摘要：AbstractCrash frequency and severity are influenced by a variety of variables that represent regional, site, crash and driver-vehicle unit characteristics. In the traditional methods of crash prediction, all the variables are considered at a single level and the multilevel structure inherent in the crash data is ignored. Hierarchical modelling is a statistical technique that allows multilevel data structure to be properly specified and estimated. In the present study, a hierarchical modelling approach was used to estimate the crash frequency and severity of single and dual carriageway roads. Since the crash patterns of single and dual carriageways were found to be different, separate models were developed for these facilities. A two level design was adopted for crash frequency prediction and four level design for crash severity prediction. The two levels in the crash frequency prediction are geographic region level and traffic site level. The additional levels in severity prediction are crash level and driver-vehicle unit level. The study indicates that hierarchical models performed better for crash frequency and severity prediction. Hierarchical models are strongly advocated for crash data that has correlated observations within groups.
关键词：Mid-block;crash frequency prediction;crash severity prediction;hierarchical models
