA], Transport engineering, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Information system, Electronic toll collection, Real-time data, Intelligent transportation system, ComputingMilieux_MISCELLANEOUS, General Environmental Science, Interurban, Estimation, 050210 logistics & transportation, Data collection, biology, Mechanical Engineering, 05 social sciences, [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Toll, biology.protein, Law
Abstract

This study reports the main findings of the Travel time Prediction based on electronic Toll collection (ETC) data with wEather effect integration on mOtorways (TPTEO) project aiming at developing and implementing a route planner tool and travel time prediction system on the interurban motorway network managed by French motorway AREA Company. One of the main innovative characteristics of this project is the use of toll collection data (TCD) to derive speed and travel time estimation and prediction. This data source is becoming more and more available on motorway facilities and provides an efficient way not only to estimate and predict travel time but also to achieve the origin–destination (OD) matrices elaboration and exhibit trends in traffic. Based on the previous studies on weather effect quantification, the prediction algorithm is designed to account for the weather impact during the prediction process. The resulting tool is considered to be accurate enough and paves the way for developing weather responsive advanced traffic management and information systems.

Published
2010

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