Jung, Rolf
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Institute
The development of Automated Driving Systems (ADS) has the potential to revolutionize the transportation industry, but it also presents significant safety challenges. One of the key challenges is ensuring that the ADS is safe in the event of Foreseeable Misuse (FM) by the human driver. To address this challenge, a case study on simulation-based testing to mitigate FM by the driver using the driving simulator is presented. FM by the human driver refers to potential driving scenarios where the driver misinterprets the intended functionality of ADS, leading to hazardous behavior. Safety of the Intended Functionality (SOTIF) focuses on ensuring the absence of unreasonable risk resulting from hazardous behaviors related to functional insufficiencies caused by FM and performance limitations of sensors and machine learning-based algorithms for ADS. The simulation-based application of SOTIF to mitigate FM in ADS entails determining potential misuse scenarios, conducting simulation-based testing, and evaluating the effectiveness of measures dedicated to preventing or mitigating FM. The major contribution includes defining (i) test requirements for performing simulation-based testing of a potential misuse scenario, (ii) evaluation criteria in accordance with SOTIF requirements for implementing measures dedicated to preventing or mitigating FM, and (iii) approach to evaluate the effectiveness of the measures dedicated to preventing or mitigating FM. In conclusion, an exemplary case study incorporating driver-vehicle interface and driver interactions with ADS forming the basis for understanding the factors and causes contributing to FM is investigated. Furthermore, the test procedure for evaluating the effectiveness of the measures dedicated to preventing or mitigating FM by the driver is developed in this work.
Safety of the Intended Functionality (SOTIF) addresses sensor performance limitations and deep learning-based object detection insufficiencies to ensure the intended functionality of Automated Driving Systems (ADS). This paper presents a methodology examining the adaptability and performance evaluation of the 3D object detection methods on a LiDAR point cloud dataset generated by simulating a SOTIF-related Use Case. The major contributions of this paper include defining and modeling a SOTIF-related Use Case with 21 diverse weather conditions and generating a LiDAR point cloud dataset suitable for application of 3D object detection methods. The dataset consists of 547 frames, encompassing clear, cloudy, rainy weather conditions, corresponding to different times of the day, including noon, sunset, and night. Employing MMDetection3D and OpenPCDET toolkits, the performance of State-of-the-Art (SOTA) 3D object detection methods is evaluated and compared by testing the pre-trained Deep Lea rning (DL) models on the generated dataset using Average Precision (AP) and Recall metrics.
Safe Scenario Boundaries Determination by Parameter Variation for an Automated Driving System
(2023)
An expanding area of research interest is the scenario-based testing and development of Automated Driving Systems (ADS). In scenario-based testing, a system is examined in a set of pre-defined scenarios to inspect its behavior. Scenarios are described by a set of parameters, such as velocities and distances. For a safety-related system, identifying the parameter limits for safe operation is essential to reduce harm. Hence, there is a need to determine safe boundaries considering the assumed parameter set in a scenario to support the Verification and Validation (V&V) of an ADS. This paper presents a systematic approach to determining safe boundaries of parameters by scenario-based testing. The contributions of this work are: (i) performing scenariobased parameter variation to detect collisions, (ii) identifying safe boundaries of each single parameter from a specific Operation Design Domain (ODD) and (iii) providing safety-related evidence to identify safe boundaries from defined ODD. The results of this work can assist scenario reduction techniques to derive nothazardous scenarios and hazardous scenarios and support the V&V Processes of ADS.
The development of Automated Driving Systems (ADS) has the potential to revolutionize the transportation industry, but it also presents significant safety challenges. One of the key challenges is ensuring that the ADS is safe in the event of Foreseeable Misuse (FM) by the human driver. To address this challenge, a case study on simulation-based testing to mitigate FM by the driver using the driving simulator is presented. FM by the human driver refers to potential driving scenarios where the driver misinterprets the intended functionality of ADS, leading to hazardous behavior. Safety of the Intended Functionality (SOTIF) focuses on ensuring the absence of unreasonable risk resulting from hazardous behaviors related to functional insufficiencies caused by FM and performance limitations of sensors and machine learning-based algorithms for ADS. The simulation-based application of SOTIF to mitigate FM in ADS entails determining potential misuse scenarios, conducting simulation-based testing, and evaluating the effectiveness of measures dedicated to preventing or mitigating FM. The major contribution includes defining (i) test requirements for performing simulation-based testing of a potential misuse scenario, (ii) evaluation criteria in accordance with SOTIF requirements for implementing measures dedicated to preventing or mitigating FM, and (iii) approach to evaluate the effectiveness of the measures dedicated to preventing or mitigating FM. In conclusion, an exemplary case study incorporating driver-vehicle interface and driver interactions with ADS forming the basis for understanding the factors and causes contributing to FM is investigated. Furthermore, the test procedure for evaluating the effectiveness of the measures dedicated to preventing or mitigating FM by the driver is developed in this work.
Scenario-based testing is essential for Highly Automated Driving (HAD) vehicles to determine the safety-related input parameters and their boundaries. The increasing complexity, vehicle functions, and operational design pose new challenges for scenario-based testing, as the number of scenarios is enormous. Therefore, an efficient and systematic process is required in the various stages of scenario-based testing. The contribution of this study is to provide sensitivity information of safety related parameters and support logical scenario reduction. This paper presents an approach that supports to optimize the safety-related parameters boundary towards logical scenario reduction. Additionally, sensitivity analysis is applied by computing Variance- Based Sensitivity Analysis (VBSA) indices and prioritize the input parameters. Two datasets are investigated by VBSA based on the input parameters. One dataset is based on the samples from realworld scenarios and other dataset is derived from the samples considering statistic distributions with a specific parameter range. Moreover, the proposed approach is applied to an exemplary use case and the outcomes are demonstrated.
Simulation-Based Testing of Foreseeable Misuse by the Driver Applicable for Highly Automated Driving
(2024)
With highly automated driving (HAD), the driver can engage in non-driving-related tasks. In the event of a system failure, the driver is expected to reasonably regain control of the automated vehicle (AV). Incorrect system understanding may provoke misuse by the driver and can lead to vehicle-level hazards. ISO 21448, referred to as the standard for safety of the intended functionality (SOTIF), defines misuse as usage of the system by the driver in a way not intended by the system’s manufacturer. Foreseeable misuse (FM) implies anticipated system misuse based on the best knowledge about the system’s design and the driver’s behavior. This is the underlying motivation to propose simulation-based testing of FM. The vital challenge is to perform a simulation-based testing for a SOTIF-related misuse scenario. Transverse guidance assist system (TGAS) is modeled for HAD. In the context of this publication, TGAS is referred to as the “system”, and the driver is the human operator of the system. This publication focuses on implementing the driver-vehicle interface (DVI) that permits the interactions between the driver and the system. The implementation and testing of a derived misuse scenario using the driving simulator ensure reasonable usage of the system by supporting the driver with unambiguous information on system functions and states so that the driver can conveniently perceive, comprehend, and act upon the information.
To ensure the safety and security of Automated Vehicles (Avs), the interaction between the Functional Safety (FuSa) and the Cybersecurity (CS) domains needs to be managed systematically. There is a demand to develop effective and structured management systems to support the homologation process. From this motivation, identifying the interaction between the Safety Management System (SMS) and the Cybersecurity Management System (CSMS) is a fundamental aspect and needs to be improved for HAD systems. Hence, the classical Decision Making Trial and Evaluation Laboratory (DEMATEL) method and fuzzy DEMATEL are applied to evaluate the influential factors that can impact the safety and security of the HAD systems. This paper proposes a list of influencing factors focusing on the interaction between SMS and CSMS for HAD systems. Additionally, the results of an anonymously conducted survey among experts from industry and research are presented and used as inputs for the methods. This work helps to understand the relationship between influencing factors and provides a simplified, easy-to-visualized, and valuable guide for developing HAD systems. The result of this study shows that the most important influential factor is F13. Moreover, the cause and effect of the factors are illustrated numerically and graphically. The influential factors F1 to F7 are identified as the cause and F8 to F13 are reasoned to effect. Finally, a circular representation of the influential factors and their interaction is presented in this paper.
Functional safety and cybersecurity are essential parts of the development of automated vehicles to ensure vehicle safety. Highly automated driving (HAD) vehicles require safe and secure development and communication processes that have to be monitored, maintained and improved through management processes. Hence, interface management systems are required to confirm HAD vehicle safety. The acceptance level of the interface between functional safety and cybersecurity in management systems is crucial for the development of Highly Automated Driving (HAD) vehicles. The Safety Management System (SMS) needs to consider the aspect of cybersecurity to ensure the overall safety of the vehicles or vice-versa. However, the interface methods of SMS and Cybersecurity Management System (CSMS) is challenging given the complexity of the system development and constraints from the company culture. The objective of this study is to present an interface approach in between management systems with a set of interface specifications including communication adaption processes. The main contributions of the paper are, (i) Illustrating the interface areas of the SMS and CSMS by identifying the management factors, (ii) Presenting the degree of influence of the management factors based on the survey results, and (iii) Providing a support to deal with SMS and CSMS interface for HAD vehicle development. A list of interface-related management factors is presented in this paper based on the literature study and findings from other disciplines. Additionally, the degree of influence of the management factors is presented as a result of this research based on the survey results from functional safety and cybersecurity experts.
Was für die sogenannte weiße Ware passt, muss sich auch für andere
Anwendungen in der Industrie eignen. Überzeugt von diesem Ansatz, kooperieren die Hochschule Kempten und ein Unternehmen für drahtlose Sensorsysteme eng miteinander, um ein kabelloses Sensorsystem weiterzuentwickeln.
Ziel des gemeinsam von Pro-micron und der Hochschule Kempten durchgeführten Projekts ist die Weiterentwicklung eines kabellosen Sensorsystems, das seit Jahren im automatisierten Garprozess in der weissen Ware zum Einsatz kommt. Das System dient zur Messung der Rotortemperatur von Elektromotoren in Großserienanwendungen. Denkbar sind somit nicht nur Anwendungen in Konvektomaten, sondern in sämtlichen Bereichen, in denen eine ausgeklügelte Temperaturmessung zu besseren Antriebseigenschaften führt. Somit liegt der Mehrwert entsprechender Temperatursignale zur Steuerung elektrischer Maschinen auf der Hand und kann erhebliche Vorteile aufweisen. Auslastung, Effizienz und Drehmomentengenauigkeit sowie ein zuverlässiger Übertemperaturschutz sind nur einige Beispiele für die Vielzahl von Vorzügen, welche sich aus der Rotortemperaturmessung ergeben.
The development of Highly Automated Driving (HAD) systems is necessary for automated vehicles in termsof various complex functionalities. HAD systems consist of complex structures containing different types ofsensors. The functionality of HAD systems needs be tested to ensure the overall safety of automated vehicles.Methods such as real-world testing require a large number of driving miles and are enormously expensive andtime-consuming. Therefore, simulation-based testing is widely accepted and applicable in the development ofHAD systems, including sensor performance improvement. In order to identify the functional insufficiencyof such sensors that affect the safety of HAD systems, it is critical to test these sensors extensively under avariety of conditions such as, road types, environment and traffic situations. Based on this motivation, the maincontributions of this paper are as follows: First, a simulation-based test concept of radar sensors with methodsfor the Safety Of the Intended Functionality (SOTIF) use case is presented. Second, a specific radar effect isevaluated through simulation-based testing of two different radar models to support and realize the sensor’sfunctional insufficiency. Finally, the development of a filter is proposed to improve the sensor performanceconsidering the radar specific multipath propagation effects.