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|Title:||Extracting Traffic Safety Knowledge from Historical Accident Data||Authors:||Gregoriades, Andreas
|Keywords:||Self-Organizing-Maps;Traffic Accidents Heat-maps;Accident Warnings||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||15-Jan-2018||Source:||14th International Conference on Location Based Services (LBS 2018), Zurich, Switzerland, January 15-17, 2018||Conference:||International Conference on Location Based Services||Abstract:||This paper presents a method and a tool for analyzing historical traffic accident records using data mining techniques for the extraction of valuable knowledge for traffic safety management. The knowledge is dis-tilled using spatio-temporal analysis of historical accidents records. Raw accident data, obtained from Police records, underwent pre-processing and subsequently integrated with secondary traffic-flow data from a mesoscopic simulation. Clustering analysis was performed with self-organizing maps (SOM) to identify accident black spots on the road network and visualizethis on a map. Distilled knowledge is used to develop a prototype mobile application to warn drivers of accident risk in real time||URI:||https://ktisis.cut.ac.cy/handle/10488/18393||DOI:||10.3929/ethz-b-000225600||Collaboration :||Cyprus University of Technology
European University Cyprus
|Rights:||ETH Zurich||Type:||Conference Papers|
|Appears in Collections:||Δημοσιεύσεις σε συνέδρια /Conference papers - poster -presentation|
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