High accuracy crash mapping using fuzzy logic
Accurate crash location data in crash databases can be shown to be essential for crash modelling, crash mapping, hazardous road segment identification and other studies that aim to decrease the number of crashes within a network area. In this paper a generic and high-accuracy automatic crash mapping method is developed and presented. The methodology is based on a transformed map-matching method for candidate road segment identification and on a fuzzy logic inference system for the final road segment selection. The method is implemented by employing all injury and fatal crashes that occurred during 2012 in the UK Strategic Road Network but can be transferred to other network/crash data. The accuracy of the developed method is estimated to be 98.9% (±1.1%) correct matches. The results of this method are compared to other less advanced crash mapping methods.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- Imprialou, Maria-Ioanna M
- Quddus, Mohammed
- Pitfield, David E
- Publication Date: 2014-5
Language
- English
Media Info
- Media Type: Print
- Features: Figures; Maps; References; Tables;
- Pagination: pp 107-120
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Serial:
- Transportation Research Part C: Emerging Technologies
- Volume: 42
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0968-090X
- Serial URL: http://www.sciencedirect.com/science/journal/0968090X
Subject/Index Terms
- TRT Terms: Crash data; Crash locations; Crash risk forecasting; Fuzzy logic; High risk locations; Mapping; Traffic crashes
- Geographic Terms: United Kingdom
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning; I81: Accident Statistics;
Filing Info
- Accession Number: 01528356
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 17 2014 9:03AM