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International Conference on Intelligent Transportation

作者： Eggert Julian Florian Damerow 2Plorian Damerow is with the Control Methods and Robotics Lab Technical University of Darmstadt Darmstadt Germany

This paper presents a general model for lane-change decision and dynamic lane change behavior based on the Foresighted Driver Model. Differently to previous models, it does not rely on indirect features like gap lengths, TTC or decelerations, but it models the lane change process by explicitly calculating the involved risks and benefits of the different trajectory alternatives. The lane change decision occurs by searching a tradeoff between the anticipated risks and the utility of the maneuver for the driver. In such a way, the model generalizes to a large variability of lane-change situations with varying number of involved traffic participants, since their states are incorporated into the risk estimation. We show that with our model, regular lane change processes can be reliably captured. We also show, how in complex constellations, the model reacts in plausible ways which are not covered by previous models. This is the case e.g. when an emergency lane-change is forced by a fast rear-end approach, or when a lane change occurs in anticipation to an expected merge-in at an entrance.

关键词： Trajectory Vehicles Frequency division multiplexing Hidden Markov models Roads Acceleration Cost function

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Managing the complexity of inner-city scenes: An efficient situation hypotheses selection scheme

Managing the complexity of inner-city scenes: An efficient s...

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IEEE Symposium on Intelligent Vehicle

作者： Stefan Klingelschmitt Florian Damerow Julian Eggert Control Methods and Robotics Lab Technical University of Darmstadt Germany Honda Research Institute Europe GmbH Germany

Due to the large number and the high variability of possible traffic situations, intersections are among the most accident-prone spots in inner-city traffic. To reliably assist the driving tasks elaborated risk assessment systems are needed. Current approaches are mainly based on the prediction of possible future trajectories of the involved traffic participants. However, considering the variability and combinatorics of intersection-related traffic situations, this becomes unfeasible for limited computational resources. Here, we present a general framework for an efficient situation hypotheses selection system. The selection process is based on reasoning about whether a particular situation results in a threat for the ego vehicle's behavior. Our approach combines the results of a probabilistic situation recognition and a fast risk assessment using state-of-the-art regression methods. We show that the proposed system is able to effectively reduce the number of unnecessarily considered situation hypotheses on average by over 80%.

关键词： Vehicles Risk management Probabilistic logic Estimation Trajectory Reliability Joints

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Distributed Dynamic Decoupling-based Output Synchronization for Networks of Linear Heterogeneous MIMO Agents

Distributed Dynamic Decoupling-based Output Synchronization ...

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IEEE Annual Conference on Decision and control

作者： Saman Khodaverdian Jurgen Adamy Institute of Automatic Control and Mechatronics Control Methods and Robotics Lab Technische Universitat Darmstadt Landgraf-Georg-Str. 4 64283 Darmstadt Germany

ISBN: (纸本)9781479978878

This paper deals with the output synchronization problem of linear heterogeneous MIMO systems. In contrast to common approaches, we present a method which works without the embedding of virtual exosystems that produce a certain synchronization trajectory. A distributed control strategy is provided that consists of three parts: First, noninteracting control techniques are used to generate the synchronization dynamics, if necessary, and to satisfy the internal model principle. Second, a transformation is proposed to get appropriate SISO descriptions for the decoupled input-output channels. Third, based on the SISO models for every channel, distributed controllers are designed that synchronize the agents' outputs.

关键词： multiple input multiple output systems Agents Network embedding noninteracting control Output Distribute control technology

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Balancing risk against utility: Behavior planning using predictive risk maps

Balancing risk against utility: Behavior planning using pred...

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IEEE Symposium on Intelligent Vehicle

作者： Florian Damerow Julian Eggert Control Methods and Robotics Lab Technical University of Darmstadt Darmstadt Germany Honda Research Institute (HRI) Europe Offenbach Germany

This paper addresses the problem of future behavior evaluation and planning for ADAS in general traffic situations. Complex traffic situations require the estimation of future behavior alternatives in terms of predictive risks. Based on the predicted future dynamics of traffic scene entities, we present an approach where a continuous, probabilistic model for future risks is used to build so-called predictive risk maps. These maps indicate how risky a certain ego-car trajectory will be at different predicted times so that they can be used to directly plan the best possible future behavior. Since this optimization problem is highly non-convex we combine the risk maps with sampling-based planning algorithms of the RRT*-type to obtain future trajectories which minimize risk and maximize utility. We apply our approach to multiple risk types and various different scenarios, including inner city and highway situations.

关键词： Trajectory Acceleration Planning Predictive models Heuristic algorithms Estimation Cost function

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Using Context Information and Probabilistic Classification for Making Extended Long-Term Trajectory Predictions

Using Context Information and Probabilistic Classification f...

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International Conference on Intelligent Transportation

作者： Stefan Klingelschmitt Julian Eggert Control Methods and Robotics Lab Technical University of Darmstadt Darmstadt Germany Honda Research Institute Europe GmbH Offenbach am Main Germany

Intersections are among the most accident prone spots in traffic. Future Advanced Driver Assistance Systems (ADAS) are aiming to assist the driving task in these complex scenarios. This can be realized by assessing the criticality of possible occurring situations. For such criticality assessment techniques predicting the trajectories of the involved traffic participants several seconds in advance is necessary. In this paper we outline a method that makes exhaustive use of context information to reliably predict maneuver-specific trajectories up to 5 seconds into the future. Since the evolution of traffic scenes cannot be predicted with absolute certainty, approximating future states in form of probability density functions will be of great benefit in terms of robustness and reliability. %Since, methods for approximating probability distributions are complex and in most cases computationally inefficient, We present an approach that is able to efficiently construct a discrete probability distribution by reformulating the problem as a probabilistic multiclass classification problem. The presented approach is evaluated on a real-world data set containing approaches to 85 different intersections. We show that we can make reliable maneuver-specific state estimations, even for a prediction horizon of up to 5 seconds.

关键词： Trajectory Vehicles Acceleration Probability distribution Context Predictive models Probabilistic logic

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A noninteracting control strategy for the robust output synchronization of linear heterogeneous networks

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control Theory and Technology 2014年第3期12卷 234-249页

作者： Saman KHODAVERDIAN Jürgen ADAMY Institute of Automatic Control and Mechatronics Control Methods and Robotics Lab Technische Universitt DarmstadtLandgraf-Georg-Str.464283 Darmstadt Germany

This paper deals with the problem of robust output synchronization for heterogeneous multi-agent systems. First, a new synchronization approach is presented to synchronize the outputs of heterogeneous agents. Based on noninteracting control techniques, a method is derived for homogenizing the input-output behavior of every agent. Hence, applying the same reference input signal to every agent leads to synchronization. Furthermore, a strategy for increasing the robustness of the synchronization process against exogenous disturbances is presented, which leads to a structurally constrained optimization problem. However, by a convenient reformulation of the problem, well established tools from robust control theory can be used. Moreover, it is shown that this procedure allows to separate the robustness issue from the synchronization task. The effectiveness of the approach is illustrated by a robust output synchronization example for a heterogeneous aircraft fleet.

关键词： Heterogeneous networks Multi-agent systems Decentralized control Robust synchronization Disturbance rejection controller constraints and structure

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Feedback control of nonlinear systems using passivity indices

Feedback control of nonlinear systems using passivity indice...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Diego de S. Madeira Jurgen Adamy Technische Universitat Darmstadt Fachbereich Biologie Darmstadt Hessen DE Control Methods and Robotics Lab. Technische Universität Darmstadt Darmstadt Germany

This paper presents a new controller design framework for nonlinear feedback systems using passivity indices. These indices measure the level of passivity of a system and can be used to set lower bounds to the parameters of a stabilizing controller. We provide a systematic way of designing a dynamic output feedback controller based on a matrix condition on the plant dynamics and its passivity indices. Instead of demanding the solution of partial differential equations and the derivation of Casimir functions, as it is the case of most control by interconnection methods, our strategy relies solely on algebraic conditions. This issue simplifies the controller design considerably. We assume that all functions involved are polynomials. Lyapunov stability of the closed-loop is addressed. An example is provided in order to demonstrate the applicability of the proposed method.

关键词： Stability criteria Output feedback Nonlinear systems Lyapunov methods Numerical stability Interconnected systems

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Finite-time behavior of log-linear learning in potential games 7

Finite-time behavior of log-linear learning in potential gam...

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7th International Conference on Network Games, control and Optimization, NetGCoop 2014

作者： Tatarenko, Tatiana TU Darmstadt Control Methods and Robotics Lab Darmstadt64289 Germany

ISBN: (纸本)9788884435743

Log-linear learning algorithm applied to the class of potential games has been proven to converge to system optimal states when these states coincide with potential function maximizers. A theoretical analysis of the algorithm based on the properties of time-inhomogeneous Markov chains provides the method to choose an algorithm parameter guaranteeing the convergence. In this work, we characterize the finite-time behavior of the log-linear learning algorithm by estimating its rate of convergence. We also provide some insights into the properties of the algorithm performance. © 2014 University of Trento.

关键词： Learning algorithms

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The Foresighted Driver Model

The Foresighted Driver Model

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IEEE Symposium on Intelligent Vehicle

作者： Julian Eggert Florian Damerow Stefan Klingelschmitt Honda Research Institute (HRI) Offenbach Germany Technische Universitat Darmstadt Fachbereich Biologie Darmstadt Hessen DE Control Methods and Robotics Lab Technical University of Darmstadt Darmstadt Germany

The Intelligent Driver Model (IDM) is a microscopic, time continuous car following model for the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity and its capacity to describe both single vehicle velocity profiles as well as collective traffic behavior. Nevertheless, it lacks a series of properties that would be desirable for more realistic agent models. In this paper, as an alternative and improvement to the IDM, we propose the Foresighted Driver Model (FDM), which assumes that a driver acts in a way that balances predictive risk (e.g. due to possible collisions along its route) with utility (e.g. the time required to travel, smoothness of ride, etc.). Based on a risk concept developed for full behavior planning, we introduce driver model equations from the assumption that a driver will mainly try to avoid risk maxima in time and space. We show how such a model can be used to simulate driving behavior similar to full behavior planning models and which generalizes and reaches beyond the IDM modeling scenarios.

关键词： Vehicles Predictive models Frequency division multiplexing Trajectory Adaptation models Acceleration Roads

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Singleton-based two-string inference in recurrent fuzzy systems 19

Singleton-based two-string inference in recurrent fuzzy syst...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Schneider, Moritz Adamy, Jürgen Institute of Automatic Control and Mechatronics Control Methods and Robotics Lab. Technische Universität Darmstadt Germany

ISBN: (纸本)9783902823625

Two-string fuzzy inference consists of two separate inference mechanisms: One conventional fuzzy inference system that processes recommending rules, as well as a mechanism for processing negative rules, which prevent the system from outputting their associated values when their premise is fulfilled. Two-string inference has valuable applications in pattern recognition and control tasks. We present a method rendering two-string inference applicable and computationally feasible in recurrent fuzzy systems, i.e. Mamdami-type fuzzy inference systems equipped with defuzzified state feedback. We show the efficiency of our approach by means of an illustrative example from biological systems modelling and suggest application areas for recurrent two-string fuzzy systems. © IFAC.

关键词： Fuzzy inference

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