Degree Type

Dissertation

Date of Award

1993

Degree Name

Doctor of Philosophy

Department

Industrial Education and Technology

First Advisor

John A. Beno

Second Advisor

William G. Miller

Abstract

This study employed the statistical process control technique to identify high-risk intersections at each time period. The method of this study consisted of three phases. The first phase of the study measured the lateral time gap used by drivers entering a major road stream of traffic from a minor street controlled by a stop sign. The second phase of the study analyzed and interpreted the time-gap data using statistical process control methods. The third phase of the study reported high-risk intersections at each time period and attempted to identify significant factors affecting the selection of time gaps;A total of 27 stop-controlled intersections including two-by-two roads (13 sites) and two-by-four roads (14 sites) throughout Iowa were investigated involving 1,981 drivers. Intersections and their corresponding times were defined as high-risk when they had out-of-control samples each at morning, noon, or evening;The hypothesis test procedure was used as a tool to investigate special variations for the identified high risk intersections at each time period. Several factors including age of drivers, speed limits, types of vehicle, traffic volumes and transmission were related to risk-takings at the stop-controlled intersections. However, gender of drivers and presence of children were not related. Also, accidents reported for observed intersections were compared with high-intersections and the findings revealed that statistical process control techniques was a reliable tool for predicting high-risk intersections at each time period.

DOI

https://doi.org/10.31274/rtd-180813-10051

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Sang-Jin Park

Language

en

Proquest ID

AAI9414009

File Format

application/pdf

File Size

151 pages

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