6.1.1 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

6.1.2 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

6.1.3 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

7.1.1 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. In a first phase, results have been obtained by two approaches. 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  74. 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  56.In the last year, we have concentrated on multi-agent optimization problems in the presence of replacements of the agents, providing several contributions: some preliminary convergence results about random coordinate descent were presented last year in 63 (a full paper is under review), the possibility of packet losses is accounted for in 36 and an analysis based on the notion of regret has been performed in 37. Future work on OMAS will resort to the approximation methods that are described in Axis 2.

7.1.2 Cyber-Physical Systems: a control-theoretic approach to privacy and security

Cyber-physical systems are composed of many simple components (agents) with interconnections giving rise to a global complex behaviour. One line of research on security of cyber-physical systems models an attack as an unknown input being maliciously injected in the system. We study linear network systems, and we aim at characterizing input and state observability (ISO), namely the conditions under which both the whole network state and the unknown input can be reconstructed from some measured local states. We complement the classical algebraic characterizations with novel structural results, which depend only on the graph of interactions (equivalently, on the zero pattern of the system matrices). More precisely, we consider a structured system, namely a family of linear systems, where the graph of interactions is fixed while the intensities of interactions (edge weights) are free parameters. We obtain two kinds of results: generic results (also known as structural results), true for almost all interaction weights, and strongly structural results, true for all non-zero interaction weights. Our recent results 32 focus on delay-L left invertibility, namely the possibility to reconstruct the input sequence from the output sequence, with the input being reconstructed up to L time steps before the current output. Delay-L left invertibility assumes that the initial input is known, but when this property is combined with strong observability, then both the input and the state can be reconstructed. Building upon classical results on linear systems theory and on structured systems, a graphical characterization is obtained of the integers L for which a structured system is generically delay-L left invertible.

7.2.1 Node aggregation and scale-free methods

The task of controlling large-scale networks is very difficult in the first place because of its large dimensionality, making the computation of traditional control algorithms too expensive. In systems of large dimensions, the number of sensors is often much lower than the number of states, which makes it hard to identify the mathematical model of the system and to estimate its state. Similar issues arise regarding the number of actuators. Another difficulty is that the energy needed to control all nodes of the network can grow exponentially with the number of nodes, at least for some network structures 67. Therefore, in some cases, it can be preferable to control and estimate some aggregated measure of the entire network rather than all individual states, since the energy required to control aggregated quantities instead of all network states is much less. Examples of aggregate quantities would be, for instance, the average state of the whole network and its variance, or the average values in different regions of the network.

Therefore, the scale-free approach that is developed in the ERC Scale-FreeBack project is based on the aggregation of the variables that belong to neighboring nodes. The aggregation is done in such a way to construct a scale-free network, where the goal is to control the averaged state and the variance of the hubs, corresponding to regions or groups of nodes, and the control is applied to the boundaries of the hubs. In scale-free dynamic network modelling & analysis, the purpose is to reduce the system network complexity by finding the appropriate level of scale aggregation, while imposing the control and observation model properties required. The ultimate goal has consisted in developing novel control methods for scale-free network systems 16. The team has applied these novel tools to traffic networks, namely in the GTL-Ville experimental platform.

7.2.2 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 15; and (2) we have applied this framework to multiple applications including swarms of autonomous robots 15, traffic networks 22, and spin-torque oscillators  65 (full paper is to appear).

7.2.3 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 61, 51. 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. Recent works related to the application of graphons include the study of dynamics over networks 58, 60, centrality measures 49, link prediction 75, large population games 66, 52. Inspired by results on centrality measures  49, we have recently been able to use graphons to define performance metrics that quantify system-theoretic properties like stability, controllability, or sensitivity to noise  73. 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 year, our work has focused on the analysis of the SIS model, through the postdoc work of Aurélien Velleret (an article is in preparation).

7.3.1 Network-level traffic estimation, prediction and control

Methods for traffic estimation, prediction and control have been widely studied for highway traffic, but need significant advances to extend to urban traffic. Indeed, urban traffic is by nature a network problem, with issues about modeling intersections, and about dealing with the increased complexity. Our contributions have covered both estimation and prediction problems and control design.

Regarding traffic state estimation in urban networks, our contributions have dealt with three main sub-problems. First, the optimal sensor location problem was considered. In 69, the location of turning ratio sensors is considered for the dynamic case, under a limited number of available sensors. The second problem considers the estimation of flow and density using heterogeneous sources of information, such as fixed sensors and aggregated vehicle velocities from Floating Car Data (FCD).

In 68, we used FCD speed information directly to better model urban intersections, and 35 incorporates OD-matrix measurements to better estimate turning parameters using a route-based approach. These methods were validated using real data under different scenarios 18. For the third problem, we consider the estimation of the aggregated density of an urban network. To solve this problem, we propose a method to calculate a virtual representation of the same underlying physical network where each road is divided into a number of cells, such that the estimator for the virtual system converges. We show that the difference between the real and virtual averages is small: these contributions were tested using real data collected in the city of Grenoble via the Grenoble Traffic Lab for urban networks (GTL-Ville) 39.

Regarding control design, we have studied control of traffic networks where the actuators can be either traffic lights schedule or variable speed limits. Most recently, we switched our focus from classical traffic performance objectives to suitably-defined performance indexes, so as to study and minimise the fuel consumption and hence the ecological impact of traffic 17. To estimate the fuel consumption, a macroscopic network traffic model is associated with an artificial neural network calibrated using a microscopic physical energy model and data provided by a microscopic traffic simulator. We find that speed limits directly impact energy consumption and pollutant emissions, as they affect the accelerations and average speeds through the network. We design controllers with variable speed limits and with signalized access control, for improved environmental sustainability and traffic performance both in a synthetic urban area and in the peri-urban area at its boundaries. Controllers are designed with non-linear model predictive control, in which the traffic evolution and the fuel consumption are predicted with macroscopic models, and then evaluated using the microscopic traffic simulator SUMO and a physical fuel consumption and NOx emission model. The results reveal that in transient phases between different levels of congestion, the variable speed-limit controller is faster to decongest the network, in an energy-efficient way, resulting in an improvement of the environmental sustainability and the traffic performance both in the controlled network, and at its boundary roads.

7.3.2 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. Indeed until recently, traffic control infrastructures, such as ramp metering systems and variable speed limits, have been considered to be the essential tools for all traffic estimation and control goals, for instance mitigation of fluctuations in traffic flow . Today, instead, the advances in automation have brought the idea of exploiting CAVs for traffic control purposes.

In 2018, the first experimental result has finally been showed in 70: using the same ring setup of 71, one of the HVs was replaced with an AV, so as to obtain a mixed traffic scenario with a single AV. Such a ring setup approximates a scenario in which AVs are sparsely and periodically introduced in the traffic. Starting from this practical evidence of the possibility of controlling traffic flow via a limited number of autonomous vehicles, our team has developed the rigorous analysis of these experiments. Our approach has been to assess the effects, and potential improvements, of autonomous vehicles in terms of system-theoretic properties of the collective vehicle dynamics, such as of stability and string stability  59. In 12 we performed an analysis of stability and safety for strings of vehicles that are described by a realistic nonlinear model (the Optimal Velocity Model).

Further results have been obtained about the coordination of CAVs with unreliable communication 7.

For this research, we have exploited tools that pertain to Axis 1, where the vehicles constitute the nodes of a network of interactions.

7.3.3 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 27.

To tackle these problems, we proposed a macroscopic electromobility model - Coupled Traffic, Energy and Charging (CTEC) model in 28. This model augments the LWR macroscopic traffic model with an inhomogeneous advection equation, describing the evolution of vehicles' State of Charge (SoC), and is completed 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.

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. To tackle this, 27 introduces a new model depicting EVs mobility and the evolution of their State-of-Charge (SoC) in urban traffic networks. The model couples the vehicles’ mobility described by a set of dynamic equations over a graph capturing the Origin-Destination motion derived from the model introduced in  64, 48, with the energy consumption associated with the EVs mobility patterns.

7.3.4 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 20 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.

7.3.5 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 marine biology.

7.3.6 Human mobility and epidemics

Reducing human mobility is a very effective non-pharmaceutical intervention to reduce epidemics spread, and lockdowns have been effectively used in various countries in 2020. However, it is clear that mobility reductions have heavy economic and social effects. In our team, we have focused on understanding the interplay of human mobility and epidemics spread at the urban level. Our model 64 is based on an urban mobility model describing daily mobility between homes and destinations such as schools, workplaces, shopping and leisure, coupled with SIR epidemics evolution at each node of the mobility network. Mobility restrictions can be easily described in this model, either by reducing capacity of some destinations, or by reducing opening hours. An optimization problem can then be devised, to maximise economic activity (a suitably weighted average of mobility towards various categories of destinations) under the constraint that epidemics spread remains low enough to avoid saturation of ICU beds in hospitals. The model and the optimization problem were initially proposed in 64, considering an academic example. The model has then be extended and implemented to a city-level model that realistically reconstructs mobility in the Grenoble area 48, 42. As a result, the web interface GTL-Healthmob is a platform which can be used to simulate different scenarios of mobility (with or without restrictions of capacity and of opening hours) and visualise their effects on epidemic spread in the Grenoble area, see 38 for a thorough description. The complexity of the non-convex optimization problem has then been tackled, with tools from monotonic optimization and a receding-horizon approach 42.

7.4.1 Opinion dynamics and social influence

Models of social influence are much studied in network science to understand the dynamics of opinions and beliefs. The team activity in this field has been focused on the following issue  57. Social influence, through phenomena of imitation and peer pressure, tends to favour the agreement of opinions and beliefs: nevertheless, disagreement persists in social groups. How can we explain the persistence of disagreement? Our research has rigorously studied multiple mathematical models that aim to understand the persistence of disagreement. The most recent results regard the effects of limited confidence between peers  55, which can explain the formation of opinion groups. Studying these dynamics has required to solve delicate mathematical questions related to switching, nonsmooth and hybrid dynamical systems  54, 31.

Another line of research focuses on methods and algorithms to effectively influence opinions. Most methods are graph-theoretical in nature and are based on on looking for the most influential nodes 8. The setup is the following: We suppose that one strategic agent must identify k target nodes in the network in order to maximally spread its preferred opinion. In the literature, this problem is cast as the maximization of a set function and, leveraging on the submodular property, is solved in a greedy manner by solving k+ separate single targeting problems. Our main contribution is to exploit the underlying graph structure to build more refined heuristics for dense and sparse graphs.

7.4.2 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  72. 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. We have already developed a mathematical model for the attention dynamics 9 and we are currently testing the predictions of the model on data sets collected with our partners at CIS, Paris, to record the fruition of contents on selected YouTube channels and on Twitter. We are also looking for similar dynamics of attention in other situations where large numbers of individuals interact: relevant instances of such collective dynamics are large-scale scientific collaborations like the PolyMath project that we study in 11.

7.4.3 Feedback in recommendation systems

In online platforms, recommender systems are responsible for directing users to relevant contents. In order to enhance the users engagement, recommender systems adapt their output to the reactions of the users, who are in turn affected by the recommended contents. This reciprocal influence creates a feedback loop that is the focus of our work. Our main result so far has been a tractable analytical model of a user that interacts with an online news aggregator 19. Creating this model has required three delicate steps:

1. defining the model of the user (who assimilates the received information with a confirmation bias);
2. defining the model of the recommender (that proposes items with the goal of maximizing the number of user's clicks);
3. specifying their interconnection, that is, the information that they exchange.

This model is able to analytically underline the feedback loop between the evolution of the users opinion and the personalised recommendation of contents, and yields qualitative predictions that support the concerns about potential long-term effects on the consumption of contents by users. Ongoing work is addressing the experimental validation of these results.

9.1.1 Participation in other International Programs

PHC (Partenariat Hubert Curien)

9.2.1 Visits of international scientists

9.2.2 Visits to international teams

10.1.1 Scientific events: selection

H. Fourati has been

• Member of the Conference Editorial Board of the IEEE Control Systems Society (CDC and ACC), 2021-present.
• Member of the Conference Editorial Board of the IEEE robotics and automation society (RAS), with main task of coordinating reviews of regular papers submitted to the Society sponsored conference: the IEEE international conference on robotics and automation (ICRA), 2023.

F. Garin has been Associate Editor in the following editorial board:

• “European Control Association (EUCA) Conference Editorial Board” (ECC) since 2017

10.1.2 Journal

C. Canudas de Wit has been

• Senior Editor of the Asian Journal of Control AJC
• Senior Editor of IEEE Transactions on Control of Networks Systems IEEE-TCNS
• Editorial Advisory Board of Transportation Research part C

H. Fourati has been

• Associate editor at IEEE Transactions on Automation Science and Engineering (TASE).
• Associate editor at IEEE sensors journal (SJ).

P. Frasca has served in the editorial boards of

• Automatica, Associate Editor (2021–2024)
• Asian Journal of Control (Wiley), Associate Editor (2017–2022)

F. Garin has been

• Associate Editor in the editorial board of IEEE Control Systems Letters, since Dec. 2021

A. Kibangou has been

• Associate Editor in the editorial board of IEEE Transactions on Control of Networks Systems IEEE-TCNS since Jan. 2022

10.1.3 Invited talks

Alain Kibangou gave a public lecture titled 'Opportunities and Challenges of flexible mobility in modern cities' on April 20, 2022 at University of Johannesburg (South Africa). Paolo Frasca has given talks on “The closed loop between opinion formation and personalised recommendations” at the Workshop on Stochastic modeling and complex networks: application to the dynamics of opinions in social networks (Avignon, October 2022) and at the Laboratoire Jacques-Louis Lions, Paris Sorbonne (November 25, 2022).

10.1.4 Leadership within the scientific community

SAGIP   C. Canudas-de-Wit has been member of the `Conseil d'Administration' of SAGIP, the French Society of Automatic Control and Industrial Engineering (2019-2022)

CNU   H. Fourati is an elected member of CNU61 (Conseil National des Universités, Génie informatique, Automatique et Traitement du Signal), since 2015. The CNU61 committee oversees promotions of university lecturers all over France.

GdR MACS   P. Frasca is member of the steering committee of the GdR MACS, a body that is funded by CNRS and coordinates national activities in Automatic Control in France, 2019–2023

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).

10.1.5 Scientific expertise

Alain Kibangou served as reviewer for the ERC StG call. Paolo Frasca served as reviewer for the ERC CoG call.

C. Canudas de Wit has been HCERES expert for the evaluation of the LITIS research laboratory, 2022.

Hassen Fourati has been member of 5th Kimura best paper award selection committee for nomination of best paper published in 2021 at Asian journal of control (AJC).

C. Canudas de Wit has been chair of the selection committer for the IFAC-High Impact Paper 2022 prize.

10.1.6 Research administration

Inria Carlos Canudas de Wit has been member of the 'Commission de Evaluation'.

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.

Persyval-lab   F. Garin has been member of the research committee of PERSYVAL-Lab LabEx as co-leader of the research axis on cyber-physical systems (since 2019).

UGA   A. Kibangou is in his second term as an elected member of “Conseil du pôle MSTIC" at Univ. Grenoble Alpes. He has been member of this council since 2016. H. Fourati is member of “Conseil documentaire” of University Grenoble Alpes representing the discipline “Sciences and technologies”, 2020-2023.

10.2.1 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.

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 (8h in 2022).

F. Garin gives each year a class `Distributed Algorithms and Network Systems', 13.5h, M2, Univ. Grenoble Alpes.

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.

10.2.2 Supervision

• PhD: Maria Castaldo, Attention dynamics on YouTube: conceptual models, temporal analysis of engagement metrics, fake views, Univ. Grenoble Alpes, Nov. 2022, co-advised by P. Frasca and Tommaso Venturini and Floriana Gargiulo (Centre Internet et Société, CNRS)
• PhD: Pierre Gogendeau, Système multi-capteurs embarqué pour la géolocation d'animaux marins, Univ. Montpellier, from Sept. 2019, Nov. 2022, co-advised by Serge Bernard (LIRMM Montpellier), Sylvain Bonhommeau (IFREMER) and H. Fourati
• PhD: Renato Vizuete, Contributions to open multi-agent systems: consensus, optimization and epidemics, Univ. Paris-Saclay, Sept. 2022, co-advised by Elena Panteley and P. Frasca
• PhD: Ujjwal Pratap, Estimation and control for resilience in large-scale network systems, Univ. Grenoble Alpes, Sept. 2022, co-advised by C. Canudas de Wit, F. Garin, and H. Sandberg (KTH Stockholm).
• 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: Nassim Bouarour, User behavior and recommendation systems, from Oct. 2020, co-advised by Sihem Amer-Yahia (LIG Grenoble), Idir Benouaret (LIG Grenoble) and P. Frasca.
• PhD in progress: Tarso Kraemer Sarzi Sartori, Mitigation of radiation effects on the attitude estimation processing of autonomous things, from Oct. 2020, co-advised by R. Possamai Bastos (TIMA Grenoble) and H. Fourati.

10.2.3 Juries

P. Frasca has been member of the following Ph.D. defense committees:

• Carmela Bernardo. Convergence analysis of heterogeneous opinion dynamics with bounded confidence and stubbornness. University of Sannio, Benevento, Italy. Ph.D. advisor: Francesco Vasca, External referee, 2022
• Zohreh Sanai. Coordination of Open Multi-Agent Systems. University of Cagliari, Italy. PhD advisors: Carla Seatzu and Mauro Franceschelli. January 2022

F. Garin has been member of the following Ph.D. defense committees:

• Bikash Adhikari, Univ. Lorraine, Nancy, July 2022
• Renato Vizuete, Univ. Paris-Saclay, Sept. 2022

A. Kibangou has been member of the following Ph.D. defense committees:

• Antoine Lebon, Univ. Toulon, Toulon, July 2022 (Reviewer)
• Maria Castaldo, Univ. Grenoble Alpes, Grenoble, Nov. 2022
• Roza Cherfi, Univ. Grenoble Alpes, Grenoble, Dec. 2022

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

International journals

• 7 articleF.Francesco Acciani, P.Paolo Frasca, G.Geert Heijenk and A.Anton Stoorvogel. Stochastic String Stability of Vehicle Platoons via Cooperative Adaptive Cruise Control With Lossy Communication.IEEE Transactions on Intelligent Transportation Systems238August 2022, 10912-10922
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• 8 articleM.Massimo Bini, P.Paolo Frasca, C.Chiara Ravazzi and F.Fabrizio Dabbene. Graph structure-based Heuristics for Optimal Targeting in Social Networks.IEEE Transactions on Control of Network Systems93September 2022, 1189-1201
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• 9 articleM.Maria Castaldo, T.Tommaso Venturini, P.Paolo Frasca and F.Floriana Gargiulo. Junk News Bubbles: Modelling the Rise and Fall of Attention in Online Arenas.New Media and Society2492022, 2027-2045
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• 10 articleM.Mladen Čičić, C.Cecilia Pasquale, S.Silvia Siri, S.Simona Sacone and K. H.Karl Henrik Johansson. Platoon-actuated variable area mainstream traffic control for bottleneck decongestion.European Journal of Control68November2022, 100687
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• 11 articleF.Floriana Gargiulo, M.Maria Castaldo, T.Tommaso Venturini and P.Paolo Frasca. Distribution of labor, productivity and innovation in collaborative science.Applied Network Science7March 2022, 19
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• 12 articleC. M.Cristina Magnetti Gisolo, M. L.Maria Laura Delle Monache, F.Francesco Ferrante and P.Paolo Frasca. Nonlinear Analysis of Stability and Safety of Optimal Velocity Model Vehicle Groups on Ring Roads.IEEE Transactions on Intelligent Transportation Systems2311November 2022, 20628-20635
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• 13 articleP.Pierre Gogendeau, S.Sylvain Bonhommeau, H.Hassen Fourati, D.Denis de Oliveira, V.Virgil Taillandier, A.Andrea Goharzadeh and S.Serge Bernard. Dead-Reckoning Configurations Analysis for Marine Turtle Context in a Controlled Environment.IEEE Sensors Journal2212June 2022, 12298-12306
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• 14 articleT.Tarso Kraemer Sarzi Sartori, H.Hassen Fourati, M.Manon Létiche and R.Rodrigo Possamai Bastos. Assessment of Radiation Effects on Attitude Estimation Processing for Autonomous Things.IEEE Transactions on Nuclear Science697July 2022, 1610-1617
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• 15 articleD.Denis Nikitin, C.Carlos Canudas de Wit and P.Paolo Frasca. A Continuation Method for Large-Scale Modeling and Control: from ODEs to PDE, a Round Trip.IEEE Transactions on Automatic Control6710October 2022, 5118-5133
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• 16 articleD.Denis Nikitin, C.Carlos Canudas de Wit and P.Paolo Frasca. Control of Average and Deviation in Large-Scale Linear Networks.IEEE Transactions on Automatic Control6742022, 1639-1654
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• 17 articleB.Bassel Othman, G. D.Giovanni De Nunzio, D. D.Domenico Di Domenico and C.Carlos Canudas de Wit. Analysis of the Impact of Variable Speed Limits on Environmental Sustainability and Traffic Performance in Urban Networks.IEEE Transactions on Intelligent Transportation Systems2311November 2022, 1-11
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• 18 articleM.Martin Rodriguez-Vega, C.Carlos Canudas de Wit and H.Hassen Fourati. Dynamic density and flow reconstruction in large-scale urban networks using heterogeneous data sources.Transportation research. Part C, Emerging technologies137AprilApril 2022, 103569
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• 19 articleW. S.Wilbert Samuel Rossi, J. W.Jan Willem Polderman and P.Paolo Frasca. The closed loop between opinion formation and personalised recommendations.IEEE Transactions on Control of Network Systems932022, 1092 - 1103
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• 20 articleF.Fadoua Taia Alaoui, H.Hassen Fourati, A.Alain Kibangou, B.Bogdan Robu and N.Nicolas Vuillerme. Kick-scooters identification in the context of transportation mode detection using inertial sensors: Methods and accuracy.Journal of Intelligent Transportation Systems: Technology, Planning, and OperationsNovember 2022
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• 21 articleL.Liudmila Tumash, C.Carlos Canudas de Wit and M. L.Maria Laura Delle Monache. Boundary Control Design for Traffic with Nonlinear Dynamics.IEEE Transactions on Automatic Control673March 2022, 1301-1313
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• 22 articleL.Liudmila Tumash, C.Carlos Canudas de Wit and M. L.Maria Laura Delle Monache. Multi-Directional Continuous Traffic Model For Large-Scale Urban Networks.Transportation Research Part B: Methodological158AprilApril 2022, 374-402
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• 23 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, 927-940
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• 24 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, 112268
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• 25 articleM.Makia Zmitri, H.Hassen Fourati and C.Christophe Prieur. BiLSTM Network-Based Extended Kalman Filter for Magnetic Field Gradient Aided Indoor Navigation.IEEE Sensors Journal2262022, 4781-4789
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International peer-reviewed conferences

• 26 inproceedingsH.Habiba Batti, C.Chiraz Ben Jabeur, H.Hassen Fourati and H.Hassene Seddik. Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation and Obstacles Avoidance.ITSIS 2022 - International Conference on Information Technology & Smart Industrial SystemsParis, FranceJuly 2022
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• 27 inproceedingsC.Carlos Canudas de Wit, M.Martin Rodriguez-Vega, G.Giovanni de Nunzio and B.Bassel Othman. A new model for electric vehicle mobility and energy consumption in urban traffic networks.MFTS 2022- 4th Symposium on Management of Future Motorway and Urban Traffic SystemsDresden, GermanyOctober 2022
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• 28 inproceedingsM.Mladen Čičić and C.Carlos Canudas de Wit. Coupled Macroscopic Modelling of Electric Vehicle Traffic and Energy Flows for Electromobility Control.CDC 2022 - 61st IEEE Conference on Decision and ControlCancún, MexicoIEEEDecember 2022, 1-8
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• 29 inproceedingsX.Xiang Dai, H.Hassen Fourati and C.Christophe Prieur. A Dynamic Grid-based Q-learning for Noise Covariance Adaptation in EKF and its Application in Navigation.CDC 2022 - 61st IEEE Conference on Decision and ControlCancún, MexicoIEEEDecember 2022
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• 30 inproceedingsX.Xiang Dai, V.Vahid Nateghi, H.Hassen Fourati and C.Christophe Prieur. Q-Learning-Based Noise Covariance Adaptation in Kalman Filter for MARG Sensors Attitude Estimation.Inertial 2022 - 9th IEEE International Symposium on Inertial Sensors & SystemsAvignon, FranceIEEEMay 2022
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• 31 inproceedingsP.Paolo Frasca and F.Francesco Rossi. Caratheodory Solutions and their Associated Graphs in Opinion Dynamics with Topological Interactions ⋆.MTNS 2022 - 25th International Symposium on Mathematical Theory of Networks and Systems5530Bayreuth, Germany2022, 436-441
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• 32 inproceedingsF.Federica Garin. Generic Delay-L Left Invertibility of Structured Systems.NecSys 2022 - 9th IFAC Conference on Networked SystemsIFAC-PapersOnLine. Part of special issue13Zurich, Switzerland2022, 210-215
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• 33 inproceedingsT.Tarso Kraemer Sarzi Sartori, H.Hassen Fourati, A. J.Anuj Justus Rajappa, P.Philippe Reiter and R.Rodrigo Possamai Bastos. Effectiveness of Attitude Estimation Processing Approaches in Tolerating Radiation Soft Errors.RADECS 2022 - Conference on Radiation Effects on Components and SystemsVenise, ItalyOctober 2022
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• 34 inproceedingsJ.Jonathan Krook, M.Mladen Čičić and K. H.Karl Henrik Johansson. Learning Micro-Macro Models for Traffic Control Using Microscopic Data.ECC 2022 - 20th European Control ConferenceLondres, United KingdomJuly 2022, 1-6
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• 35 inproceedingsM.Martin Rodriguez-Vega, C.Carlos Canudas de Wit and H.Hassen Fourati. A Route-based Method for Turning Ratio Estimation: Application to the Grenoble Downtown Traffic Flow and Density Reconstruction.CDC 2022 - 61st IEEE Conference on Decision and ControlCancun, MexicoIEEEDecember 2022, 1-7
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• 36 inproceedingsR.Renato Vizuete, P.Paolo Frasca and E.Elena Panteley. Gradient descent for resource allocation with packet loss.IFAC-PapersOnLineNecSys 2022 - 9th IFAC Conference on Networked Systems5513Zurich, Switzerland2022, 109-114
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• 37 inproceedingsR.Renato Vizuete, C. M.Charles Monnoyer de Galland, J.Julien Hendrickx, P.Paolo Frasca and E.Elena Panteley. Resource allocation in open multi-agent systems: an online optimization analysis.CDC 2022 - 61st IEEE Conference on Decision and ControlCancun, MexicoIEEEDecember 2022, 5185-5191
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National peer-reviewed Conferences

• 38 inproceedingsU.Ujjwal Pratap, L.Leo Senique and C.Carlos Canudas de Wit. GTL-Healthmob: Simulation platform for urban mobility and epidemic control.2022 - 6èmes journées des Démonstrateurs en AutomatiqueAngers, FranceJune 2022, 1-11
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• 39 inproceedingsM.Martin Rodriguez-Vega, L.Leo Senique and C.Carlos Canudas de Wit. GTL-VILLE: Experimental platform for urban traffic state estimation.2022 - 6èmes journées des Démonstrateurs en AutomatiqueAngers, FranceJune 2022, 1-9
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• 40 inproceedingsL.Leo Senique and C.Carlos Canudas de Wit. GTL-Rocade: Experimental platform for real-time traffic modeling, prediction and control.2022 - 6èmes journées des Démonstrateurs en AutomatiqueAngers, FranceJune 2022, 1-9
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Doctoral dissertations and habilitation theses

• 41 thesisM.Maria Castaldo. Attention dynamics on YouTube : conceptual models, temporal analysisof engagement metrics, fake views.Université Grenoble Alpes [2020-....]November 2022
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• 42 thesisU.Ujjwal Pratap. Estimation and control for resilience in large-scale network systems.Université Grenoble Alpes [2020-....]September 2022
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Reports & preprints

• 43 miscM.Maria Castaldo, P.Paolo Frasca, T.Tommaso Venturini and F.Floriana Gargiulo. Doing data science with platforms crumbs: an investigation into fakes views on YouTube.July 2022
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• 44 miscM.Maria Castaldo, P.Paolo Frasca and T.Tommaso Venturini. On Online Attention Dynamics.April 2022
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• 45 miscM.Mladen Čičić and C.Carlos Canudas de Wit. Macroscopic Coupled Traffic and Energy Model in Front-tracking and Cell-based Frameworks.January 2023
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• 46 miscX.Xiang Dai, R.Romain Bourdais and H.Hervé Guéguen. On feasible solutions with guaranteed suboptimality for Quadratic Programming.February 2022
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• 47 miscC.Charles Monnoyer de Galland, R.Renato Vizuete, J.Julien Hendrickx, E.Elena Panteley and P.Paolo Frasca. Random coordinate descent for resource allocation in open multi-agent systems: submitted to IEEE Transactions on Automatic Control as a Full Paper. https://doi.org/10.48550/arXiv.2205.10259.August 2022
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• 48 miscU.Ujjwal Pratap, C.Carlos Canudas de Wit and F.Federica Garin. Where, when and how people move in large-scale urban networks: the Grenoble saga.February 2022
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