2023Activity reportProject-TeamDANCE

7.1.1 eMob-Twin

• Keywords:
  Road traffic, Digital twin, Electric vehicle
• Functional Description:
  On a city scale, road traffic includes many electric vehicles whose batteries must be adequately charged. The eMob-Twin project, supported by an ERC Proof of Concept grant, and coordinated by Carlos Canudas-de-Wit from the Grenoble Image, Parole, Signal, Automatique laboratory (GIPSA-lab - CNRS/Université Grenoble Alpes), aims to adapt a mathematical model of traffic in the Grenoble metropolitan area to the needs of the electric cars that circulate there. It also involves optimizing electricity networks and better integrating intermittent renewable energies.
• URL:
  http://­emob-twin.­inrialpes.­fr/
• Contact:
  Carlos Canudas-De-Wit

7.1.2 GTL-Rocade

• Name:
  Grenoble Traffic Lab
• Keywords:
  Road traffic, Traffic data
• Functional Description:
  The Grenoble Traffic Lab (GTL-Rocade) initiative, led by the NeCS team, is a real-time traffic data Center (platform) that collects traffic road infrastructure information in real-time with minimum latency and fast sampling periods. The main elements of the GTL are: a real-time data-base, a show room, and a calibrated micro-simulator of the Grenoble South Ring. Sensed information comes from a dense wireless sensor network deployed on Grenoble South Ring, providing macroscopic traffic signals such as flows, velocities, densities, and magnetic signatures. This sensor network was set in place in collaboration with Inria spin-off Karrus-ITS, local traffic authorities (DIR-CE, CG38, La Metro), and specialized traffic research centers. In addition to real data, the project also uses simulated data, in order to validate models and to test the ramp-metering, the micro-simulator is a commercial software (developed by TSS AIMSUN ©).
• URL:
  https://­gtl.­inrialpes.­fr
• Contact:
  Carlos Canudas-De-Wit
• Participants:
  Alain Kibangou, Andres Alberto Ladino Lopez, Anton Andreev, Carlos Canudas-De-Wit, Dominik Pisarski, Enrico Lovisari, Fabio Morbidi, Federica Garin, Hassen Fourati, Iker Bellicot, Maria Laura Delle Monache, Paolo Frasca, Pascal Bellemain, Pietro Grandinetti, Remi Piotaix, Rohit Singhal, Vadim Bertrand

7.1.3 GTL-Ville

• Name:
  Grenoble Traffic Lab - City
• Keyword:
  Traffic data
• Functional Description:
  The GTL-Ville platform is developed within the framework of the ERC Scale-FreeBack project (http://scale-freeback.eu/). Its functions are divided into three axes: 1- Collect traffic data in real time via different sources. We are currently working with three suppliers: TomTom (company) for speed data from Floating Car Data (FCD), La Métro for counting data from existing loops and Karrus (company) to complete the counting data from La Métro via radars deployed since last fall. 2- Estimate traffic indicators with the lowest possible latency using collected data and historical data applied to models developed by PhD students of the ERC project. 3- Visualize raw data and calculated indicators via a web interface (http://gtlville.inrialpes.fr/).
• URL:
  http://­gtlville.­inrialpes.­fr
• Contact:
  Carlos Canudas-De-Wit

7.1.4 GTL-Healthmob

• Name:
  GTL-Healthmob
• Keywords:
  Road traffic, Epidemiology
• Functional Description:
  This project, initiated by the DANCE team with support from Scale-freeBack ERC and the Healthy Mobility Inria project, is a demonstrator of epidemics mitigation through efficient mobility control. First, mobility in the Grenoble urban area is captured through origin-destination matrices calibrated thanks to household travel surveys and INSEE data. The mobility is modeled from origins (residences) to destinations (activity-oriented) such as workplaces, schools, hospitals, parks, stores, malls,... This mobility model is coupled with a SIR model. Based on this complex model, the platform lets you visualize different pre-computed simulations using epidemiological and mobility restrictions parameters. This include scenarios optimized to limit the spread and the economic impact of the epidemic. The user can also run a simulation using custom parameters.
• URL:
  http://­gtlville.­inrialpes.­fr/­covid-19
• Contact:
  Carlos Canudas-De-Wit

8.1.1 Open Multi-Agent Systems

Open Multi-Agent Systems, also known as Open Networks or Dynamics Networks, are networks whose nodes can exit or enter the network at any time, as opposed to closed networks whose node set is fixed. In practice, this is a relevant question because large networks and populations often evolve with time. Mathematically, the evolution of the node set makes the utilisation of control-theoretic notions, such as stability, delicate. Our approach has developed in three phases. First, we have studied the stability of consensus in an open system under the assumption of having a finite “universe” set of possible nodes, from which the actual nodes of the network are chosen  47. Second, we have have studied the stability of contractive dynamics in the presence of joining/leaving nodes, essentially by understanding the process of node arrival/departure as a disturbance  37.

Third, we have concentrated on the important special case in which agents can be replaced by newcomers, but the total number of agents remains constant. Under this assumptions, we have studied optimization and resource allocation problems: convergence results about random coordinate descent in presence of replacements are under review and are available on ArXiv  39.

8.2.1 The continuation method

When considering limit models for large networks, we naturally fall into continuous limits. These limits can take different forms. One way to define continuous limits is to regard, instead of the agent states, their distribution. The evolution of the distribution would then be naturally described by a partial differential (PDE) or integro-differential equation. A good approximation implies that control actions can be designed on the continuous system and have guaranteed performance on the original (graph-based) one. By the thesis work of D. Nikitin and a series of papers, we have reached a twofold objective: (1) we have developed a sound and complete theoretical framework for the PDE approximation of large networked ODE systems  40; and (2) we have applied this framework to multiple applications including swarms of autonomous robots  40, traffic networks  44, and spin-torque oscillators 13.

8.2.2 Graphons

Another promising way to define continuous limits is by the concept of graph function, or graphon, which is the limit object of a sequence of dense networks 38. Conversely, finite graphs can be generated by sampling from the continuous graphon: in this case, the properties of the finite networks can be inferred from the properties of the graphon. Inspired by results on centrality measures  33, we have recently been able to use graphons to define performance metrics that quantify system-theoretic properties like stability, controllability, or sensitivity to noise  46. These metrics can be computed from the graphon at low computational cost and approximate well the system-theoretic properties of the corresponding dynamics on graphs of large-but-finite size. This approach is currently developed in the COCOON projet and the ongoing thesis of Raoul Prisant. In the meanwhile, we have deepened our analysis of the graphon-counterpart of the SIS model by proving a limit result as the number of agents goes to infinity: the corresponding article is forthcoming and the results available on ArXiv 30.

8.3.1 Electromobility

The simultaneous proliferation of electric vehicles (EVs) and intermittent renewable energy sources promises to expedite decarbonization of two sectors with highest emissions. As the transportation and power systems grow ever more coupled, modelling the traffic and energy flows in a joint manner is becoming increasingly important. Such models need to capture the transport and evolution of energy stored in EV batteries as they travel through the road network, as well as the flows of energy between the power and the transportation systems at charging stations.

To tackle these problems, we proposed a macroscopic electromobility model - Coupled Traffic and Energy (CTE) model in 29. This model augments the LWR macroscopic traffic model with an inhomogeneous advection equation, describing the evolution of vehicles' State of Charge (SoC). This twofold model can be complemented by a model of the charging station dynamics. Based on this model, a simple control law was designed to exemplify how controlling EV charging can potentially help the power grid by reducing peak demands.

In fact, the rise of electric vehicle charging is poised to become a critical aspect for various stakeholders in electrical networks. Producers, grappling with intermittent renewable energy production, transporters facing potential spikes in demand, and operators tasked with grid management, all stand to be significantly impacted. Public charging stations, in particular, can emerge as pivotal players in enhancing the resilience of the electrical grid. Given their substantial energy consumption, strategically controlling their operations can effectively offset overconsumption or overproduction.

By actively managing the energy consumption of public charging stations, it becomes possible to counterbalance fluctuations in demand or supply 20. This is particularly relevant in the context of the Frequency Containment Market, the primary European reserve market utilized for grid balancing. Here, charging stations can play a vital role in maintaining grid stability. To delve into this dynamic, we have developed a microscopic model 19. This model proposes a framework to utilize these stations for providing balancing services to the grid. The foundation of this framework lies in the implementation of charging price control laws. The control laws are established based on a simplified linearization of the Coupled Traffic, Energy, and Charging model. This model incorporates electric vehicle routing and charging decisions, taking into account the charging price and EV state of charge. In a competitive environment, charging stations actively compete with each other, aiming to maintain a specific number of charging vehicles to uphold their role as frequency containment reserves.

Furthermore, it is important to understand the impact that EVs will have inside urban traffic networks, which relates to the usual mobility patterns of people. Preliminary results in this sense are presented in 23 and in 22.

8.3.2 Multimodal mobility: pedestrial navigation

Mobility is currently evolving in urban scenarios and multimodality today is the key to more efficient transportation. In order to analyze the ecological impact of the various transportation modes, it is important to be able to detect the mode used by the commuter and the rule used to switch from one mode to another. The ultimate goal is to suggest smarter itineraries to commuters. To this purpose, detection and classification of activities in human mobility from one's principal residence to one's destination (for example, place of work, place of entertainment, etc.) is an important study to carry out. We aim to identify, with high precision, the nature of the transportation modes used during the day (walking, cycling, public transportation, car, etc.) as well as transitions from one mode to another. To reach this goal, our studies involve inertial and attitude modules, embedded in most inertial units, connected watches and smartphones. These technological tools constitute truly innovative and promising instrumentation for non-invasive automatic information capture. In 32 we have devised machine learning approaches for transportation mode detection (bus, tramway, walking, bike, kick scooter), by using features extracted from IMUs (Inertial Magnetic Units). The location of sensors on the body is crucial in order to get accurate results.

8.3.3 Multimodal mobility: Public transportation quality of service analysis

For efficient management of a transport system, feedback from system users is essential 8. This provides an assessment of the system's performance. This feedback is generally obtained via questionnaires. In a multi-modal context, user responses can be incorrectly labelled or even lack labels. This is the issue we are considering in the thesis of R. Kalaoane. We proposed three-steps method: i) select the key attributes defining the intrinsic characteristics that distinguish the different modes evaluated; ii) train a classifier on the basis of these attributes; iii) classify the unlabelled data and then compute the performance of the system in each class. By doing so, it is possible to significantly reduce the error in estimating system performance via user feedback 28. The proposed method is evaluated with data collected in Johannesburg (South Africa).

More specifically, in the PhD thesis works of N. Cele and R. Kalaoane, various questionnaires have been collected in Kwadeka, a township of the city of Durban, and in Braamfontein, Johannesburg. The purpose is to build new tools for analyzing the quality of service in public transportation. For the Kwadabeka case, which is an economically and socially disadvantaged area, the focus was on identification of the key factors affecting the satisfaction of commuters. The issue of mobility from disadvantaged areas to places of interest for work, health care, education, or entertainment poses specific challenges that cannot be approached under the same prism as that of well-resourced areas. In such areas, commuters are often captive of available transportation modes. However, very few studies have focused on identification of the key influential factors for satisfaction of these commuters. In the thesis of N. Cele, we introduced an agent based modelling and simulation approach, to identify these factors. We have shown that speed, quality of infrastructure, waiting time, accessibility, and safety constitute the key influential factors. Recommendations are then provided to improve the service according to these factors.

8.3.4 Heterogeneity and autonomy in traffic

After 70 years of research, traffic flows of homogeneous vehicles are fairly well understood. More elusive is the understanding of heterogeneous traffic flows. As of today, a novel and peculiar sort of heterogeneity is appearing in traffic: the presence of automated (possibly autonomous) and connected vehicles (CAVs). Their appearance has motivated us to assess their impact on traffic and explore their potential as means for estimation and for control. This year, we have obtained results about the coordination of heterogeneous autonomous vehicles and the ability of heterogenous platoons to withstand limitations in communication and actuation (braking, acceleration) 11.

8.3.5 Route recommendations in road traffic.

This line of research investigates the impact of real-time route recommendations on road congestion, specifically focusing on the consequences of navigation apps. The analytical approach of 25 involves a state-dependent switching system modeling a supply-demand mechanism, utilizing established macroscopic traffic flow models. The stability analysis of the system, with a particular emphasis on key parameters like road capacities, critical densities, and traffic demand, reveals that real-time recommendations have the potential to induce congestion in the network and result in unmet user demand.

Navigation apps use real-time data. However, inherent delays arise due to the necessity of collecting, communicating, and processing data before its integration into the app. In response to these challenges, in 15 we develop a macroscopic dynamic traffic assignment model: the model assumes that a subset of drivers follows navigation app directions based on delayed traffic data. The stability analysis of the model reveals and quantifies the substantial delay in traffic data, highlighting its adverse impact on network efficiency. This delay is shown to lead to oscillating trajectories and unmet demand, ultimately affecting the overall effectiveness of the transportation system.

8.3.6 Data fusion for navigation

Our activities on data fusion for navigation have been multifold, spanning filtering methods, applications of deep learning, noise compensation and applications that range from mobility to aerospace.

Key to our approach to navigation is the problem of attitude estimation. In many applications, attitude estimation algorithms rely mainly on magnetic and inertial measurements from MARG sensors (consisting of a magnetometer, a gyroscope, and an accelerometer). One of the main challenges facing these algorithms is that the accelerometer measures both gravity and an unknown external acceleration, while these algorithms assume that the accelerometer measures only the gravity. An attitude estimation algorithm on the special orthogonal group SO(3) is designed, considering the external acceleration as an unknown input with direct feedthrough to the output, with a local approximation approach. The proposed algorithm is validated through Monte Carlo simulations and real datasets, demonstrating better accuracy and enhanced performance than existing solutions 14. Another challenge is the significant power consumption of the gyroscope and its intrinsic bias motivate the need for more suitable solutions. A robust two-stage Kalman filter is designed for attitude estimation in the special orthogonal group SO(3), by considering the angular velocity as unknown input. The performance of the proposed algorithm was evaluated through Monte Carlo simulations compared to the known TRIAD algorithm, which utilizes measurements from only accelerometer and magnetometer sensors, and to the Invariant Extended Kalman Filter (IEKF), which is applied for SO(3) estimation using MARG sensor array 24.

A key application for our team is pedestrial navigation. In 17, we set the objective of proposing an energy-aware and gait corrected pedestrian dead reckoning (PDR) approach using foot-mounted magnetic, angular rate and gravity (MARG) sensors. Compared with existing algorithms of PDR, the proposed method aims to solve three main problems for real pedestrian applications. First, to avoid limitations of off-line calibration for personal step length parameters, we utilize the zero-velocity-update (ZUPT) aided pedestrian MARG performance to continuously compute one’s pose information. Meanwhile, it accumulates the moving distance for further estimation of one’s step length during the initialization process. Secondly, due to different pedestrian gaits implicating the heading deviation angle between one’s moving direction and heading, there are non-negligible impacts on pedestrian dead reckoning accuracy. The linear Kalman filter (KF) is used to recursively estimate the deviated heading.

Another application is in aerospace. We proposed a novel mitigation technique for soft error effects on the attitude estimation (AE) processing for spacecraft, especially for satellites’ application. Especially, we are focused on the soft errors that occur in space and affect, for example, the quaternion Kalman filter, running on the processor of control system of satellite, which leads to invert bits of the estimated states, miscalculations and a decreased performance. The mitigation technique detects first the presence of soft error effects on the AE algorithm output using some residuals. Then the residuals are passed to a trained machine learning (ML) models to estimate the quaternion error that will be used to correct the estimations. A supervised regression solution was proposed to correct the soft error effects, in methodology for creating a dataset for training classical ML models was developed. The results from the case-study scenario show a high reduction of soft error effects, while adding little overhead to the Kalman filter processing 10. Neural networks running on low-power edge devices can help in achieving ubiquitous computing with limited infrastructure. When such edge devices are deployed in conventional and extreme environments without the necessary shielding, they must be fault tolerant for reliable operation 21. Therefore, we explored mitigation strategies based on machine learning 9 and methods to ensure fault tolerance 26.

Finally, we have approached navigation through the generalized rigid registration problem in high-dimensional Euclidean spaces 16. Simulation results indicate the correctness of the proposed method and also present its efficiency on computation-time consumption, compared with previous algorithms using singular value decomposition (SVD) and linear matrix inequality (LMI). The proposed scheme is then applied to an interpolation problem on the special Euclidean group SE(n) with covariance-preserving functionality.

8.4.1 Attention dynamics in social media

According to some popular narrative, social media are plagued by issues like the viral diffusion of fake news and the formation of filter bubbles, that is situations in which an Internet user encounters only information and opinions that conform to and reinforce his/her own beliefs. Our research makes the hypothesis that these phenomena are a natural byproduct of the very nature of online social networks, which make interactions highly dynamical and introduce unprecedented effects of feedback and scale through the action of algorithms that measure, personalize, and monetize an individual’s online experience  45. Our research more precisely concentrates on what we can call “trending bubbles": digital media and their algorithms concentrate the public debate, drawing a disproportionate amount of attention on a few items and then away from them in a very short time. These effects derive from the tendency to emphasize novelty and timeliness in terms of identifying unprecedented surges of activity. Concretely, this line of research aims at identifying the concentration and scattering of media attention through a parsimonious mathematical model that captures the time evolution of collective behaviors. Based on our understanding of attention dynamics 27 and our recent mathematical model  36, we are pursuing the work of currently testing the predictions of the model on data sets collected with our partners at the Centre Internet et Société (CIS), Paris, about the fruition of contents on selected YouTube channels.

10.1.1 Participation in other International Programs: PHC (Partenariat Hubert Curien)

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

Participants: Carlos Canudas de Wit.

• Visited institution:
  University of California, Berkeley
• Country:
  USA
• Dates:
  2 weeks in November 2023
• Type of mobility:
  Gave two key notes. Collaboration with Marta Gonzalez.

Participants: Alain Kibangou, Hassen Fourati.

• Visited institution:
  University of Johannesburg
• Country:
  South Africa
• Dates:
  May 2-14; Sept. 22-27 (Kibangou); Dec. 3-6 (Kibangou and Fourati)
• Context of the visit:
  Exchanges within the PercepTrans project framework
• Mobility program/type of mobility:
  research stay, lectures, data collection campaign

Participants: Tommaso Toso.

• Visited institution:
  Cornell University
• Country:
  USA
• Dates:
  October-December
• Context of the visit:
  Collaboration on a game-theoretic approach to study the role of information and users' choices in multi-modal mobility.
• Mobility program/type of mobility:
  Research stay

11.1.1 Scientific events: organisation

P. Frasca has organized an Open Invited Track on “Control for Socio-Technical Network Systems”, IFAC World Congress, Yokohama, Japan, July 2023 (with G. Como, K. Savla, F. Parise)

M. Čičić has organized two invited sessions at the 62nd IEEE Conference on Decision and Control (CDC), Marina Bay Sands, Singapore, 2023: “Control of Connected and Autonomous Vehicles in Mixed Traffic”, together with Maria Laura Delle Monache, Cecilia Pasquale, and Fei Miao, and “Electromobility: the Interface between Transportation, Power Systems and Markets”, together with Carlo Cenedese, Carlos Canudas-de-Wit, and John Lygeros.

11.1.2 Scientific events: selection

F. Garin has been Associate Editor in the European Control Association (EUCA) Conference Editorial Board (ECC) since 2017

11.1.3 Journal

11.1.4 Invited talks

Carlos Canudas de Wit gave a presentation about Continuation methods at CRAN in January 2023, and the talk `EVs and renewable energy: Paving the way for greener electromobility networks', UC Berkeley CEE seminar, Nov. 13th, 2023

Alain Kibangou gave public lectures titled 'Impact of delayed information in navigation systems on road traffic' on May 6, 2023 and 'Machine Learning for analyzing users’ feedback' on December 5, 2023 at University of Johannesburg (South Africa).

Hassen Fourati gave a public lecture `On the use of inertial measurement units and smartphones for transportation mode classification' at the University of Johannesbourg, December 2023.

Paolo Frasca has given the invited lectures on “Navigation systems in traffic networks: Route recommendations and performance degradation”, at Focus Period Symposium on Network Dynamics and Control, Linköping, September 20–22, 2023 and “Potential deterioration in transportation network efficiency due to route recommendations”, at the Games, Learning, and Networks. Worksho on Games on networks, Singapore, 3–6 April 2023

Federica Garin has given the talk `Spectra of graphon operators and dynamical properties of systems on large graphs', GdR-MACS Workshop on Multi-agent Systems, CNAM Paris, Dec. 7th, 2023

11.1.5 Leadership within the scientific community

GdR MACS P. Frasca is member of the steering committee of the GdR MACS, a CNRS body that coordinates national activities in Automatic Control in France, 2019-2023. In this role, he contributed to GdR MACS's periodic report 31.

IEEE and IFAC C. Canudas de Wit is Fellow of the IEEE and of the IFAC (International Federation of Automatic Control), both since 2016. P. Frasca is Senior member of the IEEE since 2018. Team members participate to the following technical committees of IEEE Control Systems Society and of the IFAC: IEEE-CSS Technical Committee “Networks and Communications Systems” (P. Frasca and F. Garin); IFAC Technical Committee 1.5 on Networked Systems (P. Frasca and C. Canudas de Wit); IFAC Technical Committee 2.5 on Robust Control (P. Frasca); IFAC Technical Committee 7.1 Automotive Control (C. Canudas de Wit); IFAC Technical Committee 7.4 Transportation systems (C. Canudas de Wit); IFAC TC 9.2. Systems and Control for Societal Impact (P. Frasca).

Hassen Fourati is board member of the `International Association of Grey Systems and Uncertainty Analysis (IAGSUA)' (link), 2023-.

11.1.6 Scientific expertise

C. Canudas de Wit has participated to the Panel 7 of the ERC-Consolidator call, May and October 2023

P. Frasca has participated to the award selection committe for the 2023 Outstanding Student Paper Prize by the Networks and Communication Systems Technical Committed of the IEEE Control Systems Society.

11.1.7 Research administration

Inria Grenoble Several team members have been involved in committees at Inria Grenoble Rhône-Alpes. C. Canudas de Wit is a member of the COST-Inria-RA (Conseil d’Orientation Scientifique et Technologique, Inria Rhône-Alpes), since 2017. F. Garin has been president (since July 2019) of `Comité des Emplois Scientifiques' (post-docs and `délégations'). H. Fourati has been a member of `Commission de développement technologique' (research engineers), since 2022.

GIPSA-lab F. Garin is `responsable du pôle automatique et diagnostic’ (chair of the Automatic Control and Diagnostics division) at GIPSA-lab, since Jan 2020. A. Kibangou is an elected member of `Conseil de laboratoire' of GIPSA-lab, since Jan 2020.

UGA A. Kibangou is in his second term as an elected member of “Conseil du pôle MSTIC" at Univ. Grenoble Alpes. Since December 2023 he has been appointed Deputy Director of pôle MSTIC. H. Fourati has been in the selection committe of the yearly funding call ‘’Initiatives de Recherche à Grenoble Alpes (IRGA)‘’ - pôle ‘’Mathématiques, Sciences et Technologies de l’Information et de la Communication (MSTIC)‘’, Université Grenoble Alpes, 2023-. H. Fourati has been co-leader of the reasearch Axis Cyber-Physical Systems (CPS) for LabEx Persyval-lab 2, 2023-2024.

11.2.1 Teaching

H. Fourati gives each year around 250h of lectures and labs on average for first and second year students at the electrical engineering department (GEII) of IUT1, and third year students of bachelor's degree at Univ. Grenoble Alpes. The courses include Mathematics, logics, networks and automatic control. He also teaches for the MARS master of the University of Grenoble. He has several responsibilities related to his teaching:

• Unité d’Enseignement (UE) at UFR Physique, Ingénierie, Terre, Environnement, Mécanique (PhITEM), Université Grenoble Alpes : ‘’Single input single output (SISO) automatic control’’, 15h CM, 9h TD, 15h TP, master 1 Electronique, Energie électrique, Automatique (EEA). Since 2023
• 2nd and 3rd tear internships, département GEII, IUT 1 Grenoble. Since 2023.

P. Frasca has lectured about Intelligent Transportation Systems & Coordination of Autonomous Vehicles in the Master Autonomous and Robotics Systems (MARS) of the University of Grenoble.

P. Frasca has lectured on “Distributed algorithms over graphs: Consensus, gossiping, relative estimation, distributed optimization” at the Peyresq Summer School on Signal Processing, Peyresq, France, June 25–July 1, 2023

A. Kibangou gives each year 250h of lectures and labs on average for first and second year students at the electrical engineering department (GEII) of IUT1 at Univ. Grenoble Alpes. The courses include Control theory and Mathematics. He is director of studies for the second year of the BUT program (Bachelor Universitaire de Technologie) and responsible of Control theory teaching.

F. Garin gives each year a class `Distributed Algorithms and Network Systems', M2, Univ. Grenoble Alpes.

11.2.2 Supervision

PhD: Tarso Kraemer Sarzi Sartori, Mitigation of cosmic ray effects on inertial navigation systems, Oct. 2023, co-advised by R. Possamai Bastos (TIMA Grenoble) and H. Fourati.

PhD in progress: Ghadeer Shaaban, Magneto-visual-inertial navigation with invariance and learning: Improving estimation in benign cases and under attacks, from October 2022, co-advised by A. Kibangou, H. Fourati and C. Prieur

PhD in progress: Tommaso Toso, Online Routing Recommendations in Multimodal Transportation Networks, from October 2021, co-advised by A. Kibangou and P. Frasca.

PhD in progress: Retsepile Kalaoane, Quality of service in public transportation: case analysis of Braamfontein, Johannesburg, from November 2021, co-advised by A. Kibangou, T. Gumbo, W. Musakwa and I. Musonda (Univ. of Johannesburg).

PhD in progress: Nomfundo Cele, Perception of Quality of Service on public transportation in developing countries, from November 2020, co-advised by A. Kibangou and W. Musakwa (Univ. of Johannesburg).

PhD in progress: Manuel Campero-Jurado, Optimal design of the urban mobility network for sustainable sharing between vehicles and soft modes of transport, since February 2023 (Advisor: C. Canudas de Wit)

PhD in progress: Arold Gaborit, Perception and human-robot interfaces: application to continuous robots for assistance with medical-surgical procedures, since October 2023 (Advisors: A. Hably, S. Caroly, H. Fourati, T. Chikhaoui)

PhD in progress: Guillaume Gasnier, Modeling and optimal control of electro-mobility networks, since January 2023 (Advisor: C. Canudas de Wit)

PhD in progress: Rémi Mourgues, Variable price-optimal policies for urban electro-mobility networks, since January 2023 (Advisor: C. Canudas de Wit)

PhD in progress: Raoul Prisant, Continuous models for the control of large networks: graphon limits, since November 2023 (Advisors: F. Garin and P. Frasca)

Master: Arold Gaborit, Estimation in soft robotics. June 2023 (Advisor: H. Fourati)

Master: Raoul Prisant, Continuous Opinion and Discrete Actions in social dynamics: analysis of a quantized model. October 2023, co-advised by F. Ceragioli and P. Frasca

11.2.3 Juries

H. Fourati has been an examiner for the PhD defence of Alicia Roux, Institut franco-allemand de recherches de Saint-Louis (ISL) & Institut de Recherche en Informatique, Mathématiques, Automatique et Signal (IRIMAS), Université de Haute-Alsace (UHA), Sept 2023.

P. Frasca has been in the PhD defence committes of

• Vera Sosnovik. Detection and analysis of issue and political ads. Université Grenoble Alpes, PhD advisor: Oana Goga. September 4, 2023
• Olivier Lindamoulage de Silva. On the efficiency of decentralized epidemic management and competitive viral marketing. PhD Advisors: Irinel-Constantin Morarescu, Samson Lasaulce. Université de Lorraine, September 28, 2023
• Jonathan Adams. Mathematical modelling of person-to-person opinion exchange: understanding and quantifying polarisation. Queensland University of Technology, Brisbane, Australia. PhD advisor: Gentry White. External referee, 2023

H. Fourati has been member of the recruiting committee for Lecturers (ATER), UFR Physique, Ingénierie, Terre, Environnement, Mécanique (PhITEM), Université Grenoble Alpes, May 2023.

F. Garin has been member of the recruiting committee for a MCf (assistant professor) position, sect. 61, at École Centrale Lille.

A. Kibangou has been member of the recruiting committee for a MCf (assistant professor) position, sect. 63, at Univ. Grenoble, IUT1-GEII.

11.3.1 Articles and contents

Hassen Fourati has been coauthor of the article ‘’Couplage de navigation magnéto-inertielle filtrage de Kalman avec intelligence artificielle‘’ on the journal Techniques de l'Ingénieur 18Article (in French).

International journals

• 7 articleG.Gérard Favier and A.Alain Kibangou. Tensor-Based Approaches for Nonlinear and Multilinear Systems Modeling and Identification.Algorithms169September 2023, 443HALDOI
• 8 articleR.Retsepile Kalaoane, W.Walter Musakwa, A.Alain Kibangou, T.Trynos Gumbo, I.Innocent Musonda and A.Abraham Matamanda. Bibliometric analysis of quality of service in public transportation: current and future trends.Scientific African23MarchMarch 2024, e02059HALDOIback to text
• 9 articleT.Tarso Kraemer Sarzi Sartori, H.Hassen Fourati and R.Rodrigo Possamai Bastos. Learning-based Mitigation of Soft Error Effects on Quaternion Kalman Filter Processing.IEEE Sensors Journal2412024, 1079 - 1089HALDOIback to text
• 10 articleT.Tarso Kraemer Sarzi Sartori, L. H.Luiz Henrique Laurini, H.Hassen Fourati and R.Rodrigo Possamai Bastos. Effectiveness of Attitude Estimation Processing Approaches in Tolerating Radiation Soft Errors.IEEE Transactions on Nuclear ScienceJune 2023, 1-8HALDOIback to text
• 11 articleD.Di Liu, S.Sebastian Mair, K.Kang Yang, S.Simone Baldi, P.Paolo Frasca and M.Matthias Althoff. Resilience in Platoons of Cooperative Heterogeneous Vehicles: Self-organization Strategies and Provably-correct Design.IEEE Transactions on Intelligent Vehicles2023, 1-14HALDOIback to text
• 12 articleA.Andrea Mattioni, S.Samuele Zoboli, B.Bojan Mavkov, D.Daniele Astolfi, V.Vincent Andrieu, E.Emmanuel Witrant, P.Paolo Frasca and C.Christophe Prieur. Enhancing deep reinforcement learning with integral action to control tokamak safety factor.Fusion Engineering and Design1962023, 114008HALDOI
• 13 articleD.Denis Nikitin, C.Carlos Canudas-De-Wit, P.Paolo Frasca and U.Ursula Ebels. Synchronization of Spin-Torque Oscillators via Continuation Method.IEEE Transactions on Automatic Control68112023, 6621-6635HALDOIback to text
• 14 articleG.Ghadeer Shaaban, H.Hassen Fourati, A.Alain Kibangou and C.Christophe Prieur. MARG Sensor-Based Attitude Estimation On SO(3) Under Unknown External Acceleration.IEEE Control Systems LettersDecember 2023, 1-6HALDOIback to text
• 15 articleT.Tommaso Toso, A. Y.Alain Y Kibangou and P.Paolo Frasca. Impact on Traffic of Delayed Information in Navigation Systems.IEEE Control Systems Letters7May 2023, 1500-1505HALDOIback to text
• 16 articleJ.Jin Wu, M.Miaomiao Wang, H.Hassen Fourati, H.Hui Li, Y.Yilong Zhu, C.Chengxi Zhang, Y.Yi Jiang, X.Xiangcheng Hu and M.Ming Liu. Generalized n-Dimensional Rigid Registration: Theory and Applications.IEEE Transactions on Cybernetics532February 2023, 927-940HALDOIback to text
• 17 articleZ.Zebo Zhou, Z.Zeliang Zhang, S.Shanhui Mo, J.Jin Wu and H.Hassen Fourati. Online Calibrated, Energy-aware and Heading Corrected Pedestrian Navigation with Foot-Mounted MARG Sensors.Measurement - Journal of the International Measurement Confederation (IMEKO)206JanuaryJanuary 2023, 112268HALDOIback to text

National journals

• 18 articleH.Hassen Fourati and C.Christophe Prieur. Magneto-inertial navigation - Coupling Kalman filtering with artificial intelligence.Techniques de l'IngénieurSeptember 2023, S7809HALDOIback to text

International peer-reviewed conferences

• 19 inproceedingsM.Mladen Čičić, G.Guillaume Gasnier and C.Carlos Canudas de Wit. Electric Vehicle Charging Station Pricing Control under Balancing Reserve Capacity Commitments.CDC 2023 - 62nd IEEE Conference on Decision and ControlSingapour, SingaporeIEEE2023, 1-7HALback to text
• 20 inproceedingsM.Mladen Čičić, C.Carlos Vivas, C.Carlos Canudas de Wit and F.Francisco Rubio. Optimal Renewable Energy Curtailment Minimization Control Using a Combined Electromobility and Grid Model.IFAC WC 2023 - 22nd IFAC World CongressYokohama, JapanJuly 2023, 1-7HALback to text
• 21 inproceedingsJ.Jonas Gava, T.Tarso Kraemer Sarzi Sartori, A.Alex Hanneman, R.Rafael Garibotti, N.Ney Calazans, H.Hassen Fourati, R.Rodrigo Possamai Bastos, R.Ricardo Reis and L.Luciano Ost. Soft Error Assessment of Attitude Estimation Algorithms Running in a Resource-constrained Device under Neutron Radiation.RADECS 2023 - International Conference on Radiation and its Effects on Components and SystemsToulouse, France2023, 1-4HALback to text
• 22 inproceedingsR.Rémi Mourgues, M.Martin Rodriguez-Vega and C.Carlos Canudas de Wit. Optimal location of EVs public charging stations based on a macroscopic urban electromobility model.CDC 2023 - 62nd IEEE Conference on Decision and ControlSingapore, SingaporeIEEE2023HALback to text
• 23 inproceedingsM.Martin Rodriguez-Vega, C.Carlos Canudas de Wit, G.Giovanni de Nunzio and B.Bassel Othman. A Graph-Based Mobility Model for Electric Vehicles in Urban Traffic Networks: Application to the Grenoble Metropolitan Area.21st European Control Conference (ECC)ECC 2023 - 21st European Control ConferenceBucarest, Romania2023, 1-8HALDOIback to text
• 24 inproceedingsG.Ghadeer Shaaban, H.Hassen Fourati, A.Alain Kibangou and C.Christophe Prieur. Gyro-Free Kalman Filter with Unknown Inputs for SO(3)-based Attitude Estimation.IPIN 2023 - 13th International Conference on Indoor Positioning and Indoor NavigationNuremberg, GermanyIEEE2023, 1-6HALDOIback to text
• 25 inproceedingsT.Tommaso Toso, A. Y.Alain Y Kibangou and P.Paolo Frasca. Modeling the Impact of Route Recommendations in Road Traffic.IFAC WC 2023 - 22nd IFAC World Congress562Yokohama, JapanElsevierNovember 2023, 4179-4185HALback to text

Conferences without proceedings

• 26 inproceedingsA. J.Anuj Justus Rajappa, P.Philippe Reiter, T.Tarso Kraemer Sarzi Sartori, L. H.Luiz Henrique Laurini, H.Hassen Fourati, S.Siegfried Mercelis, P.Peter Hellinckx and R.Rodrigo Possamai Bastos. SMART: Selective MAC zero-optimzation for neural network reliability under radiation.ESREF 2023 - 34th European Symposium on Reliability of Electron Devices, Failure Physics and AnalysisToulouse, FranceMarch 2023, 1-4HALback to text

Scientific book chapters

• 27 inbookM.Maria Castaldo, P.Paolo Frasca and T.Tommaso Venturini. Online Attention Dynamics in Social Media.Cyber–Physical–Human Systems: Fundamentals and ApplicationsWileyJuly 2023, 1-15HALDOIback to text
• 28 inbookR.Retsepile Kalaoane, T.Trynos Gumbo, A.Alain Kibangou, W.Walter Musakwa and I.Innocent Musonda. Creating safe spaces: Scaling up public transport infrastructure investments in the City of Johannesburg.Smart and Resilient Infrastructure For Emerging Economies: Perspectives on Building Better1CRC PressNovember 2023, 119-124HALDOIback to text

Reports & preprints

• 29 miscM.Mladen Čičić and C.Carlos Canudas de Wit. Macroscopic Coupled Traffic and Energy Model in Front-tracking and Cell-based Frameworks.2023HALback to text
• 30 miscJ.-F.Jean-François Delmas, P.Paolo Frasca, F.Federica Garin, V.Viet Chi Tran, A.Aurélien Velleret and P.-A.Pierre-André Zitt. Individual based SIS models on (not so) dense large random networks.2023HALback to text

Other scientific publications

• 31 reportD.Dimitri Peaucelle, D.Damien Trentesaux, G.Gülgün Alpan, R.Romain Postoyan, J.Jean Auriol, C.Christophe Bérenguer, E.Eric Bonjour, O.Olivier Cardin, V.Vincent Cheutet, W.William Derigent, V.Valérie dos Santos Martins, S.Sylvain Durand, P.Paolo Frasca, L.Laurent Geneste, M.Marion Gilson, V.Virginie Goepp, M. K.Mamadou Kaba Traoré, J.Jimmy Lauber, M.Michaël Di Loreto, G.Guillaume Mercère, S.Sylvie Norre, E.Elena Panteley, F.François Pérès, P.Petreczky Mihaly, F.Franck Plestan, N.Nacim Ramdani, E.Evren Sahin, R.Reine Talj and L.Louise Travé-Massuyès. Groupement de Recherche MACS - Bilan 2019-2023 et Projet 2024-2028.October 2023HALback to text