Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

Author ORCID Identifier



Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Civil and Environmental Engineering

Year Degree Awarded


Month Degree Awarded


First Advisor

Michael Knodler, Jr.

Subject Categories

Transportation Engineering


Transportation Safety Planning (TSP) is a statewide-scale tool and combines transportation planning processes with safety aims to increase safety and reduce transportation fatalities and injuries. Traffic safety, which continues to remain a critical issue worldwide, has led to a myriad of modeling techniques to improve analytical capabilities with respect to crash modeling and prediction. State and metropolitan transportation planning processes must be consistent with Strategic Highway Safety Plans. This research aims to identify models and methods to improve the ability to capture variables that have the most significant impact on traffic safety through crash prediction modeling. In order to achieve this research goal, the research objectives are as follows:

  • Identify important variables in TSP.
  • Investigate different areal unit such as traffic analysis zones (TAZs) and traffic analysis districts (TADs).
  • Explore the modifiable areal unit problem (MAUP), which addresses crashes on the boundaries and autocorrelation in macro-level crash modeling.
  • Analysis of before and after crashes and testing Poisson distribution
This research explores the application of parametric and nonparametric approaches to use different models for prediction and inference, with the aim of minimizing the reducible error. Since a macro-level analysis involves aggregating crashes per spatial unit, a spatial dependence or autocorrelation may arise if a variable of a geographic region is affected by the same variable of the neighboring regions. So, this study also will explore the effect of spatial autocorrelation in modeling crashes in TAZs and TADs.