  The project Automated Unmanned Protective Vehicle for Highway Hard Shoulder
Road Works (aFAS) aims to develop an unmanned protective vehicle to reduce the
risk of injuries due to crashes for road workers. To ensure functional safety
during operation in public traffic the system shall be developed following the
ISO 26262 standard. After defining the functional range in the item definition,
a hazard analysis and risk assessment has to be done. The ISO 26262 standard
gives hints how to process this step and demands a systematic way to identify
system hazards. Best practice standards provide systematic ways for hazard
identification, but lack applicability for automated vehicles due to the high
variety and number of different driving situations even with a reduced
functional range. This contribution proposes a new method to identify hazardous
events for a system with a given functional description. The method utilizes a
skill graph as a functional model of the system and an overall definition of a
scene for automated vehicles to identify potential hazardous events. An adapted
Hazard and Operability Analysis approach is used to identify system
malfunctions. A combination of all methods results in operating scenes with
potential hazardous events. These can be assessed afterwards towards their
criticality. A use case example is taken from the current development phase of
the project aFAS.
