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Context Presentation

The 5G evolution is the key driving factor that provides promising support for efficient V2X (Vehicle to everything) communications. Various applications with different requirements have been designed on vehicular networks to improve the driving experience by offering multiple services. In this thesis, we are interested by safety-critical applications and focus on collision avoidance systems between vehicles and pedestrians. This type of applications imposes strict reliability, wide connectivity, and a minimum end to end delay requirements. The high dynamic topology and the different types of communication technologies raise up challenges such as scalability, heterogeneity, and high traffic load to handle.

We have chosen MEC (Multiple Access/Mobile Edge Computing) that offers direct communication exchange between the mobile nodes (vehicles and pedestrians) and the network Infrastructure and used the Network Slicing mechanism to separate the critical vehicular traffic with high priority and strict requirements from other traffic. In our scenario a network congestion risk while vehicles and pedestrians send their BSM and CAM messages to the network infrastructure. Indeed, periodical transmissions could be unnecessary or harmful especially when the network density is high. Therefore, an intelligent scheme should be developed to adapt the transmission frequency of these messages to a network server without overloading the network, while considering the dynamic network state.

The main contribution of our work is to exploit the rich environment Information and analyze those data to take future decisions and to predict the network state to decrease the traffic load and finally to meet the objective requirements. Thus, we argue for the use of advanced Machine Learning techniques to learn from the available network data and take the appropriate action by choosing the best parameters' configuration.

 Architecture - Chaima Zoghlami

Keywords

Autonomous vehicles, V2X Communications, Resource Allocation, Network Slicing, MEC, Machine Learning

Scientific goal

•    Improve the performance of V2X Communications in the context of critical road safety applications.

Contacts

Chaima.Zoghlami@irit.fr, Rahim.Kacimi@irit.fr, Riadh.Dhaou@irit.fr

Design of a Fleet of Connected and Autonomous Vehicles by Adaptive Multi-Agent System

Context Presentation

The theme addressed in this PhD concerns autonomous and connected vehicles. It is essential, after making a vehicle more reliable, to study how several connected autonomous vehicles will be able to interact to maximize the behavior of the collective (fluidity, fuel consumption and pollution). The Society of American Automotive Engineers (SAE International) has defined 5 levels of autonomy: level 1, in which the driver performs all maneuvers, at level 5, in which the vehicle is completely autonomous and can do without driver and / or passenger.This PhD concerns both level 4 autonomous vehicles in which the vehicle drives and the supervised driver can regain control of driving, as well as level 5 vehicles (total autonomy of the vehicle).

In this PhD, the aim is to study how each vehicle communicates with its neighboring vehicles and how it behaves / reacts in response to the information provided by its neighborhood. A lock consists in determining the information that is relevant to communicate among all the data recovered from the numerous sensors scattered in the vehicle and effectors. 

these_neoc - Guilhem Marcillaud

 

Keywords

Intelligent Transport System, Connected and Autonomous Vehicles, Multi-Agent System

Scientific goal

•    Learn how to use any data and which ones are the best to communicate

Contact

guilhem.marcillaud@irit.fr

Experimental Platform for Autonomous Vehicles

Context Presentation

Several manufacturers now offer road vehicles that are almost autonomous (Tesla, Uber, Apple, EasyMile, ...). But they still require certain situations where human control is essential, which is why research is still important in this field. Experimentation is an essential means to evaluate software in a context close to reality. Evaluation in real conditions has several disadvantages: (i) user safety is difficult to guarantee; (ii) the cost of experimentation is very high; (iii) experimental sites in urban areas are very rare; (iv) the volumes of communications with the infrastructure and the necessary processing capacities are difficult to guarantee.

In order to carry out this research and evaluate it experimentally, we are developing an environment in which model cars move in a realistic environment.

20200120_104900 - Guilhem Marcillaud 

 Keywords

Semi-real simulation, Intelligent Transport System

Scientific goal

•    Experiment algorithm with miniature model of vehicles

Contact

guilhem.marcillaud@irit.fr

Self-Organizing Unmanned Aerial Vehicles

Context Presentation

Soon, Air Traffic Control (ATC) will have to cope with a radical change in the structure of air transport. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as UAVs into the airspace, with different flight performances, will increase its heterogeneity. Previous work investigated the collision avoidance management problem using a decentralized distributed approach. To do so, an autonomous and generic multi-agent system has been proposed to address this complex problem.

The aim of this work is to test the genericity of the proposed multi-agent system (CAAMAS), already tested in simulation with airplanes, using it with real drones in ENAC’s drone aviary. Work carried out during the semester has allowed 1) to interface CAAMAS with ENAC drone software, Paparazzi UAV, 2) ease scenarists work by creating a user friendly interface to generate flight plans, 3) make CAAMAS easier to use by creating some configuration interfaces.Further work will focus on the trajectories modification of the agents to take into account the specificity of the UAV’s.

 s8EEGmWF4yBCLkcS1i2G8yg - Augustin Degas

 Keywords

Autonomous UAV; Multi-Agent System; Self-Avoidance ; Self-Adaptation ; Artificial Intelligence ;

Scientific goals

•    Self-Organization of an autonomous vehicles trafic

Contacts

augustin.degas@irit.fr, elsy.kaddoum@irit.fr

RECOVAC: Conditions for Retaking Control by Self-observation of Situations within a Connected Autonomous Vehicle

Context Presentation

Connected autonomous vehicles of level 3 are vehicles in which the human driver delegates driving control in specific situations. During these situations, it may be necessary for the human to regain control of the driving activity.

The main objective of this thesis is to develop a system for the safe and efficient transition of two-way control between the human and the autonomous vehicle.For this, the system must identify by self-observation and in real time situations in which the current driver will no longer be able to ensure driving. He must also provide a context for assessing the criticality of the situation as quickly as possible in order to anticipate and react to it as best as possible. The driving context is composed of indicators that characterize the elements that describes part of the driving process. The system is based on self-adaptive multi-agent learning systems.

Keywords

self-adaptive multi-agent systems, autonomous vehicle

Scientific goals

•    Dynamic learning using multi-agent systems

•    Generic approach to supervise the activity of a system

•    Insure the acceptability of the system by human driver

Contacts

kristell.aguilar-alarcon@irit.fr, marie-pierre.gleizes@irit.fr, loic.caroux@univ-tlse2.fr

Traffic simulation at Toulouse city scale

Context Presentation

The ANR SWITCH project is focused on studying the impact of smart city new transport modes on infrastructure. Although the new transports (electric, autonomous vehicles, transport on demand, bicycles, etc.) can facilitate intra-urban mobility and improve the quality of life, they can also create new constraints for which cities must be prepared. Then urban planners need tools to evaluate the impact of urban policies in terms of mobility and infrastructure to explore “What if? " scenarios.

These new simulation tools require mobility simulations on a city scale and on different time scales. As part of the meta-model design for the Smart City simulation, this internship is about developing an urban mobility model allowing to couple a flow-based circulation model with a multi-agent model allowing fine modeling of driver behavior. The internship must carry out a proof of concept on the Gama platform of this type of system on the scale of an agglomeration.

poster - loic sadou

Keywords

Traffic Simulation, GAMA, Multi-Agent Simulation, Smart City, Transport

Scientific goal

•    To validate a mesoscopic traffic multi-agent model considering various transports facilities

Contacts

loic.sadou@gmail.com, nicolas.verstaevel@irit.fr, frederic.amblard@ut-capitole.fr

myGates

Context Presentation

MyGates is a part of autOCampus project to experiment and validates the smart mobility particularly for electrics, connected and autonomous vehicles in a dense urban environment.

In that way, a gates management system for autonomous vehicles will make easier experiments. It combines an automatic license plate with a car model recognizer to make it usable for classic car. It also contains database to keep information over authorized car and application designed for security officer to give temporary authorization for delivering driver with a photo of the vehicle and the plate.

MyGates is designed to be added on existing gates and only create the automation system with SALTO automaton that already are managing gates. MyGates will belong to the AIoT platform that will come out in the regional platform of research and innovation (PRRI) context containing smart camera and other smart devices.

mygates - Vincent-Nam Dang

Keywords

Autonomous Vehicles, Gates, CNN, ALPR, Salto, Nvidia Jetson Nano, autOCampus

Scientific goals

•    Create automatic and connected gates managements with plate and car model recognition

•    Create a classifier with many classes that are very similar

Contacts

vincent-nam.dang@irit.fr, thiebolt@irit.fr

 

Conditions of Human Acceptability when Cooperating with an Autonomous Self-Adaptive Driving System

Context Presentation

This thesis project answers to the desire of the IRIT-SMAC and CLLE-LTC teams to work together to develop intelligent innovative solutions for the car of the future, both acceptable to humans and technologically feasible. As such, this thesis in cognitive ergonomics focuses on “drivengers”/ partially automated cars interactions.

The general goal is to investigate the conditions allowing to increase drivenger’s acceptability of automated driving, and performance when taking over the control of vehicle from automation.The project will combine several experimental studies, first conducted on a driving simulator (Simul’auto platform - CCU platform - UT2J), then on a closed city experimental circuit (autOCampus circuit - UPS (under design)).

 

Vectoriel_M.DELMAS - Maxime Delmas

Keywords

User experience, Mobility, Safety, Human Factor, Automated Cars

Contact

maxime.delmas@univ-tlse2.fr

Designing and Evaluating « Phygital » Interaction Techniques for Noise Management in the University Library

Context Presentation

The goal of this project is to provide a librarian with easy to use interactive tools to monitor and control the noise made by students in a University Library. Sensors installed in the library detect the level of noise in different places of the library. Based on this information, the librarian can observe where in the library the level is too high and hence go and warn the students.

In addition, this tool allows the librarian to define zones in the library with different levels of authorized noise, to allow different forms of work in the library. For monitoring and control, the approach we explore in this project is based on the use of a physical model representing the whole library as it may constitute a strong support to the librarian to understand to which place in the library the information is related to.

Illustration - Xiaobo Feng

Keywords

Interaction techniques, Phygital Interaction Technique

Scientific goals

•    Design and implement “phygital interaction techniques”, i.e. based on the use of a physical support to visualize and interact with digital data related to a physical location. Combining an immersive visualization and a physical model requires the development of original and relevant techniques.

•    Assess the impact of phygital interaction techniques, on the usability of the interaction technique. Users experiments will be conducted to compare our solutions to monitoring application based on the use of lists of table and zones.

Contact

Jiaming.Feng@irit.fr

Interaction Techniques for Situated Data through a Physical Model

Context Presentation

Over the last decades, the amount of data has increased to 29000 Go produced each second. Understanding the data requires tools to transform these numbers, texts and images into concrete representations. The field of data visualization aims to produce data representation to visualize and analyze abstract data. Building, people or vehicles produce a lot of data collected by many sensors. These specific data are related to a physical location (e.g. number of people in a room is related to the room, humidity in a floor is related to the floor, etc.) Bring and display them close from their physical context allow people to make a better representation of the data (Embedded Data Representations, Willet et al. , 2017).

In this project we aim to design interaction techniques to navigate and manipulate the data close to a physical referent. The main goal is to develop a full interactive physical model of the campus endowed with situated data.

3d flat retouche5 - Cabric Florent(1)

Keywords

Interaction Techniques, Situated Data, Phygital Model, Human Computer Interaction

Scientific goals

Design and evaluation interaction techniques to explore a digital modeldesign and evaluate interaction techniques with situated databuild a physical model of the campus endowed with situated data and interactive capabilities

Contacts

florent.cabric@irit.fr, emmanuel.dubois@irit.fr, marcos.serrano@irit.fr, christophe.hurter@enac.fr

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