Conference paper Open Access

Common Methodology for Data-Driven Scenario-Based Safety Assurance in the HEADSTART Project

Wagener, Nicolas

Weißensteiner, Patrick; Coget, Jean-Baptiste; Eckstein, Lutz; Bracquemond, Annie

One objective of introducing Connected and Automated Driving (CAD) functions on the roads is to
reduce  the  number  of  accidents  due  to  human  errors  by  reducing  the  tasks  of  the  driver  (partial
automation) or removing it completely from the driving system. Building safe and reliable automated
vehicles require specific testing methods that are adapted to higher levels of automation. Harmonised
European  Solutions  for  Testing  Automated  Road  Transport  (HEADSTART)  is  a  research  project
funded  by  the  European  Union  that  aims  to  define  testing  and  validation  procedures  for  CAD
functions.  HEADSTART  brings  a  methodology  for  testing  and  validating  these  functions  with
Data-Driven Scenario-Based Safety Assurance. The goal of this paper is first to present the overall
HEADSTART methodology for validating CAD safety, and then further explain three aspects of it,
such as: The database mechanics to extract and parametrize logical scenarios, the relevance metrics for
the selection of scenarios, and the allocation of scenarios for test execution.

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