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

8.1.1 Open Multi-Agent Systems

Open Multi-Agent Systems, also known as Open Networks or Dynamic 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 utilization of control-theoretic notions, such as stability, delicate. A broad overview of the topic is presented in our very recent survey 29. 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 55. 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 42. Similar ideas underpin the analysis of epidemics in open networks that we have published this year in 27. 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 have appeared this year 14.

8.1.2 Synchronization of networks of nonlinear systems

The problem of synchronization and consensus is still a rich and interesting topic, especially when dynamics of the agents in the networks are nonlinear. Several domains of applications such as power networks (review paper on the issues if needed) want to exploit nonlinearities to achieve better performances but face increased difficulties in designing control laws that enforce synchronization between agents. To this end, contraction theory seems a promising path that allows for a systematic design procedure for nonlinear control laws to achieve incremental stability, a property that in general shows the convergence of trajectories of different systems to each other.

By leveraging this property, we considered in 43 the problem of exponential synchronization of a network of identical input-affine nonlinear time-varying systems connected through an undirected graph, in the presence of a leader. We propose sufficient metric-based conditions to design a distributed diffusive coupling feedback law in two frameworks. For the sake of simplicity, we consider a state feedback design, where synchronization is obtained for every initial condition by means of a nonlinear control law whose designed is based on the solution of contraction-based inequalities. Furthermore, we show that synchronization can still be achieved regionally under milder assumptions which relax some of the contraction-based conditions and allows computing the proposed controller by means of an algorithm based on deep neural networks (DNNs) for practical implementation. A similar approach as been used to tackle the problem of synchronization for nonlinear discrete time systems over networks 35. As a matter of fact, the problem of synchronization for discrete time systems is much more involved and requires more complex inequalities, which depend not only on the algebraic connectivity of the graph but also on the biggest Laplacian eigenvalue. By generalizing results on synchronization of linear discrete time agents, we build strong links between the solution to the synchronization problem in the linear and nonlinear framework. We focus on the class of almost differentiable (possibly time-varying) dynamics that are linear in the input and we designed contraction-based nonlinear control law which enforce synchronization in the network.

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 47; and (2) we have applied this framework to multiple applications including swarms of autonomous robots 47, traffic networks 52, and spin-torque oscillators 46. Ongoing work focuses on developing control-oriented PDE models for traffic flows on ring roads, in which one controlled vehicles aims to smooth the flow of many human-driven ones 32.

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 44. 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 37, we have recently been able to use graphons to define performance metrics that quantify system-theoretic properties of the SIS epidemics model, such as stability, controllability, or sensitivity to noise 54. 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. We have also studied the eigenvalues of the Laplacian matrix of graphs sampled from graphons, because of the importance of such eigenvalues to evaluate performance of consensus dynamics and of Markov chains, see 56 and the more recent refinements in 34.

The graphon-based approach is currently developed in the COCOON projet and the ongoing thesis of Raoul Prisant, who has already obtained results on two specific models of opinion evolution with negative interactions 24. In the meanwhile, we have also deepened our analysis of the graphon-counterpart of the SIS model by proving a limit result as the number of agents goes to infinity 7.

8.3.1 Electromobility

With the growing number of electric vehicles (EVs) in our car fleet in the coming years, combined with an increase in electricity production from renewable energy sources, stabilizing the frequency on the electrical grid will become increasingly challenging. EV charging will represent a significant source of electricity consumption. Therefore, having a transportation model for electric vehicles is crucial to understanding the evolution of their state of charge across the road network. This, in turn, enables accurate predictions of demand at charging stations 40.

One of the tools available to grid operators to address this issue is the use of various regulation systems. One such system involves incentivizing consumers to either increase or decrease their electricity consumption in exchange for compensation. There are several European markets for frequency regulation trading. The most suitable market for EV charging stations has been identified as the Frequency Containment Reserve (FCR) market, the primary European reserve market, which responds most quickly to grid operator demands 21.

To participate in this market, a charging station operator must decide, one day in advance, what capacity they can provide to support the grid. When there are many vehicles at a station, it is easier to modulate energy consumption on a larger scale compared to when there are fewer vehicles. Therefore, it is crucial for operators to predict how many vehicles will be present at their stations throughout the day. We have developed a macroscopic mobility model to predict mobility and state of charge in space and time coupled with one or more charging station operators participating in the FCR market 21 20. This model also includes decision-making processes on the part of EVs, which decide whether to charge based on their remaining battery level and the price at charging stations and in which station. We aim to determine the optimal pricing strategy for charging stations to maximize their revenue 21. In a competitive environment, where multiple charging station operators compete directly to attract vehicles, our results indicate significant benefits for EV users and the electrical grid. Prices decrease, and the capacity available to grid operators increases 20.

8.3.2 Multimodal mobility: Transportation mode classification

Due to increasing traffic congestion, travel modeling has gained importance in the development of transportion mode detection (TMD) strategies over the past decade. Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. In particular, obtaining much more information on the transportation modes used by users through smartphones is very challenging due to the variety of the data (accelerometers, magnetometers, gyroscopes, proximity sensors, etc.), the standardization issue of datasets and the pertinence of learning methods for that purpose. Reviewing the latest progress on TMD systems is important to inform readers about recent datasets used in detection, best practices for classification issues and the remaining challenges that still impact the detection performances. Existing TMD review papers until now offer overviews of applications and algorithms without tackling the specific issues faced with real-world data collection and classification. Compared to these works, the proposed review 9 provides some novelties such as an in-depth analysis of the current state-of-the-art techniques in TMD systems, relying on recent references and focusing particularly on the major existing problems, and an evaluation of existing methodologies for detecting travel modes using smartphone IMUs (including dataset structures, sensor data types, feature extraction, etc.). This review paper can help researchers to focus their efforts on the main problems and challenges identified.

8.3.3 Multimodal mobility: Analysis of informal minibus driving

Traffic accidents pose a significant public health challenge, especially in developing countries where many people rely on informal transport, such as minibus taxis. The paper 19 aims to enhance our understanding of the driving behavior of minibus taxi drivers by employing machine learning techniques to compare driving behaviors in controlled versus uncontrolled environments in Durban (eThekwini Municipality, South Africa). Informal minibus taxis play a crucial role in urban transportation, particularly in developing countries, yet their driving patterns and safety implications remain under-explored. We utilize exploratory factor analysis to analyze data collected from smartphone GPS carried by a passenger of a minibus taxi, identifying key driving behaviors and patterns. Our study highlights significant differences in driving styles between controlled and uncontrolled environments, offering insights into safety and efficiency. The findings provide valuable information for policymakers, transportation planners, and technology developers aiming to enhance urban mobility and safety in the informal transport sector. The primary finding is that a controlled environment fosters aggressive driving, while a less controlled setting encourages speeding. These findings support the eThekwini Municipality’s stance in its road safety plan, which identifies driver aggressiveness as a major factor in road traffic accidents in Durban.

8.3.4 Multimodal mobility: Public transportation quality of service analysis

Public transport is a fundamental aspect of urban life and its quality of service can significantly impact the daily life of passengers. Research on quality of service in public transport is vital to creating efficient and inclusive public transport systems. The study in 11, which is both timely and imperative, provides a systematic literature review and bibliometric analysis of quality of service in public transport with special focus on gender and machine learning. The study employed a systematic search in Web of Science using relevant keywords. Based on 270 published articles on the Web of Science, we evaluate the state of knowledge through keyword analysis, cooccurrences, and co-citations. It appears that key themes in quality of service in public transportation have shifted from efficiency to user satisfaction and perceptions. However, there is limited literature on public transport service quality in the global south, particularly in Africa, compared to the global north. In particular, the study revealed that the total publications focusing on gender in Africa is two. Moreover, much of the literature on the African continent emanates from authors and countries outside the continent. It often does not reflect the lived realities of the state of public transport in Africa. Similarly, emerging issues pertaining to machine learning and gender in public transport also require consideration. This paper paves the way for policy, practice, and further research. The review will be useful reference for evolutions of quality of service in public transport research.

8.3.5 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) 13.

8.3.6 Cycling

In recent research, we developed a graph-based framework aimed at improving cycling networks, with a focus on optimizing safety and comfort. In our first study 36, we proposed a methodology to analyze and enhance safety in cycling networks through incremental infrastructure upgrades. By employing graph theory metrics, we modeled and optimized safety levels, addressing the challenge of resource allocation via a gradual improvement strategy. This methodology was applied to the cycling network of Grenoble, demonstrating its effectiveness in enhancing overall safety by optimizing both connectivity and infrastructure upgrades. Building on this, our subsequent work 17 expanded the framework by introducing a topology optimization problem to predict and improve perceived safety and comfort. We create a model using graph theory metrics validated with real-world data on perceived safety and comfort from cyclist surveys, we designed a novel algorithm to tackle the challenge of budget allocation for maximizing these metrics. This approach achieved significant improvements in multiple real-world networks across French cities, offering actionable insights for urban planners to implement resource-efficient upgrades while maintaining a balance between accuracy and computational efficiency.

8.3.7 Route recommendations in road traffic

This line of research, which has lead to the thesis defence of Tommaso Toso 31, investigates the impact of autonomy and user connectivity on mobility. The tools we adopt are centered on studying network flows, congestion games, and associated control systems. The main focus has been real-time route recommendations by navigation apps and their effects on road congestion. The analytical approach of 51 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. Other important question is the role of cooperative, connected, fleets of users. We have obtained analaytical results showing that the deployment of cooperative fleets can bring benefits to the transportation system, but for these effects to materialize the penetration rate may need to be higher than a threshold 26.

8.3.8 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 velocity estimation. Velocity estimation of a rigid body using measurements from low-cost inertial and magnetic sensors plays an important role in various applications. The extended Kalman filter (EKF) is widely used for this purpose. However, EKF's estimation performance relies on the knowledge of process and measurement noise covariance matrices, and this information is generally unavailable. In 25, we introduce a solution that combines two techniques: the generation of velocity pseudo-measurements using a Bidirectional Long Short-Term Memory (BiLSTM) network, and the Q-learning method for online adaptation of noise covariance matrices. The performance of the proposed solution is validated using real experimental datasets, demonstrating that Q-learning can select appropriate noise covariance matrices to enhance velocity estimation.

A key application for our team is pedestrial navigation.

A magnetic-field-aided inertial navigation system (MAINS) for indoor navigation is proposed in 10. MAINS leverages an array of magnetometers to measure spatial variations in the magnetic field, which are then used to estimate the displacement and orientation changes of the system, thereby aiding the inertial navigation system (INS). Experiments show that MAINS significantly outperforms the stand-alone INS, demonstrating the remarkable two orders of magnitude reduction in position error. Furthermore, when compared with the state-of-the-art magnetic-field-aided navigation approach, the proposed method exhibits slightly improved horizontal position accuracy. On the other hand, it has noticeably larger vertical error on datasets with large magnetic-field variations. However, one of the main advantages of MAINS compared with the state of the art is that it enables flexible sensor configurations. The experimental results show that the position error after 2 min of navigation in most cases is less than 3 m when using an array of 30 magnetometers. Thus, the proposed navigation solution has the potential to solve one of the key challenges faced with current magnetic-field simultaneous localization and mapping (SLAM) solutions—the very limited allowable length of the exploration phase during which unvisited areas are mapped.

Another application is in aerospace. There is a growing incorporation of unmanned aerial vehicles (UAVs) within remote and urban environments due to their versatility and ability to access hard-to-reach and/or congested places. UAVs offer low-cost solutions for many applications, including healthcare (e.g., medical supplies delivery) and surveillance during public events, protests, or emergencies (e.g., a nuclear accident). However, drone utilization in urban areas often relies on strict regulations to ensure safe and responsible operation. UAVs are subject to radiation-induced soft errors, and identifying the most vulnerable software and hardware components to radiation exposure is an advisable task, which is difficult to undertake. An essential task to UAVs correct operation is attitude estimation (AE). We assessed in 8 the soft error reliability of three AE algorithms running on two resource-constrained microprocessors under neutron radiation.

8.3.9 Urban 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. In this context, we had proposed a human mobility model (45) that captures daily mobility pattern between residences and different destinations in a city and also incorporates epidemic spread at each location. Interestingly, the model has a modular structure, so that the mobility model can be used without the epidemics model for other purposes, and indeed it has been used in the team as the basis for further modelling efforts in the electro-mobility context.

In the paper 15, we consider this city-wide mobility-epidemics model, and we provide techniques to compute optimal mobility control policies, which tune the operating capacities of different destinations depending on their type. To obtain this kind of policies, we solve an optimization problem that takes into account the current epidemic status, and maximizes the socio-economic activity while keeping the total infections below a desired threshold. The proposed solution techniques use an outer approximation method, thanks to the monotonic nature the problem, and a receding horizon approach. We apply these techniques to the mobility network of Grenoble metropolitan area, as it is showcased in the web interface GTL-Healthmob.

8.4.1 Opinion dynamics and social influence

Models of social influence are much studied in network science to understand the dynamics of opinions and beliefs in societies. The team activity in this field has been focused on the following issue. 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 23 regard the effects of limited precision in the exchange of information during social interactions: for instance, individuals may not communicate directly, but only display their preferences by choosing among a small number of options. This kind of dynamics can explain the formation of groups that hold distinct opinions. The rigorous study of this dynamics requires delicate mathematical tools for nonsmooth and hybrid dynamical systems.

8.4.2 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 53. In the last several years we have developed a line of research that aims at identifying the concentration and scattering of media attention through a parsimonious mathematical model that captures the time evolution of collective behaviors. This has lead to several works on attention dynamics 41, including an important empirical work about the popularity of videos in YouTube channels. In this direction, this year we have published results showing that fake views, that is, views that are illicitly made by bots, play a prominent role in determining the popoularity of videos 6.

8.4.3 Modeling satisfaction in a captive users context to prevent social bomb

This research investigates the critical issue of user dissatisfaction within essential service sectors, such as water, energy, and transportation. Recognizing that many consumers are "captive" within these markets due to limited service options, a key concern is the potential for widespread dissatisfaction to escalate into significant social disruption, a phenomenon the research metaphorically terms a "social bomb." Acknowledging this risk, the study employs a novel modeling approach inspired by infectious disease models. By analyzing how dissatisfaction spreads and evolves within a population of captive users, much like the spread of a contagious disease, this research aims to inform proactive interventions in order to develop strategies for proactively addressing user concerns, improving service quality, and mitigating potential social unrest before it reaches a critical point. In 22, similar to SIS, we have introduced the SDS (Satisfied-Dissatisfied-Satisfied) model as a compartmental model for analysing the spreading of dissatisfaction among captive users of a given service. The model was analyzed, the equilibria explicitly computed and their stability analyzed. In addition, the trajectory of the system can be precisely derived. We use this property to solve an optimal time and magnitude of intervention problem to prevent dissatisfaction going beyond a given threshold. To overcome uncertainties in the model parameters, randomized strategies as in scenario optimization approach.

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria International Program

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

11.1.1 Scientific events: organisation

P. Frasca has co-organized

• Yearly GDR MACS Seminar 2024, on the topic “Multi-agent Systems”, ENSAM Paris, September 30–October 1st, 2024.
• Invited session on “Open Multi-Agent Systems: Theory and Applications”, IEEE Conference on Decision and Control, Milan, Italy, December 2024 (with M. Franceschelli, G. Oliva, J. Hendrickx)

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• C. Canudas de Wit has given the Plenary Lecture “EVs and Renewable Energy: Paving the Way for Greener Electromobility Networks” at the MFTS 2024: The 5th Symposium On Management Of Future Motorway And Urban Traffic Systems, Heraklion, Crete, Greece.
• P. Frasca has given the invited lecture “Graphons and dynamics on large graphs, from a control systems perspective”, Symposium on Collective Models for Networked Particle Systems, University of Pavia, April 16, 2024.

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.
• 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).
• EUCA
  F. Garin is Secretary of the European Control Association (EUCA), since June 2024.
• IAGSUA
  H. Fouratiis board member of the `International Association of Grey Systems and Uncertainty Analysis (IAGSUA)' (link), 2023-.

11.1.6 Scientific expertise

• Carlos Canudas de Wit has been Chairman of the IFAC High Impact Paper Award Selection Committee 2021-2023.
• Carlos Canudas de Wit has been Chairman of 7th Kimura Best Paper Award Selection Committee.
• Carlos Canudas de Wit has been Member of the ECC 2024 Best Paper Award committee.
• P. Frasca has been a member of the CE48 committee of the National Research Agency (ANR) for the general call (AAPG) 2024.
• P. Frasca has been member of the selection committee of the National French Best PhD Thesis “GdR MACS” 2024.
• F. Garin has participated to the award selection committee for the 2024 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 committee 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.
• 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

11.2.3 Juries

P. Frasca has been member of the PhD graduation committees of

• Robin Vaudry. Modeling, analysis and simulation of structured complex systems in epidemiology. Université Grenoble Alpes, PhD advisor: Clementine Prieur and Didier Georges. October 24, 2024
• Alain Toupance. Controllability of complex systems: an information theoretic approach. Université Grenoble Alpes (Valence campus), PhD advisors: Laurent Lefèvre and Bastien Chopard. August 26, 2024

F. Garin has been a member of the PhD graduation committees of

• Lucas Magnana, INSA Lyon, Feb. 2024, thesis: Algorithmes d'apprentissage pour le cyclisme urbain : modèles implicites et infrastructure dynamique, PhD advisors: Hervé Rivano and Nicolas Chiabaut
• Pablo Andrés De Villeros Arias, Université Polytechnique Hauts de France and CINVESTAV del IPN Unidad Guadalajara (Mexico), Nov. 2024, thesis: Contributions to Multi-agent System Control through Fixed-Time Distributed Optimization, PhD advisors: Michaël Defoort, Alexander Loukianov, and Mohamed Djemai
• Elis Stefansson, KTH, Stockholm, Dec. 2024, thesis: Complexity in Decision-making with Applications to Large-scale and Human-in-the-loop Systems, PhD advisors: Karl Henrik Johansson and Henrik Sandberg

A. Kibangou has been a member of the PhD graduation committee of

• Hugo Jaquard, Univ. Grenoble Alpes, Nov. 2024, thesis: Parallel Transport for Monte-Carlo Estimation on Graph Bundles, PhD advisors: P.O. Amblard, S. Barthelmé, N. Tremblay.

F. Garin has been member of the recruiting committees:

• for CRCN/ISFP (researcher) positions at Centre Inria de Lyon, and
• for a MCf (assistant professor) position, sect. 61, at Université de Lorraine.

11.3.1 Productions (articles, videos, podcasts, serious games, ...)

11.3.2 Participation in Live events

Participation in trade shows for the presentation of our eMob-Twin technologies:

• Tech&Fest
  February 2024, Alpexpo, Grenoble: A major national event aimed at bringing together innovative companies from the Auvergne-Rhône-Alpes region and highlighting key players in the technology and entrepreneurial ecosystem.
• Drive-to-Zero
  June 2024, Hippodrome de Longchamp, Paris: A European event bringing together public and private decision-makers committed to zero-carbon mobility.

International journals

• 6 articleM.Maria Castaldo, P.Paolo Frasca, T.Tommaso Venturini and F.Floriana Gargiulo. Fake views removal and popularity on YouTube.Scientific Reports141July 2024, 15443HALDOIback to text
• 7 articleJ.-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.ALEA : Latin American Journal of Probability and Mathematical Statistics212024, 1375-1405HALDOIback to text
• 8 articleJ.Jonas Gava, T.Tarso Kraemer Sarzi Sartori, A.Alex Hanneman, R.Rafael Garibotti, F. G.Fernando Gehm Moraes, 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 on Resource-constrained Devices under Neutron Radiation.IEEE Transactions on Nuclear Science718August 2024, 1511-1519HALDOIback to text
• 9 articleI.Ilhem Gharbi, F.Fadoua Taia-Alaoui, H.Hassen Fourati, N.Nicolas Vuillerme and Z.Zebo Zhou. Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review.Sensors2422November 2024, 219–252HALDOIback to text
• 10 articleC.Chuan Huang, G.Gustaf Hendeby, H.Hassen Fourati, C.Christophe Prieur and I.Isaac Skog. MAINS: A Magnetic Field Aided Inertial Navigation System for Indoor Positioning.IEEE Sensors Journal249May 2024, 15156-15166HALDOIback to text
• 11 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
• 12 articleT.Thomas Lefebvre, H.Hélène Brogniez, I.Ilhem Gharbi, L.Laura Hermozo, D.Dominique Bouniol, F.Florent Dralet and R.Rémy Roca. Characterization of convective systems dynamics and microphysics using time-delayed tandem microwave radiometers.IEEE Transactions on Geoscience and Remote Sensing2024. In press. HAL
• 13 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 Vehicles291January 2024, 2262-2275HALDOIback to text
• 14 articleC.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 Multiagent Systems.IEEE Transactions on Automatic Control6911November 2024, 7600-7613HALDOIback to text
• 15 articleU.Ujjwal Pratap, C.Carlos Canudas de Wit and F.Federica Garin. Optimizing urban mobility for saving lives and economy during an epidemic outbreak, with application to Grenoble.IEEE Transactions on Control Systems Technology331January 2025, 288-303HALDOIback to text
• 16 articleS. M.Shelton Mthunzi Sithole, W.Walter Musakwa, J.James Magidi and A. Y.Alain Y Kibangou. Characterising landcover changes and urban sprawl using geospatial techniques and landscape metrics in Bulawayo, Zimbabwe (1984–2022).Heliyon1062024, e27275HALDOI

International peer-reviewed conferences

• 17 inproceedingsM.Manuel Campero Jurado, C.Carlos Canudas de Wit, G.Giovanni de Nunzio and R.Rémi Mourgues. A General Graph-based Optimization Framework for Improving Safety and Comfort in Cycling Networks.ITSC 2024 - 27th IEEE International Conference on Intelligent Transportation SystemsEdmonton, CanadaIEEESeptember 2024, 1-6HALback to text
• 18 inproceedingsC.Carlos Canudas de Wit and B.Baptiste Lefeuvre. eMob-Twin: A Digital Twin for Electromobility Flexibility Forecast ⋆.IFAC-PapersOnLineCTS 2024 - 17th IFAC Symposium on Control of Transportation Systems5810Ayia Napa, Cyprus2024, 29-36HALDOIback to text
• 19 inproceedingsN. P.Nomfundo P. Cele, A.Alain Kibangou and W.Walter Musakwa. Machine Learning Analysis of Informal Minibus Taxi Driving.MAIH 2024 - International Conference on Mobility, Artificial Intelligence and HealthMarrakech, Morocco2024, 1-6HALback to text
• 20 inproceedingsG.Guillaume Gasnier and C.Carlos Canudas de Wit. Competitive Optimal Pricing Strategies for Charging Station Operators in the Frequency Containment Reserves Market.CDC 2024 - 63rd IEEE Conference on Decision and ControlMilan, ItalyIEEE2024, 1-8HALback to textback to text
• 21 inproceedingsG.Guillaume Gasnier and C.Carlos Canudas de Wit. Optimal Pricing Strategies for Charging Stations in the Frequency Containment Reserves Market for Vehicle-to-Grid Integration.22nd European Control Conference (ECC)ECC 2024 - 22nd European Control ConferenceStockholm, Sweden2024, 1-8HALback to textback to textback to text
• 22 inproceedingsA.Alain Kibangou and R.Retsepile Kalaoane. Optimal Decision-Making in a Captive Users Context.CCA 2024 - 3rd Control Conference Africa5825Balaclava, MauritiusElsevier2024, 144-149HALDOIback to text
• 23 inproceedingsR.Raoul Prisant, L.Luca Cataldo, F.Francesca Ceragioli and P.Paolo Frasca. Disagreement, Limit Cycles and Zeno Solutions in Continuous Opinion Dynamics with Binary Actions.https://ecc24.euca-ecc.org/ECC 2024 - 22nd European Control ConferenceStockholm, SwedenIEEEJuly 2024, 2362-2367HALDOIback to text
• 24 inproceedingsR.Raoul Prisant, F.Federica Garin and P.Paolo Frasca. Opinion dynamics on signed graphs and graphons: Beyond the piece-wise constant case.CDC 2024 - 63rd IEEE Conference on Decision and ControlMilan, ItalyIEEE2024, 1-6HALback to text
• 25 inproceedingsG.Ghadeer Shaaban, H.Hassen Fourati, C.Christophe Prieur and A.Alain Kibangou. Q-Learning-Based Noise Covariance Matrices Adaptation in Kalman Filter for Inertial Navigation.IFAC-PapersOnLine, Volume 58, Issue 21, 2024, Pages 96-101,MICNON 2024 - 4th IFAC Conference on Modelling, Identification and Control of Nonlinear Systems5821Lyon, France2024, 96-101HALDOIback to text
• 26 inproceedingsT.Tommaso Toso, F.Francesca Parise, P.Paolo Frasca and A.Alain Kibangou. On the impact of coordinated fleets size on traffic efficiency.63rd IEEE Conference on Decision and Control (CDC)CDC 2024 - 63rd IEEE Conference on Decision and ControlMilan, ItalyIEEE2024, 1-6HALback to text
• 27 inproceedingsR.Renato Vizuete, P.Paolo Frasca and E.Elena Panteley. SIS Epidemics on Open Networks: A Replacement-Based Approximation.ECC 2024 - 22nd European Control ConferenceStockholm, SwedenIEEEMarch 2024, 1602-1608HALDOIback to text

Scientific books

• 28 bookR.Romain Postoyan, P.Paolo Frasca, E.Elena Panteley and L.Luca Zaccarian, eds. Hybrid and networked dynamical systems: Modeling, Analysis and Control.493Lecture Notes in Control and Information SciencesSpringer Nature SwitzerlandMarch 2024, XVII, 328HALDOIback to text

Scientific book chapters

• 29 inbookR.Renato Vizuete, C.Charles Monnoyer de Galland, P.Paolo Frasca, E.Elena Panteley and J.Julien Hendrickx. Trends and Questions in Open Multi-agent Systems.493Hybrid and Networked Dynamical SystemsLecture Notes in Control and Information SciencesSpringer Nature SwitzerlandMarch 2024, 219-252HALDOIback to text

Doctoral dissertations and habilitation theses

• 30 thesisP.Paolo Frasca. Distributed and scalable methods for the analysis and control of networks of dynamical agents.Université de GrenobleJuly 2024HALback to text
• 31 thesisT.Tommaso Toso. Dynamics and games for information-aware routing in traffic networks.Université Grenoble Alpes [2020-....]October 2024HALback to text

Reports & preprints

• 32 miscS.Sébastien Fueyo and C.Carlos Canudas de Wit. From Microscopic Driver Models to Macroscopic PDEs in Ring Road Traffic Dynamics.2024HALback to text
• 33 miscS.Sébastien Fueyo. Hale-Silkowski criterion for exact controllability of difference delay systems and 1-D hyperbolic PDEs.December 2024HAL
• 34 miscF.Federica Garin, P.Paolo Frasca and R.Renato Vizuete. Corrections to and Improvements on Results from "The Laplacian Spectrum of Large Graphs Sampled from Graphons".July 2024HALback to text
• 35 miscS.Samuele Zoboli, D.Daniele Astolfi, V.Vincent Andrieu, G.Giacomo Casadei and L.Luca Zaccarian. Incremental stabilization and multi-agent synchronization of discrete-time nonlinear systems.2024HALback to text

Other scientific publications

• 36 inproceedingsM.Manuel Campero Jurado, C.Carlos Canudas de Wit and G.Giovanni de Nunzio. Maximizing Safety in Cycling Networks through Optimal and Gradual Upgrading.TRC-30 2024 - 30th Anniversary of Transportation Research: Part CHeraklion, Greece2024, 1-4HALback to text