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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Andreas Homann Markus Buss Martin Keller Torsten Bertram Institute of Control Theory and Systems Engineering TU Dortmund University Dortmund Germany ZF Group Active & Passive Safety Technology Düsseldorf Germany

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

This paper presents two approaches for the determination of a feedforward for lateral trajectory tracking control. Most trajectory planning approaches for automated vehicles are based on a mass point description. Thus, the reference trajectory only provides information about the position in x- and y-coordinates over time. Therefore, this paper proposes a method to estimate the side-slip angle and to calculate the yaw rate from the course rate. With this additional enriching information about the reference trajectory, a feedforward control based on the inversion of the linear single-track model is introduced. On the other hand, a flat output is used to invert the nonlinear single-track model and thus determine a feedforward control.

关键词： Trajectory Vehicle dynamics Mathematical model Feedforward systems Planning Wheels Trajectory tracking

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Environment simulation for the development, evaluation and verification of underlying algorithms for automated driving

Environment simulation for the development, evaluation and v...

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Automotive meets Electronics, AmE 2016

作者： Wissing, Christian Nattermann, Till Glander, Karl-Heinz Seewald, Alois Bertram, Torsten TU Dortmund Institute of Control Theory and Systems Engineering Dortmund44227 Germany ZF TRW Active and Passive Safety Technology Düsseldorf40547 Germany

ISBN: (纸本)9783800741670

Algorithms for situation interpretation and prediction in traffic environments are essential in order to face automated driving challenges successfully. At the same time it is hardly possible to guarantee the functionality of such algorithms in every imaginable situation. In order to cope with such problems, the common approach in practice is to apply exhaustive and time consuming evaluation in real traffic situations. In this contribution a driving environment simulation is presented that is suited for the simulation of various highway scenarios and the generation of simulation data comparable to the output of a physical sensor data fusion architecture in real highway situations. The simulation models the dynamics of traffic flow augmented with a data based model to account for perception uncertainties. Finally a sample traffic scenario and the generated simulation output is presented. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach

关键词： Sensor data fusion

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Comparison of Curve Representations for Memory-Efficient and High-Precision Map Generation

Comparison of Curve Representations for Memory-Efficient and...

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International Conference on Intelligent Transportation

作者： Niklas Stannartz Mario Theers Adalberto Llarena Marc Sons Markus Kuhn Torsten Bertram TU Dortmund Niklas Stannartz and Torsten Bertram are with the Institute of Control Theory and Systems Engineering Dortmund Germany ZF Automotive Germany GmbH Düsseldorf Germany

The following topics are dealt with: traffic engineering computing; road traffic; road vehicles; learning (artificial intelligence); road safety; mobile robots; driver information systems; optimisation; object detecti... 详细信息

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

关键词： Splines (mathematics) Memory management Optimization Roads Physical layer Design automation Standards

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Ego-motion correction based on static objects detected by an automotive lidar sensor system 10

Ego-motion correction based on static objects detected by an...

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10. GMM-Fachtagung Automotive meets Electronics, AmE 2019 - 10th GMM-Symposium Automotive meets Electronics, AmE 2019

作者： Stannartz, Niklas Wissing, Christian Krüger, Martin Tolmidis, Avraam Ali, Syed Irtiza Nattermann, Till Bertram, Torsten TU Dortmund University Institute of Control Theory and Systems Engineering Dortmund44227 Germany ZF Automated Driving and Integral Cognitive Safety Düsseldorf40547 Germany

ISBN: (纸本)9783800748778

This paper presents a framework for ego-motion correction exploiting static objects in the environment detected by an automotive lidar sensor system. Many previous works tackle this problem using raw point cloud data yielding an improved performance with respect to dead reckoning (DR) at the cost of neglecting embedded object tracking algorithms integrated in automotive sensors while increasing the computational demands. Since exteroceptive sensors (cameras, radars and lidars) typically segment distinct objects of the environment from the raw measurements, the use of classified static objects resemble a natural choice for an ego-motion correction reducing the computational overhead in parallel. The ego-motion correction is based on an observability-constrained Unscented Kalman Filter (OCUKF) exploiting detected point- and line-shaped static objects that are temporally maintained in a local map of the visible surroundings. For the latter type a measurement model for continuous line-shaped landmarks is proposed that tackles disadvantages of the commonly used model in the literature. Finally, experimental results show the improved ego-motion estimation of the OCUKF algorithm with respect to DR. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Object detection

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Robust data-driven state-feedback design

Robust data-driven state-feedback design

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American control Conference

作者： Julian Berberich Anne Koch Carsten W. Scherer Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Institute of Mathematical Methods in the Engineering Sciences Numerical Analysis and Geometrical Modeling Department of Mathematics University of Stuttgart Stuttgart Germany

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

We consider the problem of designing robust state-feedback controllers for discrete-time linear time-invariant systems, based directly on measured data. The proposed design procedures require no model knowledge, but only a single open-loop data trajectory, which may be affected by noise. First, a data-driven characterization of the uncertain class of closed-loop matrices under state-feedback is derived. By considering this parametrization in the robust control framework, we design data-driven state-feedback gains with guarantees on stability and performance, containing, e.g., the H_ ∞-control problem as a special case. Further, we show how the proposed framework can be extended to take partial model knowledge into account. The validity of the proposed approach is illustrated via a numerical example.

关键词： data driven design process Robust control numerical example Time invariant systems

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Predictive Driving: Fusing Prediction and Planning for Automated Highway Driving

Predictive Driving: Fusing Prediction and Planning for Autom...

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作者： Lienke, Christian Wissing, Christian Keller, Martin Nattermann, Till Bertram, Torsten Institute of Control Theory and Systems Engineering TU Dortmund University DortmundD-44221 Germany Active and Passive Safety Technology ZF Group Düsseldorf40547 Germany

To guide an automated vehicle safely through complex traffic, knowledge about the future evolution of the driving situation has to be considered. The contribution at hand proposes an approach for automated driving in structured environments. An environment representation for trajectory planning is presented that enables predictive driving by interconnecting trajectory prediction for the surrounding traffic and planning of an according ego trajectory. A maneuver-based approach with an efficient trajectory model is carried out to enable an accurate and fast estimation of future motions of other vehicles. The results are directly considered in the dynamic environment representation utilized for trajectory planning. In the trajectory optimization process, the required safety distance is hence taken into account uniquely for each future time instance. The evaluation of the trajectory prediction approach shows very good performance on a simulated as well as on a dataset recorded by a test vehicle. On account of the predictive character of the developed environment potential field, simulation experiments demonstrate the feasibility and effectiveness of the proposed method. © 2016 IEEE.

关键词： Vehicles

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Combining Prior Knowledge and Data for Robust controller Design

arXiv

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arXiv 2020年

作者： Berberich, Julian Scherer, Carsten W. Allgöwer, Frank The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70569 Germany The Institute of Mathematical Methods in the Engineering Sciences Numerical Analysis and Geometrical Modeling Department of Mathematics University of Stuttgart Stuttgart70569 Germany

We present a framework for systematically combining data of an unknown linear time-invariant system with prior knowledge on the system matrices or on the uncertainty for robust controller design. Our approach leads to linear matrix inequality (LMI) based feasibility criteria which guarantee stability and performance robustly for all closed-loop systems consistent with the prior knowledge and the available data. The design procedures rely on a combination of multipliers inferred via prior knowledge and learnt from measured data, where for the latter a novel and unifying disturbance description is employed. While large parts of the paper focus on linear systems and input-state measurements, we also provide extensions to robust output-feedback design based on noisy input-output data and against nonlinear uncertainties. We illustrate through numerical examples that our approach provides a flexible framework for simultaneously leveraging prior knowledge and data, thereby reducing conservatism and improving performance significantly if compared to black-box approaches to data-driven control. Copyright © 2020, The Authors. All rights reserved.

关键词： Robust control

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Bearing-Only Formation control with Limited Visual Sensing: Two Agent Case⁎

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IFAC-PapersOnLine 2018年第23期51卷 28-33页

作者： Frank, Daniel Zelazo, Daniel Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Germany Faculty of Aerospace Engineering Technion - Israel Institute of Technology Israel

This work solves the bearing-only formation control problem for two agents with limited field-of-view sensing. We propose a bearing-only control strategy for both the position and heading of each agent that guarantees the desired formation is obtained from almost all initial conditions, and ensures that the agents always remain inside the field-of-view of the sensor. We support our analysis with simulations and explore an extension for the 3- and 4-agent case. © 2018

关键词： Multi agent systems Bearing only control strategies Field of views Formation control Formation control problems Initial conditions Two agent case Visual sensing

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Hardware-in-the-Loop-Simulation of the light distribution of automotive Matrix-LED-Headlights*

Hardware-in-the-Loop-Simulation of the light distribution of...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Mirko Waldner Maximilian Krämer Torsten Bertram Institute of Control Theory and Systems Engineering TU Dortmund University Dortmund Germany

This contribution proposes a novel Hardware-in-the-Loop (HiL)-simulation of the light distribution of matrix-headlights to reduce the duration and number of real night test drives. After calibration machine vision cameras measure and digitize the light distribution of the real matrix-headlight in the lab. The calibration process compares the light distribution measured by the camera with the absolute intensity-data from a goniophotometer. Minimizing the error determines the optimal transformation parameters. A virtual testing simulation visualizes the digitized light distribution under consideration of the actual driving dynamics. The HiL-simulation generates the control data for the real headlight. The evaluation of the approach uses a real matrix-headlight with 84 pixels and its measured intensity distribution as the reference. The system is real-time capable and the light distribution in the simulation matches the original headlight in intensity and color.

关键词： Image color analysis Light sources Cameras Vehicle dynamics Real-time systems Light emitting diodes

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Derivation and Application of an Observer Structure to Detect Inconsistencies Within a Static Environmental Model 1

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4. Internationale ATZ-Fachtagung Automatisiertes Fahren, 2018

作者： Lütkemöller, Moritz Oeljeklaus, Malte Bertram, Torsten Rink, Klaus Stählin, Ulrich Grewe, Ralph Institute of Control Theory and Systems Engineering TU Dortmund Dortmund Germany Continental Chassis & Safety Passive Safety & Sensorics Frankfurt Germany Advanced Engineering Continental Chassis & Safety Frankfurt Germany

ISBN: (数字)9783658237516

ISBN: (纸本)9783658237509

Smart vehicles like autonomously driving cars have the advantage to make a ride more safe and comfortable because intelligent vehicles respond better and faster than human beings to critical situations [1]. Having accurate knowledge of its environment is essential for a car that drives autonomously. Based on this, a maneuver adapted to the situation can be planned and carried out. The perception takes place via a variety of sensors such as cameras, radars and LIDAR's [2, 3]. However, the disadvantage of an intelligent vehicle is the complex infrastructure consisting of sensors, ECUs, communication equipment, etc. that is needed to perceive the environment correctly. As the complexity increases, the susceptibility to errors of such a system increases the same way. Errors refer to the failure of individual units, the incorrect processing of information, but also the manipulative interference of unauthorized persons.. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019.

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