Title page for ETD etd-12192008-163243


Type of Document Master's Thesis
Author Kennedy, Jason Forrest
Author's Email Address jfkenned@vt.edu
URN etd-12192008-163243
Title Estimating Pedestrian Crashes at Urban Signalized Intersections
Degree Master of Science
Department Civil Engineering
Advisory Committee
Advisor Name Title
Rakha, Hesham Ahmed Committee Chair
Hancock, Kathleen L. Committee Member
Inge, Patches Johnson Committee Member
Kikuchi, Shinya Committee Member
Murray-Tuite, Pamela M. Committee Member
Keywords
  • Crash modeling
  • Exposure to risk
  • Signalized intersections
  • Crash risk estimation
  • Pedestrian crashes
Date of Defense 2008-12-10
Availability unrestricted
Abstract
Crash prediction models are used to estimate the number of crashes using a set of explanatory variables. The highway safety community has used modeling techniques to predict vehicle-to-vehicle crashes for decades. Specifically, generalized linear models (GLMs) are commonly used because they can model non-linear count data such as motor vehicle crashes. Regression models such as the Poisson, Zero-inflated Poisson (ZIP), and the Negative Binomial are commonly used to model crashes. Until recently very little research has been conducted on crash prediction modeling for pedestrian-motor vehicle crashes. This thesis considers several candidate crash prediction models using a variety of explanatory variables and regression functions. The goal of this thesis is to develop a pedestrian crash prediction model to contribute to the field of pedestrian safety prediction research. Additionally, the thesis contributes to the work done by the Federal Highway Administration to estimate pedestrian exposure in urban areas. The results of the crash prediction analyses indicate the pedestrian-vehicle crash model is similar to models from previous work. An analysis of two pedestrian volume estimation methods indicates that using a scaling technique will produce volume estimates highly correlated to observed volumes. The ratio of crash and exposure estimates gives a crash rate estimation that is useful for traffic engineers and transportation policy makers to evaluate pedestrian safety at signalized intersections in an urban environment.
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