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Safety at the edge: a safety framework to identify edge conditions in the future transportation system with highly automated vehicles
  1. Megan S Ryerson1,
  2. Carrie S Long2,
  3. Kristen Scudder2,
  4. Flaura K Winston3
  1. 1Department of City and Regional Planning & Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  2. 2Department of City and Regional Planning, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  3. 3Center for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
  1. Correspondence to Dr Megan S Ryerson, Department of City and Regional Planning & Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA; mryerson{at}


Automated driving systems (ADS) have the potential for improving safety but also pose the risk of extending the transportation system beyond its edge conditions, beyond the operating conditions (operational design domain (ODD)) under which a given ADS or feature thereof is specifically designed to function. The ODD itself is a function of the known bounds and the unknown bounds of operation. The known bounds are those defined by vehicle designers; the unknown bounds arise based on a person operating the system outside the assumptions on which the vehicle was built. The process of identifying and mitigating risk of possible failures at the edge conditions is a cornerstone of systems safety engineering (SSE); however, SSE practitioners may not always account for the assumptions on which their risk mitigation resolutions are based. This is a particularly critical issue with the algorithms developed for highly automated vehicles (HAVs). The injury prevention community, engineers and designers must recognise that automation has introduced a fundamental shift in transportation safety and requires a new paradigm for transportation epidemiology and safety science that incorporates what edge conditions exist and how they may incite failure. Towards providing a foundational organising framework for the injury prevention community to engage with HAV development, we propose a blending of two classic safety models: the Swiss Cheese Model, which is focused on safety layers and redundancy, and the Haddon Matrix, which identifies actors and their responsibilities before, during and after an event.

  • safety
  • technology
  • automation

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  • Contributors MSR led the organisation and framing of the manuscript, as well as the writing. CSL provided heavy writing and paper framing inputs, as well as led the development of Figure 1 (both in concept and design). KS provided research support and the development of the inputs into Figure 1. FKW provided expert guidance, shaping of the narrative and a critical review.

  • Funding This project was partially funded by Carnegie Mellon University’s Mobility21 National University Transportation Center, which is sponsored by the US Department of ransportation (69A3551747111).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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