Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4978752 | Accident Analysis & Prevention | 2017 | 11 Pages |
Abstract
The paper deals with the identification of factors affecting crash severity level at urban road intersections. Two official crash records together with a weather database, a traffic data source with data aggregated into 5Â min intervals, and further information characterising the investigated urban intersections were used. Analyses were performed by using a back propagation neural network model and a generalized linear mixed model that enable the impact assessment of flow and other variables. Both methods demonstrate that flows play a role in the prediction of severity levels
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Authors
L. Mussone, M. Bassani, P. Masci,