Search

Innovative testing and validation methods are prerequisites concerning Connected, Cooperative, and Automated Mobility (CCAM), as the high number of cooperating participants and concurrent processes critically increase the probability of adverse safety and security incidents. The proposed new approaches deal with this increasing complexity of not currently having generally accepted validation mechanisms. The paper introduces a novel, mathematical model based, scenario identification methodology, facilitating the selection of critical road vehicle traffic scenarios, taking into account different testing objectives, such as maximizing the safety risk of the analyzed system. The presented results verify that applying specific decision models and quantifiable indicators related to the system elements of highly automated mobility systems can significantly contribute to the systematic identification of unsafe corner cases in connected and cooperative autonomous systems.

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is increasing interest in automating train operations of mainline services, e.g., to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but is still not implemented on a large scale. Functional, interoperability and performance tests are necessary before ATO can be introduced generally. Virtual preliminary analysis will contribute to the validation process to ensure a safe and successful implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators commonly used in the railway sector, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. They are refined by adding sub-indicators specific to the performance evaluation of ATO algorithms. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. For demonstration purposes, a simple case study is conducted. Thereby we exemplarily show-cased the approach for ATO performance testing using a microscopic train simulator in combination with an ATO algorithm. [ABSTRACT FROM AUTHOR]

There is increasing interest in automating train operations of mainline services, e.g., to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but is still not implemented on a large scale. Functional, interoperability and performance tests are necessary before ATO can be introduced generally. Virtual preliminary analysis will contribute to the validation process to ensure a safe and successful implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators commonly used in the railway sector, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. They are refined by adding sub-indicators specific to the performance evaluation of ATO algorithms. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. For demonstration purposes, a simple case study is conducted. Thereby we exemplarily show-cased the approach for ATO performance testing using a microscopic train simulator in combination with an ATO algorithm.

Highly automated vehicles are increasingly gaining the public’s attention. To achieve broad acceptance for the deployment of such vehicles, it is necessary to ensure their functionality and safety. One approach that has become popular in research is the scenario-based approach. However, manual testing of such complex systems is impractical and time-consuming. Using simulations to run and evaluate such scenarios appears to be the most viable approach. This, in turn, raises new challenges, especially in modeling the scenarios to be tested simulatively and incorporating the system under test as part of these. Since existing solutions do not solve these challenges satisfactorily—due to the strict separation of scenario and simulation model, among other reasons—this work addresses the need for a standardized, holistic, and extensible approach for modeling traffic scenarios to be executed simulatively. Requirements for such an approach are identified with focus on its application in simulation- and scenario-based verification and validation. Based on these, a model-based multi-layered approach is proposed. The foundations of this are then implemented utilizing a Meta Object Facility based heavyweight extension of the Unified Modeling Language metamodel. The resulting metamodel is used to demonstrate the applicability of the proposed approach by modeling a maritime traffic scenario.

Highly automated vehicles are increasingly gaining the public's attention. To achieve broad acceptance for the deployment of such vehicles, it is necessary to ensure their functionality and safety. One approach that has become popular in research is the scenario-based approach. However, manual testing of such complex systems is impractical and time-consuming. Using simulations to run and evaluate such scenarios appears to be the most viable approach. This, in turn, raises new challenges, especially in modeling the scenarios to be tested simulatively and incorporating the system under test as part of these. Since existing solutions do not solve these challenges satisfactorily—due to the strict separation of scenario and simulation model, among other reasons—this work addresses the need for a standardized, holistic, and extensible approach for modeling traffic scenarios to be executed simulatively. Requirements for such an approach are identified with focus on its application in simulation- and scenario-based verification and validation. Based on these, a model-based multi-layered approach is proposed. The foundations of this are then implemented utilizing a Meta Object Facility based heavyweight extension of the Unified Modeling Language metamodel. The resulting metamodel is used to demonstrate the applicability of the proposed approach by modeling a maritime traffic scenario. [ABSTRACT FROM AUTHOR]