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An analysis of urban road traffic safety in the city of Stockholm - the use of aggregate time-series models with the TRIO programme Tegner, Göran

Av: Serie: VTI konferensUtgivningsinformation: Statens väg- och transportforskningsinstitut, 2001; VTI konferens, Beskrivning: nr 15A, s. 730-85Ämnen: Bibl.nr: VTI P7000:15ALocation: Abstrakt: There is not one single factor that determines the development of road accidents. In contrary, there exists a certain "pattern" that helps us to explain and understand how and why road accidents occur. The traffic environment is changing all the time and humans adapt to new or altered circumstances. This study aims at capturing some of these determining factors and to explain the development of road accidents in a broader perspective. This DRAG-3 model for the city of Stockholm does not give all the answers. But, hopefully, it contributes to an enhanced understanding of "why" and "how much" road accidents occur. In the DRAG-3 Stockholm Study, police-reported road accidents have been analysed from January 1970 to December 1998, i.e. a time series period of 348 months. A database of some hundred possible explanatory variables has been collected, of which some 40 variables are included in the forecasting model developed within this project.
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There is not one single factor that determines the development of road accidents. In contrary, there exists a certain "pattern" that helps us to explain and understand how and why road accidents occur. The traffic environment is changing all the time and humans adapt to new or altered circumstances. This study aims at capturing some of these determining factors and to explain the development of road accidents in a broader perspective. This DRAG-3 model for the city of Stockholm does not give all the answers. But, hopefully, it contributes to an enhanced understanding of "why" and "how much" road accidents occur. In the DRAG-3 Stockholm Study, police-reported road accidents have been analysed from January 1970 to December 1998, i.e. a time series period of 348 months. A database of some hundred possible explanatory variables has been collected, of which some 40 variables are included in the forecasting model developed within this project.

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