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Estimating the Accident Probability of a Vehicular Flow by Means of an Artificial Neural Network

Author

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  • L Mussone
  • S Rinelli
  • G Reitani

    (Department of Land Engineering, University of Pavie, 1 Via Serrata, I-27100 Pavia, Italy)

Abstract

As accidents tend to be multicausal, the interpretation of accident data can be a fairly complex task. Hence it is worth experimenting with innovative procedures in order to extrapolate patterns within such data. Accordingly, records of motorway accidents in northern Italy, stored on statistical cards, were processed by means of a neural network. The clustering ability of the latter allowed for an interpretive assessment of each input variable in terms of its influence on the number of accidents occurring.

Suggested Citation

  • L Mussone & S Rinelli & G Reitani, 1996. "Estimating the Accident Probability of a Vehicular Flow by Means of an Artificial Neural Network," Environment and Planning B, , vol. 23(6), pages 667-675, December.
    • Handle: RePEc:sae:envirb:v:23:y:1996:i:6:p:667-675
    DOI: 10.1068/b230667
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