A Small-Area Approach to Construct Candidate Lists of Sites for Possible Improvements

• Activity Number: 536
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Kristian Schmidt*+ and Alicia Carriquiry
• Companies: Iowa State University and Iowa State University
• Keywords: Poisson ; Multivariate ; Hierarchical Model ; Transportation

Abstract

Improving tra?c safety is a priority of Departments of Transportation nationwide. Because every agency faces budgetary constraints, methods to identify those sites with the highest risk potential and that may respond to interventions are of special importance. The initial objective of this work is to develop an accurate approach that can be used to construct candidate lists of intersections for improvement. To do so, the methodology must take into account not only the estimated expected crash frequency (or crash rate) but also the uncertainties associated with that estimate. Special difficulties are introduced by the dimension of the data set. As not every crash falls into the same category with regard to severity, we then develop an approach to model different crash types simultaneously using a Bayesian hierarchical model based on Multivariate Poisson distributions and Gamma priors.