Doctoral Dissertations

Keywords and Phrases

Decision Making; Transportation; Work Zone

Abstract

"This research provides tools and methods for integrating stakeholder input and crash data analytics to better guide transportation engineers in effective work zone design and management. Three key contributions are presented: the importance of stakeholder input in traffic management strategies, application of data mining and pattern recognition to identify high-risk drivers in work zones, and the use of multinomial logistic regression (MLR) as a tool to understand key findings from historic crash data. Work zone signage is mandated by the Manual on Uniform Traffic Control Devices (MUTCD), but the current configurations are often criticized by the driving public and state departments of transportation have questioned whether alternate signage would provide more cost-effective, equally safe options. A driving simulator study funded by the Missouri Department of Transportation (MoDOT) evaluated one such alternate sign configuration and determined that it received higher levels of driver satisfaction with no statistical impact on safety. Findings of driver preference for the alternate configuration are considered high value by MoDOT with respect to both mobility and safety. A second contribution focused on risk mitigation through data analytics. Pattern recognition and data mining techniques were applied to driving simulator data as part of a multi-criteria decision making tool to identify drivers with high risk potential. Findings related to age and gender suggest opportunities for driver education and training to increase safety. The third contribution identifies a method for analyzing historic crash data to determine key risk factors in fatality and serious injury accidents in work zones. Multinomial logistic regression (MLR) is used. Findings outline patterns and scenarios that should be integrated into work zone design to enhance safety and improve mobility with respect to work zone lighting, impact of weather, and the like"--Abstract, page iv.

Advisor(s)

Long, Suzanna, 1961-

Committee Member(s)

Corns, Steven
Qin, Ruwen
Konur, Dincer
Leu, M. C. (Ming-Chuan)

Department(s)

Engineering Management and Systems Engineering

Degree Name

Ph. D. in Engineering Management

Sponsor(s)

Missouri Department of Transportation
Missouri University of Science and Technology Intelligent Systems Center

Comments

Funding was provided by the Missouri Department of Transportation under TR201312 and TR201512.

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2018

Journal article titles appearing in thesis/dissertation

  • Evaluating work zones sign configurations using a driving simulator
  • Using a combination of multi-criteria decision- making and data mining methods for work zone safety :A case analysis
  • Work zone safety in Missouri :A statistical analysis

Pagination

xii, 89 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2018 Samareh Moradpour, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11388

Electronic OCLC #

1051223555

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