Carlos Canudas De Wit

French National Centre for Scientific Research, Lutetia Parisorum, Île-de-France, France

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Publications (164)105.08 Total impact

  • Enrico Lovisari · Carlos Canudas De Wit · Alain Y. Kibangou

    No preview · Article · Dec 2015
  • Enrico Lovisari · Carlos Canudas De Wit · Alain Y. Kibangou

    No preview · Article · Dec 2015
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    Full-text · Article · Dec 2015
  • Pietro Grandinetti · Federica Garin · Carlos Canudas De Wit

    No preview · Article · Dec 2015
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    ABSTRACT: The problem of eco-driving is analyzed for an urban traffic network in presence of signalized intersections. It is assumed that the traffic light timings are known and available to the vehicles via infrastructure-to-vehicle communication. This work provides a solution to the energy consumption minimization while traveling through a sequence of signalized intersections and always catching a green light. The optimal- control problem is non-convex because of the constraints coming from the traffic lights; therefore, a sub-optimal strategy to restore the convexity and solve the problem is proposed. Firstly, a pruning algorithm aims at reducing the optimization domain by considering only the portions of the traffic light’s green phases that allow to drive in compliance with the city speed limits. Then, a graph is created in the feasible region in order to approximate the energy consumption associated with each available path in the driving horizon. Lastly, after the problem convexity is recovered, a simple optimization problem is solved on the selected path to calculate the optimal crossing times at each intersection. The optimal speeds are then suggested to the driver. The proposed sub-optimal strategy is compared with the optimal solution provided by dynamic programming for validation purposes. It is also shown that the low computational load of the presented approach enables robustness properties and results very appealing for online use.
    Full-text · Article · Oct 2015 · International Journal of Robust and Nonlinear Control
  • Enrico Lovisari · Carlos Canudas De Wit · Alain Y. Kibangou

    No preview · Article · Oct 2015
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    Enrico Lovisari · Carlos Canudas de Wit · Alain Kibangou
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    ABSTRACT: This paper addresses the two problems of flow and density reconstruction in Road Transportation Networks with heterogeneous information sources and cost effective sensor placement. Following standard macroscopic modeling approaches, the network is partitioned in cells, whose density of vehicles changes dynamically in time according to first order conservation laws. The first problem is to estimate the flow and the density of vehicles using two sources of information, namely standard fixed sensors, precise but expensive, and Floating Car Data, less precise due to low penetration rates, but already available on most of the main roads. A data fusion algorithm is proposed to merge the two sources of information for observing density and flow of vehicles. The second problem is to place the sensors in the network by trading off between cost and performance. A relaxation of the problem is proposed based on the concept of Virtual Variances. The efficiency of the proposed strategies is shown on a synthetic regular grid and in the real world scenario of Rocade Sud in Grenoble, France, a ring road 10.5 km long.
    Full-text · Article · Jul 2015
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    Pietro Grandinetti · Carlos Canudas De Wit · Federica Garin

    Preview · Article · Jul 2015
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    ABSTRACT: The start from the Ocean House was something marvelous to see. The drivers stormed and scolded, the women shrieked and cried, wheels locked at intervals of perhaps ten minutes. Occasionally, too, a carriage would capsize, and be hauled over to the fence for repairs... [It was] like a huge funeral procession, crawling along at a snail's pace. It was a feat to get to the city at all.
    Preview · Article · Jun 2015 · IEEE control systems
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    Dominik Pisarski · Carlos Canudas de Wit
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    ABSTRACT: In this paper, we study the problem of optimal balancing of vehicle density in the freeway traffic. The optimization is performed in a distributed manner by utilizing the controllability properties of the freeway network represented by the Cell Transmission Model. By using these properties, we identify the subsystems to be controlled by local ramp meters. The optimization problem is then formulated as a noncooperative Nash game that is solved by decomposing it into a set of two-players hierarchical and competitive games. The process of optimization employs the communication channels matching the switching structure of system interconnectivity. By defining the internal model for the boundary flows, local optimal control problems are efficiently solved by utilizing the method of Linear Quadratic Regulator. The developed control strategy is tested via numerical simulations in two scenarios for uniformly congested and transient traffic.
    Preview · Article · May 2015 · IEEE Transactions on Control of Network Systems
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    Giovanni De · Carlos Canudas De Wit · Philippe Moulin
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    ABSTRACT: The evaluation of the benefits of an Eco-Driving assistance system is carried out in the urban environment in presence of traffic lights. The traffic evolution is modeled macroscopically with the Urban Variable-Length Model [1] in a variable speed limits framework. Under the assumption of equal boundary flows, the vehicles in a road section dispose themselves according to well defined equilibrium conditions which are dependent on the traveling speed in the free-flow part of the section. Given certain initial traffic conditions, an optimal speed limit for the section can be found in order to drive the system to an efficient equilibrium state. Further analysis of the equilibrium conditions and the stability properties of the system is conducted in this work. The system is proved to be controllable, under the working hypotheses, and a controller is designed to simulate the response of the drivers compliant to the eco-speed advisory. A sub-optimal control strategy is finally proposed also in the case of unequal boundary flows.
    Full-text · Conference Paper · Dec 2014
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    Giovanni De · Carlos Canudas De Wit · Philippe Moulin
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    ABSTRACT: The problem of traveling at maximum energy efficiency (Eco-Driving) is addressed for urban traffic networks at macroscopic level. The scope of this paper is the analysis of the steady-state behavior of the system, given certain boundary flows conditions fixed by traffic lights timings, and in presence of a traffic control policy based on variable speed limits. The formal study is carried out on a two-cells variable length model adapted to the urban setup from previous works on highway traffic [1][2]. Informative traffic metrics, aimed at assessing traffic and vehicles performance in terms of traveling time, infrastructure utilization and energy consumption, are then defined and adapted to the new macroscopic traffic model. If congestion in a road section does not spill back or vanish, the system is stable and many different equilibrium points can be reached via variable speed limits. Efficient operation points and traffic conditions are identified as a trade-off between optimization of global traffic energy consumption, traveling time and infrastructure utilization.
    Full-text · Conference Paper · Jun 2014
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    Fabio Morbidi · Luis Leon Ojeda · Carlos Canudas de Wit · Iker Bellicot
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    ABSTRACT: In this paper we present a robust mode selector for the uncertain graph-constrained Switching Mode Model (SMM), which we use to describe the highway traffic density evolution. Assuming an uncertain speed of the congestion wave, the proposed selector relies on a transition digraph suitably incorporating the present and historical statistical traffic information, to determine the most probable current mode of the SMM. Its effectiveness is demonstrated on the problem of traffic density reconstruction via a switching observer, in an instrumented 2.2 km highway section of Grenoble south ring in France.
    Preview · Conference Paper · Jun 2014
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    Ruggero Fabbiano · Carlos Canudas de Wit · Federica Garin
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    ABSTRACT: We consider the problem of localizing the source of a diffusion process. The source is supposed to be isotropic, and several sensors, equipped on a vehicle moving without position information, provide pointwise measures of the quantity being emitted. The solution we propose is based on computing the gradient–and higher-order derivatives such as the Hessian–from Poisson integrals: in opposition to other solutions previously proposed, this computation does neither require specific knowledge of the solution of the diffusion process, nor the use of probing signals, but only exploits properties of the PDE describing the diffusion process. The theoretical results are illustrated by simulations.
    Preview · Article · Jun 2014 · Automatica
  • Ruggero Fabbiano · Carlos Canudas de Wit · Federica Garin
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    ABSTRACT: We consider a group of autonomous communicating sensors, and our objective is to steer the group, with a low information exchange, towards the isotropic source of a diffusion process in steady-state. We suppose the graph describing the communication links between sensors to have a time-invariant ring-topology. Each sensor, which has no position information, takes pointwise measurements of the quantity of interest, and is able to measure the bearing angle with respect to its neighbours. We solve the source-localisation task via a gradient-ascent technique based on a distributed implementation of Poisson integral formula; our approach is based on a twofold control law, which is able to bring and keep the set of sensors on a circular equispaced formation while seeking the source.
    No preview · Conference Paper · Jun 2014
  • Nicolas Cardoso De Castro · Federica Garin · Carlos Canudas De Wit
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    ABSTRACT: Energy efficiency is a major issue in wireless networked control systems. In this chapter, we address this problem by considering more specifically the energy-consumption of the radio chip of sensor nodes. There exists an interesting and rich literature on the topics of intermittent and event-based control, allowing to turn off the sensor's radio for longer time than what is possible with a classical periodic sampling. Such a literature only addresses policies using two radio-modes (Transmitting and Sleep), while this contribution aims at exploiting the use of various radio-modes, both transmitting modes having different transmission power, where increased power results in better transmission quality (fewer errors) but higher energy cost, and non-transmitting modes which correspond to switching off only some components of the chip, and result in having higher energy cost than Sleep but faster/less costly transition to transmission. We propose an event-based radio-mode switching policy to perform a trade-off between energy saving and performance of the control application. The switching policy is derived jointly with the feedback law using a switched model taking into account control and communication. We compute the optimal joint switching policy and feedback law using Dynamic Programming and we illustrate the results in simulations.
    No preview · Book · Jan 2014
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    ABSTRACT: This work addresses the problem of finding energy-optimal velocity profiles for a vehicle in an urban traffic network. Assuming communication between infrastructure and vehicles (I2V) and a complete knowledge of the upcoming traffic lights timings, a preliminary velocity pruning algorithm is proposed in order to identify the feasible region a vehicle may travel along in compliance with city speed limits. Then, a graph discretizing approach is utilized for advanced selection, among the feasible “green windows”, of the optimal ones in terms of energy consumption. Finally, a velocity trajectory is advised, which will be tracked by the driver-in-the-loop in order to pass through the signalized intersections without stopping. The proposed eco-driving assistance algorithm results are compared to the optimal solution provided by the Dynamic Programming, in order to prove not only the effectiveness but also its capability to be employed online due to its low computational load.
    Full-text · Conference Paper · Dec 2013
  • Luis Ramon Leon Ojeda · Alain Y. Kibangou · Carlos Canudas De Wit
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    ABSTRACT: Traffic forecasting is considered nowadays as one of the most important traffic management techniques on road networks. To provide suitable control strategies and advanced traveler information, which improve traffic performance, a continuous short-term prediction is a significant requirement. In this paper, we propose a new approach for travel time forecasting between two points of interest of a given highway divided in nodes and links. Since nodes and links have distinct characteristics, two different prediction methods are proposed. The resulting predicted travel time is then computed as the sum of predicted travel times in nodes with those in links. An adaptive Kalman filtering approach is considered for predicting sojourn time in nodes and flows at boundaries of links. Inside links, divided in cells for improving resolution, a deterministic observer is used for computing unmeasured densities. The performance of the proposed method is evaluated by using data of the Grenoble south ring, a case study of the NoE Hycon2.
    No preview · Conference Paper · Jul 2013
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    L.L. Ojeda · A.Y. Kibangou · Carlos Canudas de Wit
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    ABSTRACT: Given the importance of continuous traffic flow forecasting in most of Intelligent Transportation Systems (ITS) applications, where every new traffic data become available in every few minutes or seconds, the main objective of this study is to perform a multi-step ahead traffic flow forecasting that can meet a trade-off between accuracy, low computational load, and limited memory capacity. To this aim, based on adaptive Kalman filtering theory, two forecasting approaches are proposed. We suggest solving a multi-step ahead prediction problem as a filtering one by considering pseudo-observations coming from the averaged historical flow or the output of other predictors in the literature. For taking into account the stochastic modeling of the process and the current measurements we resort to an adaptive scheme. The proposed forecasting methods are evaluated by using measurements of the Grenoble south ring.
    Preview · Conference Paper · Jun 2013
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    ABSTRACT: This document is a preliminary version of the working report concerning the work packages 5.3 and 5.4 of the project VolHand 09 VTT 14, that are in charge to the Gipsa-Lab. In this working report, authors introduce the general architecture used to simulate the Electronic Power Steering (EPS) system. In this rst part, the models, the controller and the observer used for the simulation are introduced. Then, the methodology used to adapt the model to a driver with reduced mobility is described in detail. Finally, the experimental validation of this general architecture is proposed. Section 2 refers to the work-package Gipsa-Comp. Section 3 concerns the work-package Gipsa-Obs. Section 4 is dedicated to the work-package Gipsa-Booster. The work-package Gipsa-Tune is under development.
    Preview · Article · Mar 2013

Publication Stats

7k Citations
105.08 Total Impact Points

Institutions

  • 1995-2014
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
  • 2000-2001
    • University of California, Berkeley
      • Department of Mechanical Engineering
      Berkeley, MO, United States
    • Grenoble Institute of Technology
      • LIG - Computer Science Laboratory
      Grenoble, Rhône-Alpes, France
  • 1999-2000
    • Georgia Institute of Technology
      • School of Aerospace Engineering
      Atlanta, GA, United States
  • 1994-1996
    • Universiteit Twente
      • Department of Applied Mathematics
      Enschede, Overijssel, Netherlands
    • Australian National University
      Canberra, Australian Capital Territory, Australia