Posts from category "réalisation"

https://vivatechnology.com/grand-public

Marie-Pierre Gleizes participera le 16/06/2022 à une table ronde sur la ville intelligente dans le cadre du VIVA Technology à Paris.

FR-AKKODIS-Vivatech - Programme

Les chercheurs des différents laboratoires des universités toulousaines qui font partie du nouveau projet Défi de la Région MIDOC : Mobilité Intelligente et Durable en Occitanie, ont participé au congrès ITS 2022 au MEETT Toulouse du 30/05 au 01/06, dans le stand de l'UFTMP.

https://www.linkedin.com/posts/autocampus_researchandinnovation-university-mobility-activity-6938051297019359232-tKNV?utm_source=linkedin_share&utm_medium=member_desktop_web

https://itseuropeancongress.com/

Le vendredi 18 mars 2022 de 14h à 17h se déroulera la demi-journée scientifique neOCampus dans l'amphi Concorde, U4, université Paul Sabatier. Les sujets de recherche des nouveaux doctorants et stagiaires de l'année 2021-2022 ainsi que les projets seront présentés.

ProgrammeJournéeNeOCampus_18mars2022

Le 25 janvier 2022 a eu lieu le lancement du nouveau Groupement d’Intérêt Scientifique (GIS) neOCampus, avec la participation des institutions, des représentants des laboratoires, des industriels partenaires et des pôles professionnels.

neOCampus est un terrain d’expérimentations et d’innovations localisé sur le campus science de Rangueil, Université Toulouse III Paul Sabatier, ouvert à tous les laboratoires de recherche de la Région et aux partenariats avec des industriels. Les principaux axes de recherche concernent l’énergie, l’eau et l’air, la qualité de vie à l’extérieur et à l’intérieur des bâtiments, la biodiversité, le développement durable, la mobilité et l'éco-citoyenneté, l’interdisciplinarité pour la conception de services et produits innovants.

Le GIS neOCampus est le résultat du développement d’un ambitieux projet qui a commencé en 2013 à partir d’une initiative des chercheurs de différents laboratoires du campus pour créer des synergies en recherche et innovation entre les laboratoires et/ou les industriels. Le GIS est une structure souple rassemblant les diverses expertises pour faire avancer l’innovation, en concrétisant la recherche interdisciplinaire et en partageant des outils et matériels. Aujourd’hui, 19 projets académiques et industriels, financés par la Région, la nation ou l’Union européenne, sont labellisés neOCampus.

Composition actuelle du GIS neOCampus19 laboratoires et centres de recherche : CDA, CESBIO, CEREMA, CIRIMAT, CLLE, CRCA, ENAC, IDETCOM, IRIT, LA,  LAAS, LAPLACE LEFE, LCC, LISST LMDC, LERASS,  MSHST, TBS

13 organisations : CEREMA, CNRS, CNES, ENAC, INP, INSAT, IRD, SGE, TBS, UFT, UT1, UT2, UT3

2 pôles de compétitivité : AerospaceValley, Derbi

Partenaires industriels dans des divers projets : EasyMile, Soben, Guide-GNSS, Orange, Kawantech, Actia, Continental, NXP, Renault, SII.

Montage d’une nacelle pour favoriser les interactions citoyennes. Projet européen Interreg Sudoe.

Modèle/contre-moule destiné à être utilisé aussi pour la fabrication de la coque du Véhicule Autonome Connecté OPen-source (VACOP) du PIA Mobilité et Transport Intelligents. Travail mené en collaboration avec l’association TIM (Toulouse Ingénierie Multidisciplinaire).

 Arrivée d’une navette autonome EasyMile. Projet TIGA VILAGIL

Piloté par le CNRS, le projet Terra Forma (PIA3 Equipex+) vise à concevoir et déployer, sur des territoires témoins, un réseau dense de capteurs environnementaux open source et à bas coût pour mieux comprendre les changements environnementaux en cours et s’y adapter. Le projet a été officiellement lancé le 24 janvier 2022. Regroupant de nombreux laboratoires toulousains, ce projet a pour but d’impliquer les citoyens et citoyennes au dispositif scientifique.

Plusieurs membres du GIS neOCampus y participent dont le co-coordinateur Arnaud Elger du laboratoire écologie fonctionnelle et environnement et Rahim Kacimi du laboratoire IRIT responsable du WP 3.2 "Plateformes Centrales".

Plus d’informations ici : https://www.insu.cnrs.fr/fr/cnrsinfo/terra-forma-un-nouveau-paradigme-pour-lobservation-des-territoires

© Terra Forma

Evénement organisé par Toulouse Metropôle pour le grand public, avec la participation des chercheurs de l'IRIT (dans le cadre du programme Vilagil). 

Invités  du programme VILAGIL/Toulouse Métropole : Université Toulouse III (IRIT, LERASS), CNRS (CLLE et LISST, ENAC et ONERA).

Lieu : allées Jules Guesde, Toulouse

CLLE, IRIT  – Toulouse University

Keywords

driving automation, discomfort, drivenger, passenger, scenario

Although it is key to improving acceptability, there is sparse scientific literature on the experience of humans as passengers in partially automated cars. The first study introduced investigated the influence of road type, weather conditions, traffic congestion level, vehicle speed, and human factors (e.g., trust in automated cars) on passenger comfort in an automated car classified as Level 3 according to the Society of Automotive Engineers (SAE). Results showed that comfort was negatively affected by driving in downtown (vs. highway), heavy rain, and congested traffic. Interaction analyses showed that reducing the speed of the vehicle improved comfort in these two last conditions. Results also showed that the most comfortable participants had the higher level of trust in automated cars. This study suggests that optimizing comfort in automated cars should take account of both driving conditions and human profiles. Hence a personalization approach should be favored over a one-for-all.Hence, in a second study, we will investigate the benefits of adapting the behavior of the automated car to the user in a driving simulator experiment. In other words, we will investigate the influence of automated driving style familiarity on automated cars acceptability and take-over performance.  

Scientific goal

Improving scientific knowledge in cognitive psychology and ergonomics regarding the interaction between human and automated cars.

Contacts

maxime.delmas_at_univ-tlse2.fr, valerie.camps_at_irit.fr, celine.lemercier_at_univ-tlse2.fr

IRIT, ENAC - Toulouse University

Keywords

Predictive Model, Human-Computer Interaction, Mixed Reality

Mixed Reality has taken off again with the arrival of Head-Mounted Displays. Moreover, mixed reality enables long-term user engagement with the IoT. Nevertheless, the design of a usable system requires many iterations between conception, implementation and evaluation. The use of a predictive model allows usability problems to be detected before implementation. In this project, our predictive model can model the completion time for pointing, validation and selection. First, we defined five new operators. Next, we have computed the unit time for each newly introduced operators. Then, we have consolidated our model through three user studies.Our model can predict the time (± 5%) to complete pointing, validation and selection tasks. 

Figure 1 - The five newly introduced operators in our model.

Scientific goals

- Identify operators for mixed reality

- Define unit times for our newly introduced operators

- Evaluate our model in ecological tasks

Contacts

florent.cabric_at_irit.fr, emmanuel.dubois_at_irit.fr, marcos.serrano_at_irit.fr

IRIT –  Toulouse University

Keywords

Autonomous vehicles, social interaction, data collection

The Vilagil program started at the end of 2020, the shuttle project is a part of this program. Earlier this year, we closed a call for tenders which allowed us to choose our shuttle supplier, EasyMile. For now, we validated the shuttle route that you can see below. Later this year, in September, the shuttle will be delivered so that we can start our experiments in October or November. Different teams will be working on the project, for instance, a team will be looking how the users on the campus will adapt themselves to the new shuttle. The shuttle will also allow us to work on data recovery and storage. 

Scientific goal

The program aims to develop a field of experimentation for autonomous vehicles, the campus is a perfect place for this. Indeed, it brings together different user flows (pedestrians, cars, cyclists, …) with a large choice of situations without being on completely public roads. It will provide a base for social interaction experiments and data collection that will be used for further projects.

Contacts

arik.urban_at_irit.fr,  marie-pierre.gleizes_at_irit.fr, rahim.kacimi_at_irit.fr

IRIT , Toulouse University

Keywords

Intelligent Transport System, Distributed optimization, Multi-Agent System, Referential Frame Transformation

Recent advancements to improve road traffic have led to the emergence of Intelligent Transport Systems (ITS). Vehicles can replace the human driver in specific context thanks to the ever-increasing number of smart devices, and they gradually become autonomous. As an autonomous entity, a vehicle behaves according to its perceptions provided by embedded sensors. Not only it can see, but it also has access to other vehicles perceptions through communications. There is a necessity for a CAV to perform social interaction and social signaling. The range of potential interlocutors is wide: vehicles, of course, but also other road users: pedestrians, motorcycles, cyclists, electric scooters and if we think ahead, robots. The overall objective is to provide CAVs with social skills making possible cooperative behavior.

The first addressed lock is the transformation of referential frame. A CAV referential frame refers to its environment self-representation. Usually, an autonomous entity uses itself as a reference point. Position, distance, vectors, etc. are calculated from it. This leads to a possible incomprehension between CAVs and the missuses of a critical information. To counter it, we have proposed a solution enabling CAV to understand information from different referential frame.

The second lock concerns the communication optimization in a fleet of CAVs. With the continuously increasing number of vehicles and smart devices, the number of sensed data become huge. Sharing the integrality of these data can cause issues like delays, errors, and bottleneck. Obviously, not everything is useful to share, and we have proposed a solution to optimize which information is shared based on its usefulness.

Figure 1: « A fleet of autonomous and connected vehicles. »

Scientific goals

- Enabling the use of an information from different referential frames

- Addressing the high dynamicity of the ITS

- Optimizing the communication volume and efficiency

Contact

guilhem.marcillaud_at_irit.fr, valerie.camps_at_irit.fr,  stephanie.combettes_at_irit.fr, marie-pierre.gleizes_at_irit.fr