Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2388
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dc.contributor.authorChattaraj, U-
dc.contributor.authorGarnaik, M M-
dc.date.accessioned2015-12-03T07:10:33Z-
dc.date.available2015-12-03T07:10:33Z-
dc.date.issued2015-11-
dc.identifier.citationThe Eighth International Structural Engineering and Construction Conference, (ISEC-8), Sydney, Australia, 23-28 Nov 2015en_US
dc.identifier.urihttp://hdl.handle.net/2080/2388-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractRoad accident prediction plays an important role in accessing and improving the road safety. Fuzzy logic is one of the popular techniques in the broad field of artificial intelligence and ability to improve performance similar to human reasoning and describe complex systems in linguistic terms instead of numerical values. In this study, a system was established based on Fuzzy Inference System (FIS) in which output data such as traffic Accident Rate (AR) and input data such as various highway geometric parameters. The study was conducted on two road segment from plain and rolling terrain highway and two road segments from hilly and mountainous terrain highway within the rural area of the Indian Territory. Two Highway Accident Rate Prediction Models (HARPMPRT and HARPMHMT) were developed due to the complexity of geometric parameters of rural highway on different terrain conditions which takes horizontal radius, superelevation, K-value, vertical grade and visibility as input variables and Accident Rate (AR) as output variables. The findings show that the proposed model can be effectively applied as a useful Road Safety tool capable of identifying risk factors related to the characteristics of the road and great support to the decision making of incident management in Intelligent Transportation Systems.en_US
dc.language.isoenen_US
dc.subjectTopographic Surveyen_US
dc.subjectFuzzy Logicen_US
dc.subjectAccident Rateen_US
dc.subjectDigital Terrain Modelen_US
dc.subjectTriangulation Integrated Networken_US
dc.subjectHorizontal Radiusen_US
dc.subjectDeflection Angleen_US
dc.subjectHorizontal Arc Lengthen_US
dc.subjectSuperelevationen_US
dc.titleEffect of Highway Geometrics on Accident Modelingen_US
dc.typeArticleen_US
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