Longitudinal Methods for Prioritizing Highway Safety Investments

Open Access
Park, Minho
Graduate Program:
Civil Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
November 06, 2012
Committee Members:
  • Venkataraman Shankar, Dissertation Advisor
  • Swagata Banerjee, Committee Chair
  • Tao Yao, Committee Member
  • Jeremy Joseph Blum, Committee Member
  • Geometric Effects
  • Crash Frequency
  • Accident Severity
  • Heterogeneous Negative Binomial Model
  • Multinomial Logit Model
This dissertation develops a statistical basis for the evaluation of crash costs associated with interstate travel in Washington State. The statistical basis consists of two components – a frequency component and a severity component. The two components are linked via a recursive modeling structure where the frequency evaluation is conducted at a segmental level. In particular, I demonstrate this evaluation at the interchange level of spacing. I evaluate the entire interstate network in Washington State, via a longitudinal analysis of crash histories for the period 1999-2007. For the nine year period, I collected geometric and traffic volume information, and evaluated crash cost bases for the most severe outcome of a crash. The frequency component is motivated by the need to fill the gap in the extant literature. Current literature is sparse if not nonexistent in terms of insights on heterogeneity in the overdispersion parameter effect at the segmental level of analysis. The overdispersion parameter is modeled as a parametric function of highway geometry, resulting in a heterogeneous negative binomial model structure. Further, to improve insights into the effects of geometry from a design policy standpoint and enhance our understanding of the performance basis of geometric elements, I develop heterogeneous negative binomial models of heterogeneous geometry – based on the definition of segmental geometry that can consist of below-standard, at-standard and above-standard design elements. By using this approach, enhanced insight is developed due to the fact that interactions between varying standards within a segment effectively capture statistical information observed from reported crashes. This is shown by improvements in likelihoods over contemporary models which employ a non-standards approach. The second major contribution of this dissertation is the severity analytical component which is built as a second stage component. In the second stage analysis, the severity models are constructed using collision type information, as opposed to the traditional approach of involving geometrics. This allows the simplification of severity models at the unconditional level to highly tractable multinomial type specifications – a computational advantage for computing efficiently the severity outcomes on entire networks. The two-stage statistical basis thus developed in this dissertation offers a plausible and tractable methodology for determining accurately cost bases for the identification of high priority safety investment corridors. The fact that multi-year histories are used in both stages implies that the findings can be potentially robust and therefore contribute to stable parameter estimation and therefore increase our confidence in our understanding of the effect of geometry and collision type on crash frequency and severity.