A framework for definition of logical scenarios for safety assurance of automated driving

Figures & data

Figure 1. Six-layer model for scenarios (Bock et al. 2018) (reprinted with permission).

Figure 2. Database process within PEGASUS based on Zlocki et al. (2018).

Figure 3. Relative collision paths defining the base scenarios (Bock et al. 2018) (reprinted with permission).

Figure 4. High-level decision process for deriving the base scenarios.

Figure 5. Configurations of dynamic occlusions.

Table 1. Proposed nomenclature for base scenarios.

Impact location	Initial position	Path	Term
Front	1	A	Slower lead vehicle (challenger)
	2	B	Slower turn into path (challenger)
	4	C	Overtaking turn into path (challenger)
Side	2	D	Slower sideswipe (challenger)
	3	E	Sideswipe (challenger)
	4	F	Overtaking sideswipe (challenger)
Rear	2	G	Slower rear end (challenger)
	4	H	Rear end turning into path (challenger)
	5	I	Rear end (challenger)

Bock J, Krajewski R, Eckstein L, Klimke J, Sauerbier J, Zlocki A. 2018. Data basis for scenario-based validation of HAD on highways. Paper presented at: 27th Aachen Colloquium Automobile and Engine Technology; October 8–10, Aachen, Germany.

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Zlocki A, Roesener C, Klaudt S, Eckstein L. 2018. Ganzheitliche Werkzeugkette für die Entwicklung und Bewertung des automatisierten Fahrens. ATZ Extra. 23(S5):16–21.

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