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Identifying conflict clusters of cyclists at a roundabout by automated traffic surveillance

Saul, H. ; Junghans, M. ; Hoffmann, R.

Originalveröffentlichung: (2017) 7th International Conference on ESAR "Expert Symposium on Accident Research" 2016
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Dokument 1.pdf (646 KB)

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Freie Schlagwörter (Deutsch): Analyse (math) , Beinahe Unfall , Deutschland , Digitale Bildverarbeitung , Konferenz , Kreisverkehrsplatz , Ort (Position) , Radfahrer , Unfallschwerpunkt , Verfahren , Verhalten
Freie Schlagwörter (Englisch): Accident black spot , Analysis (math) , Behaviour , Conference , Cyclist , Digital image processing , Germany , Image analysis , Image generation , Method , Near miss , Position , Roundabout
Collection 1: BASt-Beiträge / Tagungen / International Conference on ESAR / 7th International Conference on ESAR
Collection 2: BASt-Beiträge / ITRD Sachgebiete / 83 Unfall und Mensch
Collection 3: BASt-Beiträge / ITRD Sachgebiete / 82 Unfall und Verkehrsinfrastruktur
Institut: Sonstige
DDC-Sachgruppe: Ingenieurwissenschaften
Sonstige beteiligte Institution: Institut für Verkehrssystemtechnik
Dokumentart: InProceedings (Aufsatz / Paper einer Konferenz etc.)
Sprache: Englisch
Erstellungsjahr: 2017
Publikationsdatum: 17.10.2017
Kurzfassung auf Englisch: Cyclists are more likely to be injured in fatal crashes than motorised vehicles. To gain detailed and precise behavioural data of road users, i.e. trajectories, a measuring campaign was conducted. Therefore, a black-spot for accidents with cyclists in Berlin, Germany was selected. The traffic has been detected by a fully automated traffic video analysis system continuously for twelve hours. The video surveillance system is capable of automatically extracting trajectories, classifying road user types and precise determining and positioning of conflicts and accidents. Additionally, pre-conflict and pre-accident situations could be analysed to provide further in-depth understanding of accident causation. The evaluation of the measuring campaign comprised the investigation of traffic parameters, e.g. traffic flow, as well as traffic-safety related parameters based on Surrogate Safety Measures (SSM). Furthermore, the spatial and temporal distributions of conflicts involving cyclists were determined. As a result, three possible conflict clusters could be identified, of which one cluster could be confirmed by detailed video analysis, showing conflicts caused by right turning vehicles.