Abstract
Road safety is a major concern, as accidents kill on average 3,600 people per day. In order to reduce the number of road accidents, the police or local authorities jointly implement actions and measures to increase road safety. Therefore, it is necessary to analyze and predict the different circumstances of accidents comprehensively. Only with the knowledge, e.g., about the temporal pattern, locations, or road conditions, meaningful actions can be derived and implemented. A framework to support strategic planning of road safety measures is designed that consists of several consecutive data mining stages, i.e., frequent itemset mining, time series clustering, forecasting, and scoring. An informative and comprehensible presentation of the results is necessary to make them usable for the planning of measures. With a strategic road safety dashboard, we enable police managers to identify accident blackspots and especially their temporal pattern for different feature combinations.
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Meißner, K., Rieck, J. (2022). Strategic Road Safety Dashboard: Visualizing Results of Accident Data Mining. In: Trautmann, N., Gnägi, M. (eds) Operations Research Proceedings 2021. OR 2021. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-08623-6_45
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DOI: https://doi.org/10.1007/978-3-031-08623-6_45
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