Identification of hotspots on roads using continual variance analysis
| Autor: | Dejan Anđelković, Krsto Lipovac, Boris Antic, Ilija Tanackov |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
frequency of traffic accidents
Identification methods 050210 logistics & transportation TA1001-1280 Operations research hotspots on the roads Traffic accident Mechanical Engineering HSID methods 05 social sciences Statistical model traffic accidents Transportation engineering traffic safety Kilometer 0502 economics and business Automotive Engineering Statistics Hotspot (geology) Environmental science 0501 psychology and cognitive sciences Analysis of variance continual analysis of variance 050107 human factors |
| Zdroj: | Transport; Vol 33 No 2 (2018); 478–488 Transport, Vol 33, Iss 2 (2018) |
| ISSN: | 1648-3480 1648-4142 |
| DOI: | 10.3846/16484142.2017.1289479 |
| Popis: | This paper presents a new statistical model for the identification of dangerous locations (subsections) on roads, also known as hotspots. The model is based on continual analysis of variance. The variance parameter has the potential for the synthesis of quantity and quality, especially regarding traffic accident frequencies and the consequences of traffic accidents within subsections and the significant comparison of the produced synthesis. The sensitivity of the suggested model can be adjusted with the level of disjunction and the length of subsections. A practical application of the new model is performed using a sample of 8442 traffic accidents, of which 6079 were Property Damage Only (PDO) accidents, 2041 resulted in injuries and 322 resulted in fatalities. The sample is for the period of 2001 to 2011 and is from an ‘I class’ two lane rural state road in the Serbia with total length of 284 kilometres. The results acquired using the continual analysis of variance were compared with previous results from four HotSpot Identification Methods (HSID) that are also based on the frequency of traffic accidents. First published online 12 April 2017 |
| Databáze: | OpenAIRE |
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