Abstract
Autonomous and Semi-autonomous Machines (ASAM) can benefit mining operations. However, demonstrating acceptable levels of safety for ASAMs through exhaustive testing is not an easy task. A promising approach is scenario-based testing, which requires the Operational Design Domain (ODD) definition, i.e., environmental, time-off-day, and traffic characteristics. Currently, an ODD specification exists for Automated Driving Systems (ADS), but, as it is, such specification is not adequate enough for describing the mine nuances. This paper presents a context-specific ODD taxonomy called ODD-UM, which is suitable for underground mining operational conditions. For this, we consider the ODD taxonomy provided by the British Publicly Available Specification PAS 1883:2020. Then, we identify attributes included in the standard ISO 17757:2019 for ASAM safety and use them to adapt the original ODD to the needs of underground mining. Finally, the adapted taxonomy is presented as a checklist, and items are selected according to the data provided by the underground mining sector. Our proposed ODD-UM provides a baseline that facilitates considering the actual needs for autonomy in mines by leading to focused questions.
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References
Austin, T.: On behalf of NSPE: Letter to Dr. Steven E. Shladover (2016). https://www.nspe.org/sites/default/files/resources/pdfs/Shladover%20Ltr-2016-Feb5-FINAL.pdf
Baumgart, S., Fröberg, J., Punnekkat, S.: Analyzing hazards in system-of-systems: described in a quarry site automation context. In: 2017 Annual IEEE International Systems Conference (SysCon), pp. 1–8. IEEE (2017)
British Standards Institution: PAS 1880:2020. Guidelines for developing and assessing control systems for automated vehicles (2020). https://www.bsigroup.com/en-GB/CAV/pas-1880/
British Standards Institution: PAS 1883:2020. Operational Design Domain (ODD) taxonomy for an automated driving system (ADS) - Specification (2020). https://www.bsigroup.com/en-GB/CAV/pas-1883/
Bussemaker, K.: Sensing requirements for an automated vehicle for highway and rural environments. Master’s thesis, Delft University of Technology (2014)
Castellanos Ardila, Julieth Patricia, Gallina, Barbara: Separation of concerns in process compliance checking: divide-and-conquer. In: Yilmaz, Murat, Niemann, Jörg., Clarke, Paul, Messnarz, Richard (eds.) EuroSPI 2020. CCIS, vol. 1251, pp. 135–147. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-56441-4_10
Colwell, I.: Runtime restriction of the operational design domain: a safety concept for automated vehicles. Master’s thesis, University of Waterloo (2018)
Czarnecki, K.: Operational design domain for automated driving systems: Taxonomy of basic terms. Waterloo Intelligent Systems Engineering (WISE) Lab, University of Waterloo, Canada (2018)
Global Mining Guidelines Group (GMG): Guideline for the implementation of autonomous systems in mining (2019). https://gmggroup.org/guidelines-and-publications/guideline-for-the-implementation-of-autonomous-systems-in-mining/
Gyllenhammar, M., et al.: Towards an operational design domain that supports the safety argumentation of an automated driving system. In: 10th European Congress on Embedded Real Time Systems (ERTS 2020) (2020)
ISO/TC 127/SC 2: ISO 17757:2019. Earth-moving machinery and mining - Autonomous and semi-autonomous machine system safety (2019). https://www.iso.org/standard/76126.html
ISO/TC 22/SC 33: ISO/CD 34503 (Under Development). Road vehicles - Taxonomy for operational design domain for automated driving systems. https://www.iso.org/standard/78952.html
Ito, M.: Odd description methods for automated driving vehicle and verifiability for safety. J. Univ. Comput. Sci. 27(8), 796–810 (2021)
Kalra, N., Paddock, S.M.: Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transp. Res. Part A Policy Practice 94, 182–193 (2016)
Kini, R.R.: Sensor position optimization for multiple LiDARs in autonomous vehicles. Master’s thesis, KTH Royal Institute of Technology (2020)
Koopman, P., Fratrik, F.: How many operational design domains, objects, and events? In: SafeAI-AAAI Workshop on Artificial Intelligence Safety (2019)
Lee, C.W., Nayeer, N., Garcia, D.E., Agrawal, A., Liu, B.: Identifying the operational design domain for an automated driving system through assessed risk. In: 2020 IEEE Intelligent Vehicles Symposium (IV), pp. 1317–1322. IEEE (2020)
Levinson, J., et al.: Towards fully autonomous driving: systems and algorithms. In: 2011 IEEE Intelligent Vehicles Symposium (IV), pp. 163–168. IEEE (2011)
Linder, J., Subbiah, P.: Deriving contextual definition and requirements from use cases of autonomous drive. Master’s thesis, Chalmers University of Technology and University of Gothenburg (2021)
Machado, T., Ahonen, A., Ghabcheloo, R.: Towards a standard taxonomy for levels of automation in heavy-duty mobile machinery. In: Fluid Power Systems Technology, vol. 85239. American Society of Mechanical Engineers (2021)
Nalic, D., Mihalj, T., Bäumler, M., Lehmann, M., Eichberger, A., Bernsteiner, S.: Scenario based testing of automated driving systems: a literature survey. In: FISITA web Congress (2020)
National Highway Traffic Safety Administration: Automated driving systems 2.0: A vision for safety. US Department of Transportation 812, 442 (2017)
Pries-Heje, J., Johansen, J.: The SPI Manifesto (2010). https://conference.eurospi.net/images/eurospi/spi_manifesto.pdf
SAE International: SAE J3016:2021. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (2021). https://www.sae.org/standards/content/j3016_202104
Thorn, E., Kimmel, S.C., Chaka, M., Hamilton, B.A., et al.: A framework for automated driving system testable cases and scenarios. Technical report, United States. National Highway Traffic Safety Administration (2018)
Tiusanen, R., Heikkilä, E., Malm, T.: System safety engineering approach for autonomous mobile machinery. In: Crespo Márquez, A., Komljenovic, D., Amadi-Echendu, J. (eds.) WCEAM 2019. LNME, pp. 239–251. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-64228-0_21
Ulbrich, S., Menzel, T., Reschka, A., Schuldt, F., Maurer, M.: Defining and substantiating the terms scene, situation, and scenario for automated driving. In: 18th International Conference on Intelligent Transportation Systems, pp. 982–988. IEEE (2015)
Acknowledgment
This research has been supported by Vinnova via the project ESCAPE-CD (Efficient Safety for Complex Autonomous Production Environments - Concept Design) Reference: 2021-03662. We thank our industrial partner in the project - Boliden Mineral AB- for the preliminary review of the proposed taxonomy.
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Castellanos-Ardila, J.P., Punnekkat, S., Fattouh, A., Hansson, H. (2022). A Context-Specific Operational Design Domain for Underground Mining (ODD-UM). In: Yilmaz, M., Clarke, P., Messnarz, R., Wöran, B. (eds) Systems, Software and Services Process Improvement. EuroSPI 2022. Communications in Computer and Information Science, vol 1646. Springer, Cham. https://doi.org/10.1007/978-3-031-15559-8_12
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