Masters Theses

Daxiao Liu

Abstract

"Observational before-after evaluation of roadway safety treatments effect is a necessary and challenging study area for traffic safety engineers. In decades, empirical Bayesian approach has been widely adopted among researchers in this area. In this approach, the researcher combined before period observation data with a safety performance function estimated from similar groups to estimate the expected number of crashes that would have occurred in the after period without the treatment. Comparing this estimate with the number of crashes observed in the after period, the researcher evaluated the effectiveness of the treatment. This approach accounts for well-known regression-to-the-mean effects. However, as a result of the recent progress in numerical methods made in recent years, more attention has been given on the fully Bayesian approach.

The fully Bayesian approach implemented via hierarchical models is believed to have more advantages over the empirical Bayesian approach. The fully Bayesian approach required less data for untreated reference sites, it better accounts for uncertainty in data used, and it provides more detailed causal inferences and more flexibility in selecting crash count distributions.

The objective of this study is to compare the differences of the empirical Bayesian procedure and the fully Bayesian procedure for before-after road safety evaluation studies. An illustrative example is included with a step-by-step procedure for both approaches. Throughout three approaches in the example, the estimated safety effects are calculated for MODOT's reference"--Abstract, page iii.

Advisor(s)

Baik, Hojong

Committee Member(s)

Luna, Ronaldo
Edara, Praveen K. (Praveen Kumar)

Department(s)

Civil, Architectural and Environmental Engineering

Degree Name

M.S. in Civil Engineering

Sponsor(s)

  • Missouri. Department of Transportation
  • Missouri University of Science and Technology. Department of Civil & Environmental Engineering

Publisher

Missouri University of Science and Technology

Publication Date

2010

Pagination

viii, 72 pages

Note about bibliography

Includes bibliographical references (pages 69-71).

Geographic Coverage

Missouri

Rights

© 2010 Daxiao Liu, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Traffic safety -- Statistical methods
Traffic safety -- Research -- Statistical methods
Traffic safety -- Missouri
Bayesian statistical decision theory

Thesis Number

T 10276

Print OCLC #

870999481

Electronic OCLC #

908844732

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