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Analysis and Investigation Method for All Traffic Scenarios (AIMATS)

Erbsmehl, Christian ; Lubbe, Nils ; Ferson, Niels ; Yuasa, Hitoshi ; Landgraf, Tom ; Urban, Martin

Originalveröffentlichung: (2017) 7th International Conference on ESAR "Expert Symposium on Accident Research" 2016
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Dokument 1.pdf (1.730 KB)

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Freie Schlagwörter (Deutsch): Analyse (math) , Aufzeichnung , Beinahe Unfall , Deutschland , Kamera , Konferenz , Tier , Unfallschwerpunkt , Verfahren
Freie Schlagwörter (Englisch): Accident black spot , Analysis (math) , Animal , Camera , Conference , Germany , Method , Near miss , Recording
Collection 1: BASt-Beiträge / Tagungen / International Conference on ESAR / 7th International Conference on ESAR
Collection 2: BASt-Beiträge / ITRD Sachgebiete / 80 Unfallforschung
Institut: Sonstige
DDC-Sachgruppe: Ingenieurwissenschaften
Sonstige beteiligte Institution: Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme (Dresden)
Dokumentart: InProceedings (Aufsatz / Paper einer Konferenz etc.)
Sprache: Deutsch
Erstellungsjahr: 2017
Publikationsdatum: 06.10.2017
Bemerkung: Außerdem beteiligt: Toyota Motors Europe, Research & Development
Kurzfassung auf Englisch: Millions of kilometers are driven and recorded by car manufacturers and researchers every year to gather information about realistic traffic situations. The focus of these studies is often the recording of critical situations to create test scenarios for the development of new systems before introducing them into the market. This paper shows a novel Analysis and Investigation Method for All Traffic Scenarios (AIMATS) based on real traffic scenes. It also shows how to get detailed information about speeds, trajectories and behavior of all participants without driving thousands of kilometers at the example of conflict situations with animals. Basis of the AIMATS is the identification of the most relevant locations as "Points of Interest" (POI), the recording of the critical situations and their "base lines" at these POI. This paper presents a new method to identify critical scenarios involving both vehicles and animals as well as preliminary results of a study done in Saxony using this new method.