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Supervised reinforcement learning based trajectory tracking control for autonomous vehicles ⁎

IFAC-PapersOnLine 2024年第10期58卷 140-145页

作者： András Mihály Van Tan Vu Trong Tu Do Péter Gáspár Systems and Control Laboratory Institute for Computer Science and Control (SZTAKI) Hungarian Research Network Kende u. 13-17 H-1111 Budapest Hungary Department of Automotive Mechanical Engineering Faculty of Mechanical Engineering University of Transport and Communications Hanoi Vietnam Mechanical and Power Engineering Faculty Electric Power University Hanoi Vietnam

Recent developments in autonomous vehicle technologies and applications gain a lot of interest by the public, as the popularity of both driver assistance and automated driving systems increase. One of the most promising aspect of the autonomous vehicle compared to conventional human driven vehicle is the increased level of safety. Machine learning techniques enables to achieve fast and efficient control actions compared to model based techniques. However, the advantages of a more conservative model based controller are their better robustness properties. In this paper a synergy of the two control philosophy is presented through a trajectory tracking control design for autonomous vehicles. A supervised reinforcement learning (RL) control method is introduced, where a robust Linear Parameter Varying (LPV) controller supervises the operation of the trained RL agent. Thus, in case sensor noise is detected, the guaranteed stability LPV controller takes over the steering control action. In order to demonstrate the operation of the proposed method, three different simulations have been evaluated and compared in CarSim simulation environment.

关键词： autonomous vehicle control supervised reinforcement learning trajectory tracking

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Analysis and control of Gene Regulation Network Models Using Kinetic Semi-Discretization

Analysis and Control of Gene Regulation Network Models Using...

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European control Conference (ECC)

作者： Mihály A. Vághy Irene Otero-Muras Gábor Szederkenyi Faculty of Information Technology and Bionics Pazmany Peter Catholic University Budapest Hungary Spanish Council for Scientific Research Carrer del Catedratic Agustin Escardino Benlloch Institute for Integrative Systems Biology Valencia Spain Systems and Control Laboratory ELKH Institute for Computer Science and Control (SZTAKI) Budapest

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper the exogenous control of gene reg-ulatory networks is investigated through the semi-discretized partial integro-differential equation (PIDE) describing the time-evolution of the network's probability density function. With an appropriate finite volume method the semi-discretized system is a mass-conservative linear compartmental model, and thus it preserves most qualitative properties of the solution of the PIDE, namely, it is nonnegative and mass conservative. These advantages combined with the newly investigated mesh-invariance of control allows us to efficiently determine the reachability set. The possibilities of this framework are demon-strated through an illustrative example from literature.

关键词： Solid modeling Analytical models Computational modeling Volume measurement Sociology Switches Mathematical models

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Towards Measuring the Traceability of Cryptocurrencies

arXiv

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arXiv 2022年

作者： Kelen, Domokos M. Seres, István András ELKH Institute for Computer Science and Control SZTAKI Budapest Hungary Eötvös Loránd University Budapest Hungary

Cryptocurrencies aim to replicate physical cash in the digital realm while removing centralized and trusted intermediaries. Decentralization is achieved by the blockchain, a permanent public ledger that contains a record of every transaction. The public ledger ensures transparency, which enables public verifiability but harms untraceability, fungibility, and anonymity. In the last decade, cryptocurrencies attracted millions of users, with their total market cap reaching approximately three trillion USD at its peak. However, their anonymity guarantees are poorly understood and plagued by widespread misbeliefs. Indeed, previous notions of privacy, anonymity, and traceability for cryptocurrencies are either non-quantitative or inapplicable, e.g., computationally hard to measure. In this work, we put forward a formal framework to measure the (un)traceability and anonymity of cryptocurrencies, allowing us to quantitatively reason about the mixing characteristics of cryptocurrencies and the privacy-enhancing technologies built on top of them. Our methods apply absorbing Markov chains combined with Shannon entropy. To the best of our knowledge, our work provides the first practical, efficient, and probabilistic measure to assess the traceability of cryptocurrencies quantitatively, which also generalizes to entire cryptocurrency transaction graphs. We implement and extensively evaluate our proposed traceability measure on several cryptocurrency transaction graphs. Among other quantitative results, we find that in the studied one-week interval, the Bitcoin blockchain, on average, provided comparable but quantifiably more natural mixing than the Ethereum blockchain. © 2022, CC BY.

关键词： Blockchain

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Route selection method with ethical considerations for automated vehicles under critical situations

Route selection method with ethical considerations for autom...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Balá zs Né meth Systems and Control Laboratory Institute for Computer Science and Control (SZTAKI) E&#x00F6 tv&#x00F6 s Lor&#x00E1 nd Research Network (ELKH) Budapest Hungary

Route selection for automated vehicle is a challenging task under critical situations, i.e., which can lead to serious or fatal injury. Due to the high risk of a dangerous collision with its consequences on human participants, the selection on possible routes poses ethical problems. This paper proposes a multi-layer route selection strategy for automated vehicles under critical situations, in which ethical considerations have been incorporated. The selection strategy contains a graph-based quantitative evaluation layer and a layer with qualitative evaluation based on the ethical principles. The operation of the route selection method through some examples is illustrated.

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Voting Based Navigation System Fault Detection for Aircraft Position Information During Final Approach

Voting Based Navigation System Fault Detection for Aircraft ...

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Conference on control and Fault-Tolerant Systems (SysTol)

作者： Tamas Grof Peter Bauer Institute for Computer Science and Control (SZTAKI) ELKH Budapest Hungary

This paper presents a simple and so easily implementable threshold and up-down counter-based voting algorithm for the fault detection of aircraft position information during landing. Easy implementation is inevitable in case of small unmanned aircraft due to the size weight and power consumption constraints. Most of the development is based-on real flight test data collected in frame of the VISION EU H2020 research project on a 4m wingspan aircraft. The aircraft’s position flight measurements were provided by an on-board GPS unit with SBAS correction and an on-board data-based inertial-barometric-camera sensor fusion ESKF algorithm. ILS was simulated as the aircraft and airport were not equipped with it. SBAS, ILS and ESKF errors were all artificially added to the nominal flight and simulated data. Pairwise comparison of position information is the basis of fault detection. Category I precision approach requirements are considered to tune and test the fault-detection algorithm first, by the selection of thresholds and then by the fine tuning of up-down counters to reduce false alarms. Both integrity risk and time-to-alert requirements are satisfied only the continuity risk resulted below the expected but this does not mean needless abortion of landings.

关键词： Fault tolerance Power demand Fault detection Fault tolerant systems Sensor fusion Position measurement Aircraft navigation

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Collision-free motion control with learning features for automated vehicles in roundabouts

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Transportation Research Procedia 2023年 72卷 3545-3552页

作者： Balázs Németh Zsófia Farkas Zoltán Antal Dániel Fényes Péter Gáspár Institute for Computer Science and Control (SZTAKI) Eötvös Loránd Research Network (ELKH) Kende utca 13-15. 1111 Budapest Hungary Budapest University of Technology and Economics Department of Control for Transportation and Vehicle Systems Stoczek utca 2. 1111 Budapest Hungary

control design for safe and time-efficient motion of automated vehicles in roundabout scenarios poses various challenges, especially adaptation to the actual traffic scenario and coordination of the vehicles. This paper proposes the design of a hierarchical motion control with learning feature for roundabout scenarios. The control is designed on two levels, such as on cloud level and on vehicle level. The control on the cloud level is designed by using reinforcement learning ( RL ), with which the energy efficient motion of the vehicle is achieved. The vehicle level contains a robust controller and a supervisor, with which the collision avoidance of the vehicles is guaranteed. The proposed control on a Hardware-in-the-Loop environment with small-scaled indoor vehicles in augmented reality is implemented. The effectiveness of the control and the safe motion of the automated vehicles under multi -vehicle scenario are demonstrated. The provided scenario illustrates that safe, i.e., collision-free motion of all automated vehicles can be guaranteed.

关键词： automated vehicles learning features roundabouts collision-free motion control design

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Lyapunov stability of generalized ribosome flows*

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IFAC-PapersOnLine 2022年第18期55卷 56-61页

作者： Mihály A. Vághy Gábor Szederkényi Faculty of Information Technology and Bionics Pázmany Péter Catholic University H-1444 Budapest Hungary Systems and Control Laboratory Institute for Computer Science and Control (SZTAKI) H-1111 Budapest Hungary

In this paper we show that a wide class of compartmental systems with bounded capacities called generalized ribosome flow models are stable with an entropy-like logarithmic Lyapunov function known from the theory of nonnegative systems and reaction networks. The stability proof uses the kinetic representation of the compartmental model and earlier approaches applied for the input-to-state stability analysis of reaction networks with time-varying reaction rates. The results are valid not only for mass action type systems but also for models with more general reaction rates. Illustrative examples are given to show the qualitative dynamical properties of simple generalized ribosome flow models.

关键词： Lyapunov methods stability of nonlinear systems stability of distributed parameter systems kinetic modeling

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Analyzing Aerial 3D Maps to Guide a Ground Vehicle to Complement the Regions Not Visible from Above

Analyzing Aerial 3D Maps to Guide a Ground Vehicle to Comple...

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International Conference on Advanced Robotics (ICAR)

作者： Barnabás Bugár-Mészáros András L. Majdik Machine Perception Research Laboratory HUN-REN Institute for Computer Science and Control (HUN-REN SZTAKI) Budapest Hungary Department of Material Handling and Logistics Systems Budapest University of Technology and Economics Budapest

The detailed reconstruction of complex unknown environments is a challenging task in several robotic applications. Multi-robot systems combining the advantages of aerial and ground vehicles are often used for this purpose, where the different perspectives of sensors are leveraged to reduce the proportion of uncovered areas. Since the lower speed of ground robots in cluttered environments compared to aerial vehicles can significantly limit the efficiency of the exploration, in this paper we propose a cooperative mapping system in which only the necessary regions are assigned to the ground vehicle. These regions are selected based on the structural analysis of the 3D model built by an aerial robot and a global path is computed connecting them which only passes traversable parts of the environment. A ground 3D map is also created and the two models are fused when the robot reaches the last waypoint of the path. We tested our solution in multiple simulated environments to verify its functionality.

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Combined observer design for road vehicles using LPV-based and learning-based methods

Combined observer design for road vehicles using LPV-based a...

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Mediterranean Conference on control and Automation (MED)

作者： Dá niel Fé nyes Tamá s Hegedű s Balá zs Né meth Institute for Computer Science and Control (SZTAKI) E&#x00F6 tv&#x00F6 s Lor&#x00E1 nd Research Network (ELKH) Budapest H-1111 Hungary

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

In this paper a novel observer design method is proposed, which combines Linear Parameter-Varying-based (LPV) and machine-learning-based design tools. As a first step, a parameter optimization technique is developed to achieve a polytopic LPV formulation of the system model. This modeling technique also involves a machine-learning-based solution to determine scheduling parameters for the LPV system. In the second step, a LPV-based observer design based on the achieved system representation is proposed. Finally, the operation and the effectiveness of the proposed observer algorithm are demonstrated through a vehicle-oriented estimation problem, i.e., estimation of the lateral velocity. In the paper two simulations illustrate the accuracy and the advantageous impact of the observer on the control performances of the closed-loop system.

关键词： Learning systems Road vehicles Neural networks Estimation Observers Software Design tools

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Software-in-the-loop simulation of the forerunner UAV system

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IFAC-PapersOnLine 2022年第14期55卷 139-144页

作者： Antal Hiba Peter Bauer Mihaly Nagy Erno Simonyi Adam Kisari Gergely Istvan Kuna Istvan Drotar Research Center of Vehicle Industry Széchenyi István University Győr Hungary and Computational Optical Sensing and Processing Laboratory Institute for Computer Science and Control (SZTAKI) ELKH Budapest Hungary Research Center of Vehicle Industry Széchenyi István University Győr Hungary and Systems and Control Laboratory Institute for Computer Science and Control (SZTAKI) ELKH Budapest Hungary Széchenyi István University Győr Hungary

The forerunner UAV means a camera equipped drone flying in front of the advancing first responder units to increase driver situational awareness with an aerial view of the traffic situation and notification about imminent dangers. This article presents the software-in-the-loop (SIL) simulation of the concept including UNREAL4-Carla as the virtual reality environment with a firetruck driven through a game controller, the Matlab simulation of the DJI M600 forerunner hexacopter with UDP communication between firetruck and M600 and the real-time AI processing of synthetic images to detect ground vehicles and pedestrians. The target of SIL development is threefold. First, to test M600 autopilot and AI-based object detection in close to realistic conditions before the real flights. Second, to make an exhaustive feasibility study of the whole forerunner concept with several simulated situations. Third, to generate the required large amount of image data for AI object detection tuning. After introducing all parts of the SIL simulation the article presents an illustrative example evaluating the tracking of the ground vehicle with the M600 and the inference system results.

关键词： first responders forerunner UAV SIL simulation

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