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PublicationPAISE®. Das Vorgehensmodell für KI-Engineering(Fraunhofer IOSB, 2021)Das Process Model for AI Systems Engineering, kurz: PAISE®, ist ein Vorgehensmodell für KIEngineering.Es wurde innerhalb des Kompetenzzentrums für KI-Engineering (CC-KING) entwickelt.PAISE® umfasst die systematische und standardisierte Entwicklung und den Betriebvon KI-basierten Systemlösungen. Vorgehensweisen aus der Informatik und datengetriebenenModellbildung werden mit denen der klassischen Ingenieurdisziplinen, wie z. B. SystemsEngineering, kombiniert.
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PublicationDeutsche Normungsroadmap Künstliche Intelligenz(DIN, 2020)
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PublicationRealtime Global Optimization of a Fail-Safe Emergency Stop Maneuver for Arbitrary Electrical/Electronical Failures in Automated Driving( 2020)In the event of a critical system failures in auto-mated vehicles, fail-operational or fail-safe measures provide minimum guarantees for the vehicle's performance, depending on which of its subsystems remain operational. Various such methods have been proposed which, upon failure, use different remaining sets of operational subsystems to execute maneuvers that bring the vehicle into a safe state under different environmental conditions. One particular such method proposes a fail-safe emergency stop system that requires no particular electric or electronic subsystem to be available after failure, and still provides a basic situation-dependent emergency stop maneuver. This is achieved by preemptively setting parameters to a hydraulic / mechanical system prior to failure, which after failure executes the preset maneuver ""blindly"". The focus of this paper is the particular challenge of implementing a lightweight planning algorithm that can cope with the complex uncertainties of the given task while still providing a globally optimal solution at regular intervals, based on the perceived and predicted environment of the automated vehicle.
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PublicationAccuracy Evaluation of a Lightweight Analytic Vehicle Dynamics Model for Maneuver Planning( 2020)Models for vehicle dynamics play an important role in maneuver planning for automated driving. They are used to derive trajectories from given control inputs, or to evaluate a given trajectory in terms of constraint violation or optimality criteria such as safety, comfort or ecology. Depending on the computation process, models with different assumptions and levels of detail are used; since maneuver planning usually has strong requirements for computation speed at a potentially high number of trajectory evaluations per planning cycle, most of the applied models aim to reduce complexity by implicitly or explicitly introducing simplifying assumptions. While evaluations show that these assumptions may be sufficiently valid under typical conditions, their effect has yet to be studied conclusively. We propose a model for vehicle dynamics that is convenient for maneuver planning by supporting both an analytic approach of extracting parameters from a given trajectory, and a generative approach of establishing a trajectory from given control inputs. Both applications of the model are evaluated in real-world test drives under dynamic conditions, both on a closed-off test track and on public roads, and effects arising from the simplifying assumptions are analyzed.
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PublicationGeneral Fail-Safe Emergency Stopping for Highly Automated Vehicles( 2019)From SAE level 3 onwards, automated vehicles must be able to resolve sudden system failures without driver intervention, including failure modes that are difficult or impossible to address by redundancy alone. Causes of hazardous multiple-point faults-beyond internal failures-include lightning strikes or deliberate attacks by electromagnetic pulses. Stopping the vehicle under such conditions is challenging: A full braking maneuver may risk rear-end collisions or loss of traction; likewise, any other constant braking profile will pose considerable risk of not achieving a true ""safe state"". This paper presents an emergency stopping system to execute a situation-dependent braking maneuver that can resolve system failures up to(but not limited to) a full electrics/electronics failure, with the aim of providing a baseline safety solution for all failure modes (short of mechanical failures) for which no dedicated solution is available. The system is composed of an electronic planning unit and a hydraulic/mechanical subsystem, both of which are implemented and tested in simulated and in real environments.
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PatentVerfahren zum Steuern eines Fahrzeugs, Vorrichtung zum Erzeugen von Steuersignalen für ein Fahrzeug und Fahrzeug( 2015)EP2881829A2 [DE] Ein Verfahren zum Steuern eines Fahrzeugs von einer aktuellen Position in die Naehe einer Zielposition umfasst das Bestimmen (S102) des Befahrungsrisikos einer Mehrzahl von Positionen in einer Umgebung des Fahrzeugs zu einem aktuellen Zeitpunkt und zu mehreren, dem aktuellen Zeitpunkt folgenden Zeitpunkten und das Bestimmen einer Trajektorie fuer das Fahrzeug, die die aktuelle Position und die Zielposition verbindet oder naeherungsweise verbindet, unter Beruecksichtigung von errechneten Befahrungsrisiken (etwa basierend auf Kollisionswahrscheinlichkeiten, Verkehrsregeln) sowie Fahrdynamik- und Komfortparametern. Das Fahrzeugs wird dann entlang der modifizierten Trajektorie gesteuert (S110).
