Studies from P. Nitsche et al Further Understanding of Risk Management (Pre-crash scenarios at road junctions: A clustering method for car crash data)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Researchers detail new data in Risk Management. According to news reporting out of Vienna, Austria, by VerticalNews editors, research stated, "Given the recent advancements in autonomous driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual simulation environments or on real-world test tracks."

Our news journalists obtained a quote from the research, "This paper presents a novel data analysis method including the preparation, analysis and visualization of car crash data, to identify the critical pre-crash scenarios at T- and four-legged junctions as a basis for testing the safety of automated driving systems. The presented method employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1056 junction crashes in the UK, which were exported from the in-depth 'On-the-Spot' database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions."

According to the news editors, the research concluded: "The results support existing findings on road junction accidents and provide benchmark situations for safety performance tests in order to reduce the possible number parameter combinations."

For more information on this research see: Pre-crash scenarios at road junctions: A clustering method for car crash data. Accident Analysis and Prevention, 2017;107():137-151. Accident Analysis and Prevention can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis and Prevention - www.journals.elsevier.com/accident-analysis-and-prevention/)

Our news journalists report that additional information may be obtained by contacting P. Nitsche, AIT, A-1210 Vienna, Austria. Additional authors for this research include P. Thomas, R. Stuetz and R. Welsh.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2017.07.011. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Keywords for this news article include: Vienna, Austria, Europe, Risk Management.

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