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  • 1.
    Dahlbom, Sixten
    et al.
    RISE Research Institutes of Sweden, Safety and Transport, Fire and Safety.
    Sanfridson, Martin
    RISE Research Institutes of Sweden, Safety and Transport, Measurement Technology.
    Sjöblom, Ted
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    Evaluation of Detection Principles and Challenges in Early Detection of Thermal Runaway in Batteries2023Report (Other academic)
    Abstract [en]

    The amount of battery electrical vehicles (BEVs) carried as cargo on ro-ro ships is increasing. The possibility of thermal runaway in a lithium-ion battery makes BEVs a different fire risk compared to internal combustion engine vehicles (ICEV). One of the challenges that arise is how to detect a thermal runaway early. Current detection systems in ro-ro spaces generally consist of smoke and/or heat detection. To identify potential techniques and challenges for detection of a thermal runaway, as early as possible, tests with batteries and detectors are needed. Tests with one battery cell were performed inside an ISO container (with almost negligible ventilation) as well as in an open room with moderate ventilation (14 air changes per hour). Point-type detectors (two smoke and heat detectors, one CO detector, and one LEL detector), thermal imaging, video analytics, and light detection and ranging (LIDAR) were evaluated in the tests. A total of 14 tests were conducted. The detectors were evaluated in different positions relative to the battery cell and comparative tests with wood-sticks were performed to investigate the detectors’ ability to detect a more conventional source of fire. Based on the results, it can be concluded that early detection of thermal runaway in batteries is possible in principle. However, detection is a matter of circumstances e.g., ventilation, gas/smoke production and the location of the detector(s). The result indicates that detection in a small and confined space is relatively manageable, but detection in a large and open space could be more of a challenge. If the gas/smoke is cooled down it may sink and spread along the floor/deck, instead of rising and spreading along the ceiling. This would be a challenge with current smoke detectors installed in the ceiling. Shielding may be a problem, especially with LIDAR and thermal imaging. Future research should address full-scale tests, and it is recommended to include Optical Gas Imaging (OGI) as a mean of detection.

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  • 2.
    Gyllenhammar, Magnus
    et al.
    Zenuity AB, Sweden.
    Johansson, Rolf
    Autonomous Intelligent Driving, Sweden.
    Warg, Fredrik
    RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.
    Chen, DeJiu
    KTH Royal Institute of Technology, Sweden.
    Heyn, Hans-Martin
    Volvo Technology AB, Sweden.
    Sanfridson, Martin
    Volvo Technology AB, Sweden.
    Söderberg, Jan
    Systemite AB, Sweden.
    Thorsén, Anders
    RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.
    Ursing, Stig
    Semcon Sweden AB, Sweden.
    Towards an Operational Design Domain That Supports the Safety Argumentation of an Automated Driving System2020In: 10th European Congress on Embedded Real Time Systems (ERTS 2020), Toulouse, France, 2020Conference paper (Refereed)
    Abstract [en]

    One of the biggest challenges for self-driving road vehicles is how to argue that their safety cases are complete.The operational design domain (ODD) of the automated driving system (ADS) can be used to restrict where the ADS is valid and thus confine the scope of the safety case as well as the verification. To complete the safety case there is a need to ensure that the ADS will not exit its ODD. We present four generic strategies to ensure this. Use cases (UCs) provide a convenient way providing such a strategy for a collection of operating conditions (OCs) and furth erensures that the ODD allows for operation within the real world. A framework to categorise the OCs of a UC is presented and it is suggested that the ODD is written with this structure in mind to facilitate mapping towards potential UCs. The ODD defines the functional boundary of the system and modelling it with this structure makes it modular and generalisable across different potential UCs. Further, using the ODD to connect the ADS to the UC enables the continuous delivery of the ADS feature. Two examples of dimensions of the ODD are given and a strategy to avoid an ODD exit is proposed in the respective case.

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  • 3.
    Hadj-Bachir, Mokrane
    et al.
    ESI Group, France.
    Bagheri, Toktam
    UniqueSec AB, Sweden.
    Toss, Henrik
    RISE Research Institutes of Sweden, Safety and Transport, Vehicles and Automation.
    de Souza, Philippe
    ESI Group, France.
    Sanfridson, Martin
    RISE Research Institutes of Sweden, Safety and Transport, Measurement Technology.
    Over-the-Air Automotive Radars Hardware-in-Loop Test for Development and Validation of Active Safety Systems and Autonomous Cars2023In: 2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive), 2023, p. 205-210Conference paper (Refereed)
    Abstract [en]

    Due to the development of new radar technology for advanced driver-assistance systems (ADAS) and automated driving (AD) applications, testing radars for real world conditions is highly desirable. However, testing autonomous driving functions on public roads can be dangerous and the tests results are not always reproducible. In this paper, we present a novel Over-the-Air (OTA) Hardware-In-the-Loop (HIL) radar target simulator for testing radar systems. The complete simulation setup including hardware and software implementations will be presented in this article. We illustrate a test procedure by creating Euro NCAP scenarios, and explain the benefits and importance of realtime HIL testing of automotive radars.

  • 4.
    Sjöblom, Ted
    et al.
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    Benderius, Ola
    Chalmers University of Technology, Sweden.
    Blanch, Krister
    Chalmers University of Technology, Sweden.
    Berger, Christian
    Chalmers University of Technology, Sweden.
    Rylander, Robert
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    Karlsson, Fredrik
    Swedish Maritime Administration, Sweden.
    Olsson, Rick
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    Sanfridson, Martin
    RISE Research Institutes of Sweden, Safety and Transport, Measurement Technology.
    Toss, Henrik
    RISE Research Institutes of Sweden, Safety and Transport, Vehicles and Automation.
    Olsson, Fredrik
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    Lundman, Joakim
    RISE Research Institutes of Sweden, Safety and Transport, Maritime department.
    REEDS: Reference data and algorithms for research and development of smart ships2023Report (Other academic)
    Abstract [en]

    The Swedish Transport Administration Research and Innovation fund for Maritime research funded the project "Reference data and algorithms to support research and development of smart ships". The project goes by the working name, and is communicated as, Reeds. It responds to a synthesis of a number of different needs identified in previous projects and studies. The background to the project is that in recent years the focus has been on developing algorithms to interpret and act on the physical environment around different types of craft. In order to be able to develop and evaluate these algorithms, it has become clear that open datasets and a fair benchmarking platform are required that allow various developers in industries and researchers to evaluate algorithms. In the road vehicle sector, Kitti, as of 2013, is the largest dataset used as a reference dataset. The dataset in this project contains sensor data from several data collection occasions within a maritime context, from high-precision sensors such as cameras, radar, lidar, and IMU. For marine applications, there has been no similar dataset with anywhere near the same amount of data and time synchronisation between sensors. The reference data and reference algorithms were available periodically during the project through an online service where researchers and developers could upload their algorithms to use the dataset.

    In addition to the dataset itself, Reeds adds additional strengths compared to other reference datasets:

    -        New approach to comparing algorithms fairly, where new algorithms are always compared on a centralised hardware in a cloud service and re-evaluated when new data is added, i.e. an unbiased algorithm evaluation service.

    -        Method that combines NTP and PTP time protocols for synchronisation between the sensors with microsecond accuracy

    -        More types and more modern sensors that can be used at a higher level of abstraction and can thus be applied in more areas.

    -        Sensor fusion of both onboard and land-side sensors

    -        Identify areas of application for navigation and surveillance on land based on the algorithms developed during the project and the use of new sensor types not established in shipping.

    -         

    The project built up a maritime reference data set that enables the creation of a digital description for the ship's surrounding environment and developed reference algorithms to demonstrate new navigation and monitoring methodology in the area of "enhanced navigation".

    "Enhanced navigation" is defined under the project as the use of new technology based on developments in digitisation and autonomous functions, where new navigation methods use sensors both on board and ashore to increase maritime safety and robustness. The project has built a web-based user interface referred to in the report as "Crowsnest" that handles these new sensors and visualises this data in a familiar interface similar to an overlay in ECDIS that is openly available for the public to build on. Which was used for the evaluation and concept development of new user interfaces based on feedback from pilots and VTS operators.

    By providing reference datasets and reference algorithms with demonstrations, researchers and companies now have the opportunity to develop algorithms for the intelligent and autonomous ships of the future.

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  • 5.
    Warg, Fredrik
    et al.
    RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.
    Johansson, Rolf
    Autonomous Intelligent Driving, Sweden.
    Skoglund, Martin
    RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.
    Thorsén, Anders
    RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.
    Brännström, Mattias
    Zenuity AB, Sweden.
    Gyllenhammar, Magnus
    Zenuity AB, Sweden.
    Sanfridson, Martin
    Volvo Technology AB, Sweden.
    The Quantitative Risk Norm - A Proposed Tailoring of HARA for ADS2020In: Proceedings of 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Los Alamitos, 2020Conference paper (Refereed)
    Abstract [en]

    One of the major challenges of automated drivingsystems (ADS) is showing that they drive safely. Key to ensuringsafety is eliciting a complete set of top-level safety requirements(safety goals). This is typically done with an activity called hazardanalysis and risk assessment (HARA). In this paper we argue thatthe HARA of ISO 26262:2018 is not directly suitable for an ADS,both because the number of relevant operational situations maybe vast, and because the ability of the ADS to make decisionsin order to reduce risks will affect the analysis of exposure andhazards. Instead we propose a tailoring using a quantitative risknorm (QRN) with consequence classes, where each class has alimit for the frequency within which the consequences may occur.Incident types are then defined and assigned to the consequenceclasses; the requirements prescribing the limits of these incidenttypes are used as safety goals to fulfil in the implementation.The main benefits of the QRN approach are the ability to showcompleteness of safety goals, and make sure that the safetystrategy is not limited by safety goals which are not formulatedin a way suitable for an ADS.

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