The development of a quantitative intersection aggressiveness propensity index (API) is described in this paper. The index is intended to capture the overall propensity for aggressive driving to be experienced at a given signalized intersection. The index is a latent quantity that can be estimated from observed environmental, situational and driving behavior variables using structural equations modeling techniques. An empirical study of 10major signalized intersections in the greater Washington DC metropolitan area was conducted to illustrate the approach. The API is shown to provide(a) an approach for capturing and quantifying aggressive driving behaviorgiven certain measurements taken at a particular intersection, (b) understanding of the factors and intersection characteristics that may affect aggressiveness, and (c) an index for the cross comparison of different traffic areas with different features. This index has the potential to support safety policy analysis and decision-making. (A) Reprinted with permission from Elsevier.
Abstract