Doctoral Dissertations
Keywords and Phrases
Autocorrelation; Autoregressive; Crash Frequency Model; Generalized Estimation Equation; Longitudinal Analysis; Temporal Correlation
Abstract
"This study comprises mainly of three papers. First, a systematic evaluation of the effects of Missouri's Strategic Highway Safety Plan between 2004 and 2007 is presented. Negative binomial regression models were developed for the before-through-change conditions for the various collision types and crash severities. The models were used to predict the expected number of crashes assuming with and without the implementation of MSHSP. This procedure estimated significant reductions of 10% in crashes frequency and a 30% reduction for fatal crashes. Reductions in the number of different collision types were estimated to be 18-37%. The results suggest that the MSHSP was successful in decreasing fatalities.
Second, ten years (2002 - 2011) of Missouri Interstate highway crash data was utilized to develop a longitudinal negative binomial model using generalized estimating equation (GEE) procedure. This model incorporated the temporal correlations in crash frequency data was compared to the more traditional NB model and was found to be superior. The GEE model does not underestimate the variance in the coefficient estimates, and provides more accurate and less biased estimates. Furthermore, the autoregressive correlation structure used for the temporal correlation of the data was found to be an appropriate structure for longitudinal type of data used in this study.
Third, this study developed another longitudinal negative binomial model that takes into account the seasonal effects of crash causality factors using Missouri crash data. A GEE with autoregressive correlation structure was used again for model estimation. The results improves the understanding of seasonality and whether the magnitude and/or type of various effects are different according to climatic changes. It was found that the traffic volume has a higher effect in increasing the crash occurrence in spring and lower effect in winter, compared to fall season. The crash reducing effect of better pavements was found to be highest in spring season followed by summer and winter, compared to the fall season. The results suggest that winter season has the highest effect in increasing crash occurrences followed by summer and spring"--Abstract, page v.
Advisor(s)
Samaranayake, V. A.
Bham, Ghulam
Committee Member(s)
Luna, Ronaldo
Paige, Robert
Gosavi, Abhijit
Department(s)
Civil, Architectural and Environmental Engineering
Degree Name
Ph. D. in Civil Engineering
Publisher
Missouri University of Science and Technology
Publication Date
2014
Journal article titles appearing in thesis/dissertation
- Safety effect of Missouri's strategic highway safety plan - Missouri's blueprint for safer roadways
- Crash frequency modeling using negative binomial models: An application of generalized estimating equation to longitudinal data
- Seasonal effects of crash contributing factors on highway safety
Pagination
x, 143 pages
Note about bibliography
Includes bibliographic references.
Geographic Coverage
Missouri
Rights
© 2014 Mojtaba Ale Mohammadi, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Subject Headings
Traffic safety -- Research -- MissouriTraffic safety -- Missouri -- Statistical methodsTraffic accidents -- Missouri -- Statistical methodsLongitudinal method
Thesis Number
T 10852
Electronic OCLC #
953972914
Recommended Citation
Ale Mohammadi, Mojtaba, "Longitudinal analysis of crash frequency data" (2014). Doctoral Dissertations. 2498.
https://scholarsmine.mst.edu/doctoral_dissertations/2498