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  • 1351.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, SE-10044 Stockholm, Sweden..
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, SE-10044 Stockholm, Sweden..
    Parameter Privacy versus Control Performance: Fisher Information Regularized Control2020In: 2020 AMERICAN CONTROL CONFERENCE (ACC), IEEE , 2020, p. 1259-1265Conference paper (Refereed)
    Abstract [en]

    This article introduces and solves a new privacy-related optimization problem for cyber-physical systems where an adversary tries to learn the system dynamics. In the context of linear quadratic systems, we consider the problem of achieving a small cost while balancing the need for keeping knowledge about the model's parameters private. To this end, we formulate a Fisher information regularized version of the linear quadratic regulator with cheap cost. Here the control operator is allowed to not only control the plant but also mask its state by injecting further noise. Within the class of linear policies with additive noise, we solve this problem and show that the optimal noise distribution is Gaussian with state dependent covariance. Next, we prove that the optimal linear feedback law is the same as without regularization. Finally, to motivate our proposed scheme, we formulate for scalar systems an equivalent maximin problem for the worst-case scenario in which the adversary has full knowledge of all other inputs and outputs. Here, our policies are maximin optimal with respect to maximizing the variance over all asymptotically unbiased estimators.

  • 1352.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Regret Lower Bounds for Unbiased Adaptive Control of Linear Quadratic Regulators2020In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 4, no 3, p. 785-790Article in journal (Refereed)
    Abstract [en]

    We present lower bounds for the regret of adaptive control of the linear quadratic regulator. These are given in terms of problem specific expected regret lower bounds valid for unbiased policies linear in the state. Our approach is based on the insight that the adaptive control problem can, given our assumptions, be reduced to a sequential estimation problem. This enables the use of the Cramer-Rao information inequality which yields a scaling limit lower bound of logarithmic order. The bound features both information-theoretic and control-theoretic quantities. By leveraging existing results, we are able to show that the bound is tight in a special case.

  • 1353.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Resource Constrained Sensor Attacks by Minimizing Fisher Information2021In: 2021 American control conference (ACC), Institute of Electrical and Electronics Engineers Inc. , 2021, p. 4580-4585, article id 9482865Conference paper (Refereed)
    Abstract [en]

    We analyze the impact of sensor attacks on a linear state estimation problem subject to variance and sparsity constraints. We show that the maximum impact in a leader-follower game where the attacker first chooses the distribution of an adversarial perturbation and the defender follows by choosing an estimator is characterized by a minimum Fisher information principle. In general, this is a nonlinear variational problem, but we show that it can be reduced to a finite-dimensional mixed integer SDP. Alternatively, the proposed solution can be seen as a lower bound on the maximum impact for a game in which the defender plays first.

  • 1354.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Matni, Nikolai
    University of Pennsylvania, University of Pennsylvania.
    Single Trajectory Nonparametric Learning of Nonlinear Dynamics2022In: Proceedings of 35th Conference on Learning Theory, COLT 2022, ML Research Press , 2022, p. 3333-3364Conference paper (Refereed)
    Abstract [en]

    Given a single trajectory of a dynamical system, we analyze the performance of the nonparametric least squares estimator (LSE). More precisely, we give nonasymptotic expected l2-distance bounds between the LSE and the true regression function, where expectation is evaluated on a fresh, counterfactual, trajectory. We leverage recently developed information-theoretic methods to establish the optimality of the LSE for nonparametric hypotheses classes in terms of supremum norm metric entropy and a subgaussian parameter. Next, we relate this subgaussian parameter to the stability of the underlying process using notions from dynamical systems theory. When combined, these developments lead to rate-optimal error bounds that scale as T−1/(2+q) for suitably stable processes and hypothesis classes with metric entropy growth of order δ−q. Here, T is the length of the observed trajectory, δ ∈ R+ is the packing granularity and q ∈ (0, 2) is a complexity term. Finally, we specialize our results to a number of scenarios of practical interest, such as Lipschitz dynamics, generalized linear models, and dynamics described by functions in certain classes of Reproducing Kernel Hilbert Spaces (RKHS).

  • 1355.
    Ziemann, Ingvar
    et al.
    University of Pennsylvania, University of Pennsylvania.
    Tsiamis, Anastasios
    ETH Zürich, Eth Zürich.
    Lee, Bruce
    University of Pennsylvania, University of Pennsylvania.
    Jedra, Yassir
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Matni, Nikolai
    University of Pennsylvania, University of Pennsylvania.
    Pappas, George J.
    University of Pennsylvania, University of Pennsylvania.
    A Tutorial on the Non-Asymptotic Theory of System Identification2023In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 8921-8939Conference paper (Refereed)
    Abstract [en]

    This tutorial serves as an introduction to recently developed non-asymptotic methods in the theory of-mainly linear-system identification. We emphasize tools we deem particularly useful for a range of problems in this domain, such as the covering technique, the Hanson-Wright Inequality and the method of self-normalized martingales. We then employ these tools to give streamlined proofs of the performance of various least-squares based estimators for identifying the parameters in autoregressive models. We conclude by sketching out how the ideas presented herein can be extended to certain nonlinear identification problems. Note: For reasons of space, proofs have been omitted in this version and are available in an online version: https://arxiv.org/abs/2309.03873.

  • 1356.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tsiamis, Anastasios
    Swiss Fed Inst Technol, Automat Control Lab, Zurich, Switzerland..
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Matni, Nikolai
    Univ Penn, Dept Elect & Syst Engn, Philadelphia, PA 19104 USA..
    How are policy gradient methods affected by the limits of control?2022In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 5992-5999Conference paper (Refereed)
    Abstract [en]

    We study stochastic policy gradient methods from the perspective of control-theoretic limitations. Our main result is that ill-conditioned linear systems in the sense of Doyle inevitably lead to noisy gradient estimates. We also give an example of a class of stable systems in which policy gradient methods suffer from the curse of dimensionality. Finally, we show how our results extend to partially observed systems.

  • 1357.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tu, Stephen
    Robotics at Google, Robotics at Google.
    Learning with little mixing2022In: Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Neural information processing systems foundation , 2022Conference paper (Refereed)
    Abstract [en]

    We study square loss in a realizable time-series framework with martingale difference noise. Our main result is a fast rate excess risk bound which shows that whenever a trajectory hypercontractivity condition holds, the risk of the least-squares estimator on dependent data matches the iid rate order-wise after a burn-in time. In comparison, many existing results in learning from dependent data have rates where the effective sample size is deflated by a factor of the mixing-time of the underlying process, even after the burn-in time. Furthermore, our results allow the covariate process to exhibit long range correlations which are substantially weaker than geometric ergodicity. We call this phenomenon learning with little mixing, and present several examples for when it occurs: bounded function classes for which the L2 and L2+ε norms are equivalent, ergodic finite state Markov chains, various parametric models, and a broad family of infinite dimensional ℓ2(N) ellipsoids. By instantiating our main result to system identification of nonlinear dynamics with generalized linear model transitions, we obtain a nearly minimax optimal excess risk bound after only a polynomial burn-in time.

  • 1358.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Zhou, Yishao
    Stockholm Univ, Dept Math, SE-10691 Stockholm, Sweden..
    Model Reduction of Semistable Distributed Parameter Systems2019In: Proceedings 2019 18th European Control Conference (ECC), IEEE , 2019, p. 1944-1950Conference paper (Refereed)
    Abstract [en]

    The model reduction problem for semistable infinite-dimensional control systems is studied in this paper. In relation to these systems, we study an object we call the semistability Gramian, which serves as a generalization of the ordinary controllability Gramian valid for semistable systems. This Gramian is then given geometric as well as algebraic characterization via a Lyapunov equation. We then proceed to show that under a commutativity assumption relating the original and reduced systems, and as long as the semistability is preserved, we may derive a priori error formulas in H-2-norm in terms of the trace of this Gramian.

  • 1359.
    Ziemann, Ingvar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Ziemann, Volker
    Uppsala Univ, S-75120 Uppsala, Sweden..
    Noninvasively improving the orbit-response matrix while continuously correcting the orbit2021In: Physical Review Accelerators and Beams, E-ISSN 2469-9888, Vol. 24, no 7, article id 072804Article in journal (Refereed)
    Abstract [en]

    Based on continuously recorded beam positions and corrector excitations from, for example, a closedorbit feedback system we describe an algorithm that continuously updates an estimate of the orbit response matrix. The speed of convergence can be increased by adding very small perturbations, so-called dither, to the corrector excitations. Estimates for the rate of convergence and the asymptotically achievable accuracies are provided.

  • 1360.
    Zolich, Artur
    et al.
    Norwegian Univ Sci & Technol, Dept Engn Cybernet, NTNU, Ctr Autonomous Marine Operat & Syst NTNU AMOS, Trondheim, Norway..
    Palma, David
    NTNU, Dept Informat Secur & Commun Technol, Trondheim, Norway..
    Kansanen, Kimmo
    NTNU, Dept Elect Syst, Trondheim, Norway..
    Fjortoft, Kay
    SINTEF Ocean, Trondheim, Norway..
    Sousa, Joao
    Univ Porto, Dept Elect & Comp Engn, Porto, Portugal..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. Norwegian Univ Sci & Technol, Dept Engn Cybernet, NTNU, Ctr Autonomous Marine Operat & Syst NTNU AMOS, Trondheim, Norway.;KTH Royal Inst Technol, Sch Elect Engn, Stockholm, Sweden..
    Jiang, Yuming
    NTNU, Dept Informat Secur & Commun Technol, Trondheim, Norway..
    Dong, Hefeng
    NTNU, Dept Elect Syst, Trondheim, Norway..
    Johansen, Tor A.
    Norwegian Univ Sci & Technol, Dept Engn Cybernet, NTNU, Ctr Autonomous Marine Operat & Syst NTNU AMOS, Trondheim, Norway..
    Survey on Communication and Networks for Autonomous Marine Systems2019In: Journal of Intelligent and Robotic Systems, ISSN 0921-0296, E-ISSN 1573-0409, Vol. 95, no 3-4, p. 789-813Article in journal (Refereed)
    Abstract [en]

    The rapid development of autonomous systems and Information and Communications Technologies (ICT) create new opportunities for maritime activities. Existing autonomous systems are becoming more powerful and utilise the capabilities of several types of devices such as Autonomous Underwater Vehicles (AUVs), Unmanned Surface Vehicles (USVs) - sometimes referred as Autonomous Surface Vehicles (ASVs) -, Unmanned Aerial Vehicles (UAVs), moored and drifting systems and, recently emerging, autonomous vessels. Their importance in providing new services in maritime environments is undeniable and the opportunity for coordinated and interconnected operations is clear. However, continuous wide integration of various technologies in maritime environments still faces many challenges. Operations may take place in remote locations, so that dependence on third-party infrastructures such as satellite communication or terrestrial communication systems must be expected. The reliability, performance, availability, and cost of such systems are important issues that need to be tackled. This work reviews the major advancements on state-of-the-art autonomous maritime vehicles and systems, which are used in several different scenarios, from scientific research to transportation. Moreover, the paper highlights how available technologies can be composed in order to efficiently and effectively operate in maritime environments. Highlights of the trade-off between autonomy and communication requirements are provided and followed by an overview of promising communication and networking technologies that could encourage the integration of autonomous systems in maritime scenarios.

  • 1361.
    Åstrand, Max
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Short-term Underground Mine Scheduling: An Industrial Application of Constraint Programming2021Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The mining industry is facing a surge in automation in the pursuit of safe and profitable operations. As the excavation process is increasingly automated, today's mining companies seek to optimize the coordination of the now automated mining activities. This coordination is called short-term mine scheduling, and it is the process of allocating resources and determining feasible start and end times for the upcoming mining activities. Unfortunately, current industrial practice relies heavily on manual labor, making the performance critically dependent on the expertise of the individual scheduler. In this thesis, we study how to automate the short-term mine scheduling process to increase the efficiency in a vital part of the underground mine planning chain. 

    First, the short-term underground mine scheduling problem is detailed, and the surrounding operational context is clarified. Central aspects of the excavation process are shown to be adequately described by a scheduling abstraction known as a hybrid flow shop. We demonstrate that some popular mine production methods can be considered rich variants of a k-stage hybrid flow shop exhibiting a mix of interruptible and uninterruptible activities, sequence-dependent setup times, and sharing of machines between stages. 

    An approach based on constraint programming is then presented that can be used for short-term scheduling in underground mines. For mines that have vast underground road networks, it is important to consider the travel times needed for the mobile machines between subsequent activities. The proposed extension of the first approach can unfortunately only solve small instances in reasonable computation times. To solve industrially relevant problem sizes, we introduce a second approach. The second approach does not solve the interruptible scheduling problem directly; instead, it solves a related uninterruptible problem and transforms the solution back to the original time domain. It is significantly faster than the first approach and can be used to solve larger instances, even when including travel times. The second approach is also extended to support more general mining scenarios that cannot be described as hybrid flow shops.

    To improve the quality of the schedules, we introduce a domain-specific neighborhood definition that is used in large neighborhood search. Initially, different fixed neighborhood sizes are investigated. Upon observing that there is no clear dominant strategy, we propose an algorithm for dynamically adjusting the size of the explored neighborhoods. The constructed schedules are improved rapidly using the proposed algorithm, which also introduces local optimality properties that are beneficial when it comes to industrial acceptance. For all models and methods presented in this thesis, we perform extensive numerical evaluations on problem instances derived from operational underground mines.

    This thesis is concluded by presenting practical experiences from automating the short-term scheduling process in underground mines. Assumptions and design choices are motivated by earlier experiences from using simpler scheduling algorithms. Finally, senior mine schedulers from two different mine sites assess the real-life applicability of the final scheduling approach.

    Download full text (pdf)
    Short-term Underground Mine Scheduling - An Industrial Application of Constraint Programming
  • 1362.
    Åstrand, Max
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Short-term Underground Mine Scheduling: Constraint Programming in an Industrial Application2018Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The operational performance of an underground mine depends critically on how the production is scheduled. Increasingly advanced methods are used to create optimized long-term plans, and simultaneously the actual excavation is getting more and more automated. Therefore, the mapping of long-term goals into tasks by manual short-term scheduling is becoming a limiting segment in the optimization chain. In this thesis we study automating the short-term mine scheduling process, and thus contribute to an important missing piece in the pursuit of autonomous mining.

    First, we clarify the fleet scheduling problem and the surrounding context. Based on this knowledge, we propose a flow shop that models the mine scheduling problem. A flow shop is a general abstract process formulation that captures the key properties of a scheduling problem without going into specific details. We argue that several popular mining methods can be modeled as a rich variant of a k-stage hybrid flow shop, where the flow shop includes a mix of interruptible and uninterruptible tasks, after-lags, machine unavailabilities, and sharing of machines between stages.

    Then, we propose a Constraint Programming approach to schedule the underground production fleet. We formalize the problem and present a model that can be used to solve it. The model is implemented and evaluated on instances representative of medium-sized underground mines.

    After that, we introduce travel times of the mobile machines to the scheduling problem. This acknowledges that underground road networks can span several hundreds of kilometers. With this addition, the initially proposed Constraint Programming model struggles with scaling to larger instances. Therefore, we introduce a second model. The second model does not solve the interruptible scheduling problem directly; instead, it solves a related uninterruptible problem and transforms the solution back to the original time domain. This model is significantly faster, and can solve instances representative of large-sized mines even when including travel times.

    Lastly, we focus on finding high-quality schedules by introducing Large Neighborhood Search. To do this, we present a domain-specific neighborhood definition based on relaxing variables corresponding to certain work areas. Variants of this neighborhood are evaluated in Large Neighborhood Search and compared to using only restarts. All methods and models in this thesis are evaluated on instances generated from an operational underground mine.

     

     

    Download full text (pdf)
    Short-term Underground Mine Scheduling - Constraint Programming in an Industrial Application - Lic. Åstrand
  • 1363.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). ABB Corporate Research, SE-722 26 Västerås, Sweden.
    Jakobsson, Erik
    Linköping University, SE-581 83 Linköping, Sweden.
    Lindfors, Martin
    Linköping University, SE-581 83 Linköping, Sweden.
    Svensson, John
    Linköping University, SE-581 83 Linköping, Sweden.
    A system for underground road condition monitoring2020In: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 30, no 3, p. 405-411Article in journal (Refereed)
    Abstract [en]

    Poor road conditions in underground mine tunnels can lead to decreased production efficiency and increased wear on production vehicles. A prototype system for road condition monitoring is presented in this paper to counteract this. The system consists of three components i.e. localization, road monitoring, and scheduling. The localization of vehicles is performed using a Rao-Blackwellized extended particle filter, combining vehicle mounted sensors with signal strengths of WiFi access points. Two methods for road monitoring are described: a Kalman filter used together with a model of the vehicle suspension system, and a relative condition measure based on the power spectral density. Lastly, a method for taking automatic action on an ill-conditioned road segment is proposed in the form of a rescheduling algorithm. The scheduling algorithm is based on the large neighborhood search and is used to integrate road service activities in the short-term production schedule while minimizing introduced production disturbances. The system is demonstrated on experimental data collected in a Swedish underground mine.

  • 1364.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Automation Solutions, ABB Corporate Research, Västerås, Sweden.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    A Neighborhood Selection Strategy for Production Scheduling using CP and LNS2020In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 1183-1186Conference paper (Refereed)
    Abstract [en]

    High-quality production scheduling is increasingly important in modern industry operations. We study a class of scheduling problems where jobs take place at predefined locations, as is common in mining, forestry and logistics. The proposed neighborhood selection algorithm is able to find high- quality solutions fast and guarantees that a globally optimal solution is eventually found. Preliminary results are promising.

  • 1365.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). ABB Corporate Research, Västerås, Sweden.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Feyzmahdavian, Hamid Reza
    ABB Corporate Research, Västerås, Sweden.
    Short-Term Scheduling of Production Fleets in Underground Mines Using CP-Based LNS2021In: Lecture Notes in Computer Science, Springer Nature , 2021, p. 365-382Conference paper (Refereed)
    Abstract [en]

    Coordinating the mobile production fleet in underground mines becomes increasingly important as the machines are more and more automated. We present a scheduling approach that applies to several of the most important production methods used in underground mines. Our algorithm combines constraint programming with a large neighborhood search strategy that dynamically adjusts the neighborhood size. The resulting algorithm is complete and able to rapidly improve constructed schedules in practice. In addition, it has important benefits when it comes to the acceptance of the approach in real-life operations. Our approach is evaluated on public and private industrial problem instances representing different mines and production methods. We find significant improvements over the current industrial practice.

  • 1366.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). ABB Corp Res, Control Optimizat & Analyt, Automat Solut, Vasteras, Sweden.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Greberg, J.
    Lulea Univ Technol, Dept Civil Environm & Nat Resources Engn, Div Min & Geotech Engn, Lulea, Sweden..
    Underground mine scheduling modelled as a flow shop: a review of relevant work and future challenges2018In: Journal of the Southern African Institute of Mining and Metallurgy, ISSN 2225-6253, E-ISSN 2411-9717, Vol. 118, no 12, p. 1265-1276Article, review/survey (Refereed)
    Abstract [en]

    Advanced planning and automation are increasingly important in modern mines. Sophisticated methods for long-term mine planning are often used, and the advent of autonomous machines makes the actual operation more predictable. However, the interface between these two timescales, i.e. the scheduling of the mobile production fleet, often limits the ability to operate mines at maximum profitability. We show how scheduling the production fleet in an underground mine can be modelled as a flow shop. A flow shop is a general abstract process formulation that captures the key properties of a scheduling problem without going into specific details. Thus, the flow shop enables mine scheduling to reap the benefits of scheduling research from other industries. We review recent results from the mining community and the flow shop community, and introduce scheduling methods used in these two fields. This work aims at providing value to researchers from the mining community who want to leverage their skill set, as well as to theoretical researchers by presenting the mining process as a potential application area. Lastly, we discuss the results, and outline some future challenges and opportunities facing the industry.

  • 1367.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). ABB Corporate Research Center, Västerås, Sweden.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Zanarini, A.
    Fleet scheduling in underground mines using constraint programming2018In: 15th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2018, Springer, 2018, Vol. 10848, p. 605-613Conference paper (Refereed)
    Abstract [en]

    The profitability of an underground mine is greatly affected by the scheduling of the mobile production fleet. Today, most mine operations are scheduled manually, which is a tedious and error-prone activity. In this contribution, we present and formalize the underground mine scheduling problem, and propose a CP-based model for solving it. The model is evaluated on instances generated from real data. The results are promising and show a potential for further extensions.

  • 1368.
    Åstrand, Max
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). ABB Corp Res, Västerås, Sweden..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Zanarini, Alessandro
    ABB Corp Res, Baden, Switzerland..
    Underground mine scheduling of mobile machines using Constraint Programming and Large Neighborhood Search2020In: Computers & Operations Research, ISSN 0305-0548, E-ISSN 1873-765X, Vol. 123, article id 105036Article in journal (Refereed)
    Abstract [en]

    Manual short-term scheduling in underground mines is a time-consuming and error-prone activity. In this work, we present a Constraint Programming approach capable of automating the short-term scheduling process in a cut-and-fill mine. The approach extends previous work by accounting for fleet travel times, and thus captures an important aspect of the real-world machine scheduling problem. We introduce two models: one that directly solves the original interruptible scheduling problem, and one that is based on solving a related uninterruptible scheduling problem and transforming its solution back to the original domain. Large Neighborhood Search is also employed with a domain-specific neighborhood definition that helps to find high-quality schedules faster. Problem instances derived from an operational mine are used to demonstrate the efficacy of our approach.

  • 1369.
    Ótão Pereira, Pedro Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Geometric Control of Thrust Propelled Systems2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis was motivated and inspired by the AEROWORKS project, a European research project, whose main goal was to deploy multiple heterogeneous unmanned aerial vehicles in environments where human intervention is restricted.In particular, this thesis focuses on control of aerial vehicles for the purposes of cargo transportation, an application of interest, for example, in inspection and maintenance of aging infrastructures.

    This thesis also focuses on control of multi-agent systems, where agents are required to accomplish some common goal, such as collaborating on transporting a common cargo. In the first part of this thesis, we focus on control of thrust-propelled systems.A thrust-propelled system is similar to a multi-rotor system, where a thrust input is available along some direction, which we can rotate by means of a torque input.In a first step, we develop controllers for the thrust-propelled system, by application of nonlinear control techniques.In a second and final step, we convert a physical system, by means of an appropriate change of coordinates, into the thrust-propelled system form, at which point we are able to leverage the controllers designed in the first step.Among the physical systems considered in this thesis, we highlight slung-load transportation, where a point-mass cargo is tethered to a single aerial vehicle, and slung-bar transportation, where a bar cargo is tethered to two aerial vehicles.Another key idea, exploited throughout this thesis, is that of geometric control, where one attempts to design controllers that are independent of the user choices.For example, when performing an experiment, a user picks a reference frame, and the application of a geometric controller is insensitive to that choice.On the contrary, a non-geometric controller yields different results depending on which frame is chosen.Experiments and simulations illustrate the performance of the proposed control strategies.

    In the second part of this thesis, we focus on global stabilization of mechanical systems, in contrast with the first part, where almost global and/or local stabilization sufficed.However, for non-contractible sets, which are pervasive throughout this thesis, a globally asymptotically stable equilibrium point does not exist under a continuous control law.In particular, we consider a rigid-body pendulum, which we wish to globally stabilize at some desired configuration.To accomplish the latter, we create a graph between several stabilizing continuous control laws, and switch among them so as to provide the desired equilibrium with a global region of attraction, which we validate in simulations.

    In the final part of this thesis, we consider a multi-agent system composed of rotation matrices, and we design controllers that guarantee asymptotic incomplete synchronization.In particular, we develop decentralized torque controllers for the agents, and when the directions to be synchronized are principal axes, we are able to propose torque control laws that do not require torque input in all bodies directions, but rather only in the body directions orthogonal to the respective principal axis.Simulations are then presented which illustrate the performance of the proposed control strategy.

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  • 1370.
    Ótão Pereira, Pedro Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Cortes, Jorge
    Univ Calif San Diego, Dept Mech & Aerosp Engn, San Diego, CA 92093 USA..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Aerial Slung-Load Position Tracking Under Unknown Wind Forces2021In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 66, no 9, p. 3952-3968Article in journal (Refereed)
    Abstract [en]

    We propose a dynamic controller for position tracking of a point-mass load attached to an omnidirectional aerial vehicle by means of a cable. Both the load and the aerial vehicle are subject to unknown wind forces. We model the dynamics of the slung-load system and put it into canonical form, i.e., a form which is independent of the system's physical parameters. Following a backstepping strategy, we design a dynamic control law for the canonical system that contains four estimators, since each of the two wind disturbances has two separate effects: an effect on the linear acceleration and another on the angular acceleration. Loosely speaking, the difference between the wind forces is an input-additive disturbance, while the wind force on the load is not, which makes removing the wind force on the load nontrivial. We identify conditions on the desired position trajectory and on the wind on the load, which guarantee that a well-defined equilibrium trajectory exists. The designed controller guarantees simultaneously that the latter trajectory is asymptotically tracked and the cable remains taut, provided that the system is initialized in a suitable set. Simulations illustrate our results.

  • 1371.
    Ótão Pereira, Pedro Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Cunha, Rita
    Univ Lisbon, Inst Robot & Syst Engn & Sci LARSyS, Inst Super Tecn, P-1049001 Lisbon, Portugal.;Univ Lisbon, Inst Super Tecn, Dept Elect Engn & Comp Sci, P-1049001 Lisbon, Portugal..
    Cabecinhas, David
    Univ Lisbon, Inst Robot & Syst Engn & Sci LARSyS, Inst Super Tecn, P-1049001 Lisbon, Portugal.;Univ Macau, Dept Elect & Comp Engn, Fac Sci & Technol, Macau, Peoples R China..
    Silvestre, Carlos
    Univ Lisbon, Inst Robot & Syst Engn & Sci LARSyS, Inst Super Tecn, P-1049001 Lisbon, Portugal.;Univ Macau, Dept Elect & Comp Engn, Fac Sci & Technol, Macau, Peoples R China..
    Oliveira, Paulo
    Univ Lisbon, Inst Robot & Syst Engn & Sci LARSyS, Inst Super Tecn, P-1049001 Lisbon, Portugal.;Univ Lisbon, Inst Super Tecn, Dept Mech Engn, P-1049001 Lisbon, Portugal..
    A 3-D Trailer Approach to Leader-Following Formation Control2020In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 28, no 6, p. 2292-2308Article in journal (Refereed)
    Abstract [en]

    A real-time 3-D trajectory planner for the leader-following formation control of autonomous vehicles is proposed. The planner relies on the definition of a trailer body whose hinge point is rigidly attached to the leader and assigns each follower to a distinct point of such a trailer. Convergence results for the trailer body reference frame are presented based on Lyapunov analysis, which guarantee that the planning can be independently implemented by n followers, with a common leader, as they asymptotically behave as n points of a unique trailer body. As such, the need for communication among followers is dispensable. The proposed strategy is divided into trajectory planning and trajectory tracking, the first problem being vehicle-independent. Experimental results obtained with quadrotor vehicles are presented, which demonstrate the richness and suitability of the planned trajectories.

  • 1372.
    Ótão Pereira, Pedro Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Lyapunov-based Generic Controller Design for Thrust-Propelled Underactuated Systems2016In: 2016 EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2016, p. 594-599Conference paper (Refereed)
    Abstract [en]

    We present a controller for an underactuated system which is driven by a one dimensional linear acceleration/thrust along a direction vector, by a time-varying gravity, and by the angular acceleration of the direction vector. We propose state and time-dependent control laws for the linear and angular accelerations that guarantee that the position of the system is steered to the origin. The proposed control law depends on (i) a bounded control law for a double integrator system; and (ii) on a Lyapunov function that guarantees asymptotic stability of the origin for the double integrator system when controlled with the previous bounded control law. As such, the control law forms a family of control laws depending on (i) and (ii). The complete state space of the system, under the proposed control laws, has two equilibria, and by proper control design, a trajectory of the system is guaranteed to converge to only one of those. The overall design provides a common framework for controlling different systems, such as quadrotors and slung load transportation systems.

  • 1373.
    Ótão Pereira, Pedro Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, SE-10044 Stockholm, Sweden..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Pose stabilization of a bar tethered to two aerial vehicles2020In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 112, article id 108695Article in journal (Refereed)
    Abstract [en]

    This work focuses on the modeling, control and analysis of a bar, tethered to two unmanned aerial vehicles, which is required to stabilize around a desired pose. We derive the equations of motion of the system, we close the loop by equipping each UAV with a PID control law, and finally we linearize the closed-loop vector field around some equilibrium points of interest. When requiring the bar to stay on the horizontal plane and under no normal stress, we verify that the bar's motion is decomposable into three decoupled motions, namely a longitudinal, a lateral and a vertical: for a symmetric system, each of those motions is further decomposed into two decoupled sub-motions, one linear and one angular; for an asymmetric system, we provide relations on the UAVs' gains that compensate for the system asymmetries and which decouple the linear sub-motions from the angular sub-motions. From this analysis, we provide conditions, based on the system's physical parameters, that describe good and bad types of asymmetries. Finally, when requiring the bar to pitch or to be under normal stress, we verify that there is a coupling between the longitudinal and the vertical motions, and that a positive normal stress (tension) has a positive effect on the stability, while a negative normal stress (compression) has a negative effect on the stability.

  • 1374.
    Ótão Pereira, Pedro Miguel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Roque, Pedro
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Asymmetric Collaborative Bar Stabilization Tethered to Two Heterogeneous Aerial Vehicles2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE Computer Society, 2018, p. 5247-5253Conference paper (Refereed)
    Abstract [en]

    We consider a system composed of a bar tethered to two unmanned aerial vehicles (UAVs), where the cables behave as rigid links under tensile forces, and with the control objective of stabilizing the bar's pose around a desired pose. Each UAV is equipped with a PID control law, and we verify that the bar's motion is decomposable into three decoupled motions, namely a longitudinal, a lateral and a vertical. We then provide relations between the UAVs' gains, which, if satisfied, allows us to decompose each of those motions into two cascaded motions; the latter relations between the UAVs' gains are found so as to counteract the system asymmetries, such as the different cable lengths and the different UAVs' weights. Finally, we provide conditions, based on the system's physical parameters, that describe good and bad types of asymmetries. We present experiments that demonstrate the stabilization of the bar's pose.

  • 1375.
    Özkahraman, Özer
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Tajvar, Pouria
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Ögren, Petter
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Data-Driven Damage Detection and Control Adaptation for an Autonomous Underwater Vehicle2022In: 61st IEEE Conference on Decision and Control (CDC), 2022, 2022Conference paper (Refereed)
    Abstract [en]

    Underwater robotic exploration missions typically involve traveling long distances without any human contact.The robots that go on such missions risk getting damaged by the unknown environment, accruing great costs and missed opportunities.Thus it is important for the robot to be able to accommodate unknown changes to its dynamics as much as possible and attempt to finish the given mission, or at the very least move itself to a retrievable position.

    In this paper, we show how we can detect physical changes to the robot reliably (79\% on real robot data) and then incorporate these changes through adapting the model to the data followed by automated control redesign. We adopt a piecewise-affine (PWA) modelling of the dynamics that is well suited for low data regime learning of the dynamics and provides a structure for computationally efficient control synthesis.We demonstrate the effectiveness of the proposed method on a combination of real robot data and simulated scenarios.

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  • 1376.
    Čičić, Mladen
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Control of vehicle platoons and traffic dynamics: catch-up coordination and congestion dissipation2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Traffic congestion is a constantly growing problem, with a wide array ofnegative effects on the society, from wasted time and productivity to elevated air pollution and increased number of accidents. Classical traffic control methods have long been successfully employed to alleviate congestion, improving the traffic situation of many cities and highways. However, traffic control is not universally employed, because of the necessity of installing additional equipment and instating new legislation. 

    The introduction of connected, autonomous vehicles offers new opportunities for sensing and controlling the traffic. The data that most of the vehicles nowadays provide are already widely used to measure the traffic conditions. It is natural to consider how vehicles could also be used as actuators, driving them in a specific way so that they affect the traffic positively. However, many of the currently considered strategies for congestion reduction using autonomous vehicles rely on having a high penetration rate, which is not likely to be the case in the near future. This raises the question: How can we influence the overall traffic by using only a small portion of vehicles that we have direct control over? There are two problems in particular that this thesis considers, congestion wave dissipation and avoidance, and platoon catch-up coordination.

    First, we study how to dissipate congestion waves by use of a directly controlled vehicle acting as a moving bottleneck. Traffic data can help predict disturbances and constraints that the vehicle will face, and the individual vehicles can be actuated to improve the overall traffic situation. We extend the classical cell transmission model to include the influence of a moving bottleneck, and then use this model to devise a control strategy for an actuator vehicle. By employing such control, we are able to homogenize the traffic without significantly reducing throughput. Under realistic conditions, it is shown that the average total variation of traffic density can be reduced over 5%, while the total travel time increases only 1%.

    Second, we study how to predict and control vehicles catching up in order to form a platoon, while driving in highway traffic. The influences of road grade and background traffic are examined and vehicles attempting to form a platoon are modelled as moving bottlenecks. Using this model, we are able to predict how much the vehicles might be delayed because of congestion and adjust the plan accordingly, calculating the optimal platoon catch-up speeds for the vehicles by minimizing their energy consumption. This leads to a reduction of energy cost of up to 0.5% compared to the case when we ignore the traffic conditions. More importantly, we are able to predict when attemptingto form a platoon will result in no energy savings, with approximately 80% accuracy.

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  • 1377.
    Čičić, Mladen
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Modelling and Lagrangian control of mixed traffic: platoon coordination, congestion dissipation and state reconstruction2021Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Traffic congestion is a constantly growing problem, with a wide array of negative effects on the society, from wasted time and productivity to elevated air pollution and reduction of safety. The introduction of connected, autonomous vehicles enables a new, Lagrangian paradigm for sensing andcontrolling the traffic, by directly using connected vehicles inside the traffic flow, as opposed to the classical, Eulerian paradigm, which relies on stationary equipment on the road. By using control methods specifically tailored to the Lagrangian paradigm, we are able to influence the traffic flow even if the penetration rate of connected vehicle is low. This allows us to answer one of the central impending questions of the traffic control using emerging technologies: How can we influence the overall traffic by using only a smallportion of vehicles that we can control directly?

    Traffic phenomena such as moving bottlenecks and stop-and-go waves are particularly pertinent to Lagrangian traffic control, and therefore need to be captured in traffic models. In this thesis we introduce the influence of these phenomena into the cell transmission model, multi-class cell transmission model, and tandem queueing model. We also propose a transition system model based on front tracking, which captures the relevant phenomena, and show under which conditions it corresponds to the Lighthill-Whitham-Richards model. Moving bottlenecks are introduced as a moving zone in which a reduced flux function describes the traffic flow, and their influence on the surrounding traffic is given by solving the Riemann problems at the flux function boundaries. Stop-and-go waves are introduced by constraining the wave speed of rarefaction, resulting in constant stop-and-go wave propagation speed and discharging flow lower than the road capacity, which is consistent with the empirical observations.

    We use the proposed traffic models to design control laws that address three problems: platoon merging coordination, congestion reduction, and traffic state reconstruction. We study the case when two trucks are closing the distance and merging into a platoon on a public road, and propose an optimal control algorithm which accounts for the mutual influence between the trucks and the surrounding traffic. The proposed control law minimizes the total fuel consumption of the trucks, and improves the reliability of platooning. Then, we consider two forms of the congestion reduction problem: stationary bottleneck decongestion, and stop-and-go wave dissipation. In both cases, connected vehicles are used as moving bottlenecks to restrict the traffic flow enough to let the congestion dissipate. By applying these control laws, the throughput of the road is increased and the total travel time of all vehiclesis reduced. Finally, we generalize the stop-and-go wave dissipation problem by dropping the assumption that the full traffic state is known, and instead propose traffic state reconstruction algorithms which use local measurements originating from the connected vehicles. We show that the proposed control laws can also be implemented using the reconstructed traffic state. In this case, as the number of available connected vehicles increases, the control performance approaches the full-information control case.

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  • 1378.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Barreau, Matthieu
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Numerical Investigation of Traffic State Reconstruction and Control Using Connected Automated Vehicles2020In: 2020 IEEE 23rd international conference on intelligent transportation systems (ITSC), IEEE , 2020Conference paper (Refereed)
    Abstract [en]

    In this paper we present a numerical study on control and observation of traffic flow using Lagrangian measurements and actuators. We investigate the effect of some basic control and observation schemes using probe and actuated vehicles within the flow. The aim is to show the effect of the state reconstruction on the efficiency of the control, compared to the case using full information about the traffic. The effectiveness of the proposed state reconstruction and control algorithms is demonstrated in simulations. They show that control using the reconstructed state approaches the full-information control when the gap between the connected vehicles is not too large, reducing the delay by more than 60% when the gap between the sensor vehicles is 1.25 km on average, compared to a delay reduction of almost 80% in the full-information control case. Moreover, we propose a simple scheme for selecting which vehicles to use as sensors, in order to reduce the communication burden. Numerical simulations demonstrate that with this triggering mechanism, the delay is reduced by around 65%, compared to a reduction of 72% if all connected vehicles are communicating at all times.

  • 1379.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Energy-optimal platoon catch-up in moving bottleneck framework2019In: 2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), Institute of Electrical and Electronics Engineers (IEEE) , 2019, p. 3674-3679Conference paper (Refereed)
    Abstract [en]

    Truck platooning, where vehicles drive close together in order to reduce air drag, is a promising technology that is slowly reaching maturity. In order to fully exploit its potential, we will need to be able to efficiently form platoons enroute, while driving on the road, by having the vehicles adjust their speeds so that they catch-up and merge into a platoon. Since this means that the participating vehicles will have to deviate from their own optimal speed profiles, experiencing unpredicted disturbances caused by the surrounding traffic might lead to higher fuel consumption. Therefore, in order to increase the fuel savings and improve their predictability, we devise a control strategy that takes into account the traffic conditions and yields optimal catch-up speeds for both the leader and the follower vehicle. The control strategy is based on minimizing total energy consumption, and it models the vehicles as moving bottlenecks. We compare this strategy to one that does not consider the influence of traffic, and show that it achieves better results in terms of energy savings.

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  • 1380.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Front-tracking transition system model for traffic state reconstruction, model learning, and control with application to stop-and-go wave dissipation2022In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 166, p. 212-236Article in journal (Refereed)
    Abstract [en]

    Connected and Autonomous Vehicles is a technology that will be disruptive for all layers of traffic control. The Lagrangian, in-the-flow nature of their operation offers untapped new potentials for sensing and actuation, but also presents new fundamental challenges. In order to use these vehicles for traffic state reconstruction and control, we need suitable traffic models, which should be computationally efficient and able to represent complex traffic phenomena. To this end, we propose the Front-tracking Transition System Model, a cell-free modelling approach that can incorporate Lagrangian measurements, and has a structure that yields itself to on-line model learning and control. The model is formulated as a transition system, and based on the front-tracking method for finding entropy solutions to the Lighthill-Whitham-Richards model. We characterize the solution of this model and show that it corresponds to the solution of the underlying PDE traffic model. Algorithms for traffic state reconstruction and model learning are proposed, exploiting the model structure. The model is then used to design a prediction -based control law for stop-and-go wave dissipation using randomly arriving Connected and Autonomous Vehicles. The proposed control framework is able to estimate the traffic state and model, adapt to changes in the traffic dynamics, and achieve a reduction in vehicles' Total Time Spent.

  • 1381.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Stop-and-go wave dissipation using accumulated controlled moving bottlenecks in multi-class CTM framework2019In: Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 3146-3151Conference paper (Refereed)
    Abstract [en]

    Stop-and-go waves on freeways are a well known problem that has typically been addressed using dynamic speed limits. As connected automated vehicles enter the roads, new approaches to traffic control are becoming available, since the control actions can now be communicated to these vehicles directly. It is therefore important to consider automated vehicles independently from the rest of the traffic, using traffic models with multiple vehicle classes. In this paper, we use a multi-class CTM to capture the interaction between the controlled vehicles and the background traffic. Exploiting the nonlinear nature of the model, we are able to first collect enough controlled vehicles into an area, and then use them to actuate the rest of the traffic by acting as a controlled moving bottleneck. In this way, we are able to dissipate stop-and-go waves quicker, improving the throughput and homogenizing the traffic. The effectiveness of the approach is demonstrated in simulations. 

  • 1382.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Traffic regulation via individually controlled automated vehicles: a cell transmission model approach2018In: 2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), IEEE , 2018, p. 766-771Conference paper (Refereed)
    Abstract [en]

    The advent of automated, infrastructure-controlled vehicles offers new opportunities for traffic control. Even when the number of controlled vehicles is small, they can significantly affect the surrounding traffic. One way of regulating traffic is by using the automated vehicles as controlled moving bottlenecks. We present an extension of the cell transmission model that includes the influence of moving bottlenecks, consistently with the corresponding PDE traffic model. Based on this model, a control strategy is derived for traffic jam resolution. The strategy is tested in simulations, and shown to reduce the average travel time of surrounding vehicles, while also helping dissipate the traffic jam faster and ensuring the controlled vehicle avoids it.

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  • 1383.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Scania CV AB.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Platoon Merging Distance Prediction using a Neural Network Vehicle Speed Model2017In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 50, no 1, p. 3720-3725Article in journal (Refereed)
    Abstract [en]

    Heavy-duty vehicle platooning has been an important research topic in recent years. By driving closely together, the vehicles save fuel by reducing total air drag and utilize the road more efficiently. Often the heavy-duty vehicles will catch-up in order to platoon while driving on the common stretch of road, and in this case, a good prediction of when the platoon merging will take place is required in order to make predictions on overall fuel savings and to automatically control the velocity prior to the merge. The vehicle speed prior to platoon merging is mostly influenced by the road grade and by the local traffic condition. In this paper, we examine the influence of road grade and propose a method for predicting platoon merge distance using vehicle speed prediction based on road grade. The proposed method is evaluated using experimental data from platoon merging test runs done on a highway with varying level of traffic. It is shown that under reasonable conditions, the error in the merge distance prediction is smaller than 8%.

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    PlatoonMergingDistancePrediction
  • 1384.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Mikolasek, Igor
    CDV Transport Res Ctr, Brno, Czech Republic..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Front tracking transition system model with controlled moving bottlenecks and probabilistic traffic breakdowns2020In: IFAC PAPERSONLINE, Elsevier BV , 2020, Vol. 53, no 2, p. 14990-14996Conference paper (Refereed)
    Abstract [en]

    Cell-based approximations of PDE traffic models are widely used for traffic prediction and control. However, in order to represent the traffic state with good resolution, cell-based models often require a short cell length, which results in a very large number of states. We propose a new transition system traffic model, based on the front tracking method for solving the LWR PDE model. Assuming piecewise-linear flux function and piecewise-constant initial conditions, this model gives an exact solution. Furthermore, it is easier to extend, has fewer states and, although its dynamics are intrinsically hybrid, is faster to simulate than an equivalent cell-based approximation. The model is extended to enable handling moving bottlenecks as well as probabilistic traffic breakdowns and capacity drops at static bottlenecks. A control strategy that utilizes controlled moving bottlenecks for bottleneck decongestion is described and tested in simulation. It is shown that we are able to keep the static bottleneck in free flow by creating controlled moving bottlenecks at specific instances along on the road, and using them to regulate the incoming traffic flow. 

  • 1385.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Univ Grenoble Alpes, GIPSA Lab, CNRS, Inria,Grenoble INP, Grenoble, France..
    Pasquale, Cecilia
    Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy..
    Siri, Silvia
    Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy..
    Sacone, Simona
    Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Platoon-actuated variable area mainstream traffic control for bottleneck decongestion2022In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 68Article in journal (Refereed)
    Abstract [en]

    In this paper a platoon-actuated mainstream traffic control is proposed to decongest bottlenecks due to recurrent and nonrecurrent events. Indeed, differently from traditional mainstream control strategies, i.e., control strategies applied with fixed actuators, platoon-actuated control can be applied at any location on the freeway. In this work, the control actions to be communicated to the platoons, i.e., speed and configuration, are defined by means of a predictive control law based on traffic and platoon state detected in an area identified immediately upstream of the bottleneck. The main peculiarity of this scheme is that the size of the controlled area is dynamically adjusted based on the predicted congestion at the bottleneck. This approach keeps the control law computation burden low, while not sacrificing much control performance. Specifically, the number of platoons to be controlled and the time at which the platoons begin to be controlled depend on the size of the controlled area. Simulation results reported in the paper show the effectiveness of the proposed scheme, eliminating from 60% to 80% of the delay incurred from congestion compared with the uncontrolled case, depending on the level of traffic.

  • 1386.
    Čičić, Mladen
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Xiong, X.
    Jin, L.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Coordinating Vehicle Platoons for Highway Bottleneck Decongestion and Throughput Improvement2021In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, p. 1-13Article in journal (Refereed)
    Abstract [en]

    Truck platooning is a technology that is expected to become widespread in the coming years. Apart from the numerous benefits that it brings, its potential effects on the overall traffic situation need to be studied further, especially at bottlenecks and ramps. Assuming we can control the platoons from the infrastructure, they can be used as controlled moving bottlenecks, actuating control actions on the rest of the traffic, and potentially improving the throughput of the whole system. In this work, we use a tandem queueing model with moving bottlenecks as a prediction model to calculate control actions for the platoons. We use platoon speeds and formations as control inputs, and design a control law for throughput improvement of a highway section with a stationary bottleneck. By postponing and shaping the inflow to the bottleneck, we are able to avoid capacity drop, which significantly reduces the total time spent of all vehicles. We derived the estimated improvement in throughput that is achieved by applying the proposed control law, and tested it in a simulation study, with multi-class cell transmission model with platoons used as the simulation model, finding that the median delay of all vehicles is reduced by 75.6% compared to the uncontrolled case. Notably, although they are slowed down while actuating control actions, platooned vehicles experience less delay compared to the uncontrolled case, since they avoid going through congestion at the bottleneck. 

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