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https://hdl.handle.net/20.500.14279/18393| Title: | Extracting Traffic Safety Knowledge from Historical Accident Data | Authors: | Gregoriades, Andreas Chrystodoulides, Andreas |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Self-Organizing-Maps;Traffic Accidents Heat-maps;Accident Warnings | Issue Date: | 15-Jan-2018 | Source: | 14th International Conference on Location Based Services (LBS 2018), Zurich, Switzerland, January 15-17, 2018 | Start page: | 109 | End page: | 114 | 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://hdl.handle.net/20.500.14279/18393 | DOI: | 10.3929/ethz-b-000225600 | Rights: | ETH Zurich | Type: | Conference Papers | Affiliation : | Cyprus University of Technology European University Cyprus |
Publication Type: | Peer Reviewed |
| Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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