Sippl et al 2016a - Revision history

Scipediacontent at 07:06, 2 February 2021

2021-02-02T07:06:22Z

Scipediacontent at 09:58, 25 January 2021

2021-01-25T09:58:31Z

Scipediacontent at 15:02, 21 January 2021

2021-01-21T15:02:30Z

Scipediacontent: Scipediacontent moved page Draft Content 282915430 to Sippl et al 2016a

2020-10-14T14:35:45Z

Scipediacontent moved page Draft Content 282915430 to Sippl et al 2016a

Scipediacontent: Created page with " == Abstract == Part 3: Practical Applications International audience Within this paper we present a new concept on deriving test cases from simulation data and outline cha..."

2020-10-14T14:35:42Z

Created page with " == Abstract == Part 3: Practical Applications International audience Within this paper we present a new concept on deriving test cases from simulation data and outline cha..."

New page

== Abstract ==

Part 3: Practical Applications International audience Within this paper we present a new concept on deriving test cases from simulation data and outline challenging tasks when testing and validating fully automated driving functions and Advanced Driver Assistance Systems (ADAS). Open questions on topics like virtual simulation and identification of relevant situations for consistent testing of fully automated vehicles are given. Well known criticality metrics are assessed and discussed with regard to their potential to test fully automated vehicles and ADAS. Upon our knowledge most of them are not applicable to identify relevant traffic situations which are of importance for fully automated driving and ADAS. To overcome this limitation, we present a concept including filtering and rating of potentially relevant situations. Identified situations are described in a formal, abstract and human readable way. Finally, a situation catalogue is built up and linked to system requirements to derive test cases using a Domain Specific Language (DSL).

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_282915430-beopen1049-5406-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf] under the license cc-by

← Older revision		Revision as of 07:06, 2 February 2021
Line 7:		Line 7:

	== Full document ==		== Full document ==
−	<pdf>Media:Sippl_et_al_2016a-~~beopen1110~~-~~2207~~-document.pdf</pdf>	+	<pdf>Media:Sippl_et_al_2016a-beopen4739-1576-document.pdf</pdf>

← Older revision		Revision as of 09:58, 25 January 2021
Line 7:		Line 7:

	== Full document ==		== Full document ==
−	<pdf>Media:Sippl_et_al_2016a-~~beopen1235~~-~~4394~~-document.pdf</pdf>	+	<pdf>Media:Sippl_et_al_2016a-beopen1110-2207-document.pdf</pdf>

@@ Line 2: / Line 2: @@
 == Abstract ==
-Part 3: Practical Applications  International audience  Within this paper we present a new concept on deriving test cases from simulation data and outline challenging tasks when testing and validating fully automated driving functions and Advanced Driver Assistance Systems (ADAS). Open questions on topics like virtual simulation and identification of relevant situations for consistent testing of fully automated vehicles are given. Well known criticality metrics are assessed and discussed with regard to their potential to test fully automated vehicles and ADAS. Upon our knowledge most of them are not applicable to identify relevant traffic situations which are of importance for fully automated driving and ADAS. To overcome this limitation, we present a concept including filtering and rating of potentially relevant situations. Identified situations are described in a formal, abstract and human readable way. Finally, a situation catalogue is built up and linked to system requirements to derive test cases using a Domain Specific Language (DSL).
+Part 3: Practical Applications; International audience; Within this paper we present a new concept on deriving test cases from simulation data and outline challenging tasks when testing and validating fully automated driving functions and Advanced Driver Assistance Systems (ADAS). Open questions on topics like virtual simulation and identification of relevant situations for consistent testing of fully automated vehicles are given. Well known criticality metrics are assessed and discussed with regard to their potential to test fully automated vehicles and ADAS. Upon our knowledge most of them are not applicable to identify relevant traffic situations which are of importance for fully automated driving and ADAS. To overcome this limitation, we present a concept including filtering and rating of potentially relevant situations. Identified situations are described in a formal, abstract and human readable way. Finally, a situation catalogue is built up and linked to system requirements to derive test cases using a Domain Specific Language (DSL).
 Document type: Part of book or chapter of book
 == Full document ==
-<pdf>Media:Draft_Content_282915430-beopen1049-5406-document.pdf</pdf>
+<pdf>Media:Sippl_et_al_2016a-beopen1235-4394-document.pdf</pdf>
@@ Line 14: / Line 14: @@
 The different versions of the original document can be found in:
-* [https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf] under the license cc-by
+* [https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf https://hal.inria.fr/hal-01643731/file/419911_1_En_12_Chapter.pdf] under the license https://creativecommons.org/licenses/by

← Older revision	Revision as of 14:35, 14 October 2020
(No difference)