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Edge conditions and crash-avoidance roles: the future of traffic safety in the world of autonomous vehicles
  1. Megan S Ryerson1,2,
  2. Jordan E Miller3,
  3. Flaura K Winston3,4
  1. 1Department of City and Regional Planning, School of Design; University of Pennsylvania, Philadelphia, Pennsylvania, USA
  2. 2Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  3. 3Center for Injury Research and Prevention, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
  4. 4Division of General Pediatrics, Department of Pediatrics, University of Pennsylvania Perlman, School of Medicine, Philadelphia, Pennsylvania, USA
  1. Correspondence to Dr Flaura K Winston, Center for Injury Research and Prevention, Children’s Hospital of Philadelphia; 2716 South Street; Philadelphia, PA 19104, USA; flaura{at}upenn.edu

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Introduction

Self-driving or highly automated vehicle (HAV) technologies, now undergoing public trials in major cities,1 are positioned to bring about transformative change to the entire transportation system. Far from being a distant innovation, retail autonomous vehicles have already been announced by various manufacturers for release as early as 2018, complementing estimates that on-road HAVs will reach market ubiquity as part of a US$7 trillion passenger economy by 2055.2 Transportation planners and policymakers are welcoming HAVs for their potential to positively impact traffic safety by fundamentally changing the interaction and relationship between drivers and vehicles, and how drivers and vehicles collect and process information from their environment. HAVs will not, however, offer safety in every possible condition. As HAV technology will have limits, manufacturers and lawmakers suggest vehicles have an operational design domain (ODD) which specifies under which conditions an autonomous driving mode can perform safely.3 ODDs may require HAVs to avoid mixed vehicle routes, inclement weather conditions or unmarked roads; in general, ODDs reflect the limits of HAV technologies. In engineering terms, these are known as ‘edge conditions’: situations that go beyond the reliable and accurate capability and limits of HAV technology. The injury prevention community must understand how these edge conditions could lead to crashes in order to formulate crash countermeasures which ultimately inform vehicle development standards and training.

The Haddon Matrix, the long-established safety paradigm for injury prevention, has a rich history of helping those focused on transportation safety explicitly separate roles and responsibilities of all drivers, technologies and environmental factors involved in a crash event.4 A new framework and modification of the Haddon Matrix is needed as man–machine–environment interactions will be facilitated by technology and roles in preventing a crash event will be much more shared. While one could argue that the Haddon Matrix was …

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