Stefan Otten

Stellv. Bereichsleiter

Werdegang

Stefan Otten schloss den Masterstudiengang Elektrotechnik am Karlsruher Institut für Technologie (KIT) mit dem Modell Systems Engineering ab. Thematische Schwerpunkte liegen auf der Entwicklung und Absicherung von zukünftigen Fahrzeugsystemen durch neuartige Prozesse/Methoden, Verzahnung von simulativen und realen Tests sowie die Verwendung von Daten im Automobil. Seit 2015 ist er als Abteilungsleiter im Bereich Embedded Systems and Sensors Engineering (ESS) verantwortlich für Themen rund um Automotive Systems Engineering, seit 2017 verantwortet er den Forschungsbereich ESS stellvertretend.

Publikationen

Buch (2)

1. Classification of Automotive Electric/Electronic Features and the Consequent Hierarchization of the Logical System ArchitectureDetails

   Bach, Johannes and Otten, Stefan and Sax, Eric, Springer International Publishing, 2019

2. Automated assessment and evaluation of digital test drivesDetails

   Stefan Otten, Johannes Bach, Christoph Wohlfahrt, Christian King, Jan Lier, Hermann Schmid, Stefan Schmerler, Eric Sax, Springer International Publishing, 2018

Zeitungs- oder Zeitschriftenartikel (6)

1. Absicherung der Reichweitenschätzung basierend auf aufgezeichneten RealdatenDetails

   Patrick Petersen, Stefan Otten, Adam Thorgeirsson, Stefan Scheubner, 2019

2. Prozessanlagenplanung 2.0 - Netzarchitektur aus Verfahrensbeschreibung ableitenInfoDetails

   Thomas Glock, Matthias Kern, Stefan Otten, Eric Sax, Martin Hillenbrand, Michael Hübner, 2016

   Die Planung von elektrischen Kabelnetzen und die Auswahl von geeigneten Geräten, die die elektrische/elektronische Realisierung der Verfahrensbeschreibung (Rohrleitungs- und Instrumentenfließschema) in industriellen Prozessanlagen repräsentieren, erfolgt heute weitgehend manuell. Um den Aufwand zu reduzieren, die Kosten zu mindern und die Qualität zu erhöhen, sind modellbasierte Ansätze und Methoden, wie sie bereits in der Entwicklung von Elektrik-/Elektronikarchitekturen im Automobil eingesetzt werden, ein vielversprechender Ansatz. Dieser Beitrag stellt eine Methodik vor, die, basierend auf neuartigen Methoden und Werkzeugen, die Ableitung und Verwendung einer Vernetzungsarchitektur zur Planung von Industrieanlagen auf Basis der Verfahrensbeschreibung unterstützt.

3. Managing Functional Safety Processes for Automotive E/E Architectures in Integrated Model-based Development EnvironmentsDetails

   Adler, Nico and Otten, Stefan and Schwär, Melanie and Müller-Glaser, Klaus D., 2014

4. Design and analysis of functionally safe hardware in an EBSDetails

   Adler, Nico and Metzker, Eduard and Rudolph, Alexander and Otten, Stefan and Müller-Glaser, K. D., 2014

5. Design und Analyse funktional sicherer Hardware in einem EBSDetails

   Adler, Nico and Metzker, Eduard and Rudolph, Alexander and Otten, Stefan and Müller-Glaser, K. D., 2014

6. Performing Safety Evaluation on Detailed Hardware Level according to ISO 26262Details

   Adler, Nico and Otten, Stefan and Cuenot, Philippe and Müller-Glaser, Klaus D., 2013

Konferenzbeitrag (18)

1. Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-DataInfoDetails

   Jacob Langner, Hannes Grolig, Stefan Otten, Marc Holzäpfel, Eric Sax, 2019

   For the development of Advanced Driver Assistant Systems (ADAS) and Automated Driving Systems (ADS) a change from test case-based testing towards scenario-based testing can be observed. Based on current approaches to define scenarios and their inherent problems, we identify the need to extract scenarios including the static environment from recorded real-world-driving-data. We present an approach, that solves the problem to extract dynamic-length-segments containing a single scenario. These segments are enriched with a feature vector with information relevant for the feature under test. By clustering these scenarios a logical scenario catalog is created, containing all scenarios within the test data. Corner cases are represented as well as common scenarios. An accumulated total length can be calculated for each logical scenario, giving a brief understanding about existing test coverage of the scenario.

2. Training and Validation Methodology for Range Estimation AlgorithmsInfoDetails

   Patrick Petersen, Adam Thorgeirsson, Stefan Scheubner, Stefan Otten, Frank Gauterin, Eric Sax, 2019

   Estimating the range of battery electric vehicles is one of the most challenging topics for the current trend in the automotive industry, the electrification of vehicles. Range anxiety still limits the adoption of battery electric vehicles. Since the range estimation is dependent on different influencing factors, complex algorithms to accurately estimate the vehicles consumption are required. To evaluate the accuracy of data-driven machine learning algorithms, an exhaustive training and validation procedure is mandatory. In this paper, we propose a novel methodology for the development and validation of range estimation algorithms based on machine learning validation approaches. The proposed methodology considers the evaluation of driver-specific and driver-unspecific performance. In addition, an error measure is introduced to assess the performance of range estimation algorithms. This approach is demonstrated and evaluated on a set of recorded real-world driving data. It is shown that our approach helps to analyze the performance of the range estimation algorithm and the influences of different parameter sets.

3. Integrating Static Code Analysis ToolchainsDetails

   Matthias Kern, Ferhat Erata, Markus Iser, Carsten Sinz, Frederic Loiret, Stefan Otten, Eric Sax, 2019

4. Scenario-based Functional Safety for Automated Driving on the Example of Valet ParkingInfoDetails

   Valerij Schönemann, Hermann Winner, Thomas Glock, Stefan Otten, Eric Sax, Bert Boeddeker, Geert Verhaeg, Fabrizio Tronci, Gustavo G. Padilla, IEEE - Future Information and Communication Conference (FICC2018), 2018

   New safety challenges have to be targeted due to the development of fully automated vehicles in the upcoming future. However, designing safe vehicle automation systems is essential. This work presents a scenario-based methodology for functional safety analysis according to the ISO 26262 using the example of automated valet parking (AVP). The vehicle automation system is decomposed into functional scenarios that can occur during operation. Potential malfunctions are identified for each scenario within a hazard analysis and risk assessment (HARA). Elaborated safety goals for automated valet parking are presented.

5. Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using AutoencodersInfoDetails

   Jacob Langner and Johannes Bach and Lennart Ries and Stefan Otten and Eric Sax and Marc Holzäpfel, 2018

   Advanced Driver Assistant Systems (ADAS) use a multitude of input signals for tasks like trajectory planning and control of vehicle dynamics provided by a large variety of information sources such as sensors and digital maps. To assure the feature?s valid behavior all realistically possible environmental situations have to be tested. The test scenarios used for simulation can be derived from real-world-driving-data. However, the significance of derived scenarios is weakened by repetitive similar situations within the driving data, which increase the test efforts without providing new insights regarding the test of the ADAS. In this contribution, an automated selection algorithm for test scenarios based on relevant environmental parameters is presented. Starting with a randomly selected initial testset, the machine-learning concept of autoencoders is utilized to recognize novel scenarios within the data pool, which are iteratively added to the initial testset. Furthermore, the key parameters for the autoencoder?s performance are shown in depths. The approach is fully automated, so that the identified novel scenarios within an entire testset are automatically combined to a reduced testset of unique relevant scenarios. The achieved testset reduction and thereby the saving potential in simulation time is demonstrated on a dataset including several thousand test kilometers.

6. Modellbasierte Planung und Konfiguration von verteilten Funktionsumfängen in der FeldebeneInfoDetails

   Thomas Glock, Stefan Otten, Sebastian Rebmann, Eric Sax, VDI-Verlag, 2017

   Die Planung und Konfiguration von heutigen Industrieanlagen sind mit existierenden Vorgehen und Planungswerkzeugen realisierbar. Im zunehmend vernetzten Umfeld und der damit einhergehenden Dezentralisierung von Funktionalitäten im Kontext von Industrie 4.0 bestehen Herausforderungen, die mit vorhandenen Verfahren und Techniken nicht bewältigt werden können. Insbesondere existieren keine Ansätze zur Planung, Analyse und Konfiguration von hybriden Anlagen, die eine Vereinigung von traditionellen und Internet of Things (IoT) Technologien beschreiben können. In diesem Beitrag wird ein Konzept vorgestellt, welches auf Basis von Methoden und Werkzeugen der Automobil-Entwicklung eine durchgängige, modellbasierte Beschreibung von dezentralen Funktionen, deren Verteilung auf Hardware sowie Analyse und Konfiguration unterstützt. Dies ermöglicht erstmals die gesamtheitliche Auslegung und Konzeption von hybriden Netzwerken in Industrieanlagen in frühen Produktentwicklungsphasen. Der Beitrag wird durch eine beispielhafte Anwendung und Validierung des modellbasierten Ansatzes an einem IoT-Demonstrator einer Mehrtankanlage abgerundet.

7. Identifikation von Fahrszenarien während einer virtuellen Testfahrt Details

   Christian King, Johannes Bach, Stefan Otten, Eric Sax, 2017

8. Test Scenario Selection for System-Level Verification and Validation of Geolocation-Dependent Automotive Control SystemsInfoDetails

   Johannes Bach, Jacob Langner, Stefan Otten, Marc Holzäpfel, Eric Sax, 2017

   Enhanced capabilities of sensors and digital maps for intelligent vehicles lead to a complex and multivariant system environment with a broad variety of situations and traffic scenarios. To assure the feature under development's valid behavior, the sample of scenarios evaluated for Verification & Validation (VV) needs to proof substantial coverage of all possible situations. Currently applied (VV) activities on system-level are in a large part based on real world tests. These are not scalable to sufficiently cover the variant system environment. Our previously introduced Reactive-Replay enables substantial coverage by reuse of recorded real world data in closed-loop simulation. In this contribution we present an approach to determine the relevance of recorded scenarios and derive efficient sets of test scenarios. Our two-step approach starts with a specification-based classification-tree for initial scenario selection. A data-driven reduction of the initial scenario set is achieved by the following analysis of covered parameter spaces. The final consolidated test set avoids repetitive situations while ensuring a significant diversity of the sampled system environment.

9. Data-Driven Development, A Complementing Approach for Automotive Systems EngineeringInfoDetails

   Johannes Bach, Jacob Langner, Stefan Otten, Marc Holzäpfel, Eric Sax, 2017

   Established methods and processes in the field of Automotive Systems Engineering (ASE) are challenged by the rising complexity of current features. Expanding system boundaries, tighter interconnections of functional elements, increasingly complex algorithms and an ever growing operational domain generate a multitude of different scenarios that require consideration during specification, design, implementation and testing. This paper reflects the current practice on the example of the Automotive SPICE process reference for system and software development in the automotive domain. It then contemplates on opportunities of consistent usage of recorded vehicle data throughout all phases of automotive development. Our concept of data-driven development is not intended to replace the current practice but to complement it. A summary of our previous work demonstrates the practicability of the concept on the basis of the development of a Predictive Cruise Control (PCC) feature. The contribution concludes with a scalable concept for the large scale application of data-driven development in ASE.

10. Framework for using real driving data in automotive feature development and validationInfoDetails

    Jacob Langner, Johannes Bach, Stefan Otten, Eric Sax, Carl Esselborn, Marc Holzäpfel, Michael Eckert, 2017

    The increasing complexity and interconnectivity of automotive features raises the significance of comprehensive verification and validation activities. High-level automotive features use the information provided by complex environmental perception sensors and systems. Due to the rising number of these sensors and the usage of enhanced digital maps, System level verification and validation for high-level features has become a challenge, that is often tackled by a combination of real world tests and simulation approaches. In this contribution we present a method, that combines the realism of real world tests with the scalability of simulation approaches. In the presented framework a feature under development is executed in a Software-in-the-Loop environment with the help of recorded real world driving data. With the steadily growing pool of recorded test drives from test campaigns and country approvals, large scale simulations have been facilitated. This enables statistically significant assertions, continuous maturity tracking as well as geolocation-dependent evaluation of the feature under test. The framework makes these large scale simulations feasible during automotive feature development by utilizing parallelization concepts to achieve simulation speeds of thousands of kilometers within minutes and by reducing adaptation overhead for changes in the feature's software code to a minimum.

11. Reactive-Replay Approach for Verification and Validation of Closed-Loop Control Systems in Early DevelopmentInfoDetails

    Johannes Bach and Marc Holzäpfel and Stefan Otten and Eric Sax, SAE International, 2017

    AbstractEnhanced technological capabilities render the application of various, increasingly complex, functional concepts for automated driving possible. In the process, the significance of automotive software for a satisfactory driving experience is growing. To benefit from these new opportunities, thorough assessment in early development stages is highly important. It enables manufacturers to focus resources on the most promising concepts. For early assessment, a common approach is to set up vehicles with additional prototyping hardware and perform real world testing. While this approach is essential to assess the look-and-feel of newly developed concepts, its drawbacks are reduced reproducibility and high expenses to achieve a sufficient and balanced sample. To overcome these drawbacks, new flexible, realistic and preferably automated virtual test methods to complement real world verification and validation are especially required during early development phases. In this contribution, we present a method for automated system assessments based on the reuse of recorded driving data in closed-loop simulation and its application in early development of a predictive cruise control system. Firstly, we identify the requirements for early assessment of closed-loop system concepts, analyze the eligibility of established methods regarding the identified requirements and describe open challenges for development of automotive software systems with focus on early development stages. Our previously introduced Reactive-Replay approach addresses these challenges by enabling reuse of recorded driving data in closed-loop simulation. We complement this approach by introducing automated assessments for evaluation of software increments. By integrating periodic assessments into the development process, we achieve continuous tracking of software quality with very small effort. It is shown that the provision of a broad data pool for simulation based evaluation of new and refined concepts contributes to a substantial reduction of real world test mileage in early development stages.

12. A Taxonomy and Systematic Approach for Automotive System Architectures: From Functional Chains to Functional NetworksDetails

    Bach, Johannes, Otten, Stefan, Sax, Eric, 2017

13. Identifikation von Fahrszenarien während einer virtuellen TestfahrtDetails

    King, Christian; Bach, Johannes; Otten, Stefan; Sax, Eric, 2017

14. Model based scenario specification for development and test of automated driving functionsInfoDetails

    Johannes Bach, Stefan Otten, Eric Sax, 2016

    Research and evaluation of algorithms and system architectures for automated driving advanced to a stage where transition from prototyping to series development seems practicable in some extent. While particular systems for environmental perception play a key role in advanced driving assistance systems, we still lack feasible methods for specification and validation of complex driving scenarios. This leads to increased effort in testing and inconsistent requirement definition along different development phases. In this paper we propose a methodology for abstract positional and temporal description of driving scenarios. The approach utilizes a movie related and omniscient view composed of sequential acts. Each act combines both states and interactions of distinct participants as well as the rudimental scenery. Selective events trigger changes in conduct leading to transitions between acts. Graphical visualization provides simple presentation of complex scenarios. Rule sets provide consistency checks and support semi-automated generation of test cases. The presented methodology facilitates model based test specification and requirements design constituting a consistent characterization of system environment from early concept and development to validation.

15. Ableitung von modellbasierten industriellen Vernetzungsarchitekturen aus dem Rohrleitungs- und InstrumentenfließschemaInfoDetails

    Thomas Glock, Matthias Kern, Stefan Otten, Eric Sax, VDI Verlag GmbH, 2016

    Die Planung von elektronischen Kabelnetzen, die die elektronische Realisierung der Verfahrensbeschreibung (Rohrleitungs- und Instrumenten Fließschema) in industriellen Prozessanlagen repräsentieren, erfolgt heute weitgehend manuell. Zu diesen Anlagen gehören zum Beispiel Raffinerien, kunststofferzeugende Fabriken und Lebensmittelgewerbe. Die Anforderungen an diese Anlagen sind unterschiedlich und liegen in der Regel nur als Text vor. Um den Aufwand zu reduzieren, die Kosten zu mindern und die Qualität zu erhöhen, sind modellbasierte Ansätze und Methoden, wie sie beispielsweise bereits in der Entwicklung von Elektrik-/Elektronik-Architekturen im Automobil eingesetzt werden, eine realistische Chance. Durchgängigkeit von den Anforderungen zur Realisierung, frühe Fehlerentdeckung und –behebung während der Planung von elektronischen Kabelnetzen sowie die Wiederverwendung von Bibliothekselementen sind das Ziel. So wird in diesem Beitrag dargelegt, wie mit Hilfe von Methoden und Tools der Automobil-Entwicklung neue Methoden für die unterstützende Planung von Industrieanlagen auf Basis der Verfahrensbeschreibung abgeleitet und genutzt werden können. Dabei fokussiert dieser Beitrag eine Methode zur automatisierten Erstellung von elektronischen Kabelnetzen (Vernetzungsarchitekturen) aus der Verfahrensbeschreibung. Ein Beispiel einer Mehrtankanlage, die als ein Bestandteil in Verfahren der Lebensmittelherstellung vorzufinden ist, rundet den Beitrag ab.

16. Domain model based derivation of virtual driving scenarios for vehicle simulations from in-field measurementsDetails

    Johannes Bach, Stefan Otten, Eric Sax, 2016

17. Applying Model Based Techniques for Early Safety Evaluation of an Automotive Architecture in Compliance with the ISO 26262 StandardDetails

    Cuenot, Philippe and Ainhauser, Christoph and Adler, Nico and Otten, Stefan and Meurville, Florent, 2014

18. Rapid safety evaluation of hardware architectural designs compliant with ISO 26262Details

    Adler, Nico and Otten, Stefan and Mohrhard, Markus and Müller-Glaser, Klaus D., 2013

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