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Traffic

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Client:
Federal Roads Office FEDRO, Switzerland
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traffic_PURNA
 
 
 
 
 
Project:
Development, application and evaluation of a method for predicting the risk of accidents on national roads
Period:
2013 – 2014
Partner:
ETH Zürich (lead)
The project involves the development of a model for predicting the risk of accidents on the Swiss national road network (class 1 and 2).
The model is based on Bayesian networks and can be used to predict the probability of occurrence and the number of accidents involving personal injury. The results are displayed in a geo-referenced manner.
 
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Client:
Austrian Road Safety Board KfV, Austria
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traffic_KfV
 
 
 
 
Project:
Standardized approaches to data representation and development of models for risk assessment
Period:
2011
Partner:
ETH Zürich (lead)
The KfV provided data that was used to develop a model for accident prediction on a defined highway route. This model is based on an innovative concept and considered to be a prototype offering strong potential for a more accurate prediction of accident occurrences also in other areas. The examination is of highly scientific value because an equivalent model providing similar predictive results is not yet available.


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