Masters Theses

Abstract

"This study examined the variables related to roadway geometry, environmental, driver and traffic factors to identify crash causal factors. It relied on three years of crash data from the Arkansas Highway Transportation Department (AHTD) and analyzed nonjunctions of rural and urban US highway systems. In the first part of this study, negative binomial modeling technique was used to model the frequency of crash occurrence. To further analyze the crash factors this study also analyzed crash severity and collision types. The second part identified the factors responsible for severe crashes and fatalities including using the binary logistic regression modeling technique. The third part used the multinomial logistic regression modeling technique to identify the factors associated with specific collision types (single vehicle, head-on, rear-end, sideswipe-same, and sideswipe-opposite direction).

The crash data were analyzed statistically, and the factors significant for crash frequency proved to be surface width, roughness, left and right shoulder widths, road segment length, and Annual Average Daily Traffic. Driver related factors such as age, gender, restraint type, and alcohol consumption were significant in severe crashes. Variables such as horizontal and vertical road curvature, wet road surface, and darkness differentiated single-vehicle collisions from multi-vehicle collisions. This study clearly indicated the importance of using different analysis techniques to identify the main factors responsible for crashes"--Abstract, page iii.

Advisor(s)

Bham, Ghulam

Committee Member(s)

Leu, M. C. (Ming-Chuan)
Samaranayake, V. A.

Department(s)

Civil, Architectural and Environmental Engineering

Degree Name

M.S. in Civil Engineering

Sponsor(s)

  • Arkansas. State Highway & Transportation Department
  • Mack-Blackwell National Rural Transportation Study Center (U.S.)

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2010

Pagination

x, 75 pages

Note about bibliography

Includes bibliographical references (pages 71-74).

Rights

© 2010 Bhanu Sireesha Javvadi, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Library of Congress Subject Headings

Traffic accidents -- Research -- Statistical methods
Traffic accidents -- Statistical methods
Traffic safety -- Research -- Statistical methods
Traffic safety -- Statistical methods

Thesis Number

T 10274

Print OCLC #

863154038

Electronic OCLC #

908695228

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu:80/record=b10158440~S5

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