Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Decision-making under extreme *uncertainty: Rethinking hazard -related perceptions and action

Understanding who evacuates and who does not has been one of the cornerstones of research on the pre-impact phase of both natural and technological hazards. Its history is rich in descriptive illustrations focusing on lists of characteristics of those who flee to safety. Early models of evacuation focused almost exclusively on the relationship between whether warnings were heard and ultimately believed and evacuation behavior. How people came to believe these warnings and even how they interpreted the warnings were not incorporated. In fact, the individual seemed almost removed from the picture with analysis focusing exclusively on external measures. ^ This study built and tested a more comprehensive model of evacuation that centers on the decision-making process, rather than decision outcomes. The model focused on three important factors that alter and shape the evacuation decision-making landscape. These factors are: individual level indicators which exist independently of the hazard itself and act as cultural lenses through which information is heard, processed and interpreted; hazard specific variables that directly relate to the specific hazard threat; and risk perception. The ultimate goal is to determine what factors influence the evacuation decision-making process. Using data collected for 1998's Hurricane Georges, logistic regression models were used to evaluate how well the three main factors help our understanding of how individuals come to their decisions to either flee to safety during a hurricane or remain in their homes. ^ The results of the logistic regression were significant emphasizing that the three broad types of factors tested in the model influence the decision making process. Conclusions drawn from the data analysis focus on how decision-making frames are different for those who can be designated “evacuators” and for those in evacuation zones. ^

The Influence of Psychological Predictors and Cognitive Behavioral Stress Management Intervention on Antiretroviral Therapy (ART) Adherence Among HIV-Positive Female Haitian Alcohol Users

Purpose: Over half the HIV-infected persons in the Caribbean, the second most HIV-impacted region in the world, live in Haiti. Using secondary data from a parent study, this research assessed the effects of psychological and social factors on antiretroviral therapy (ART) adherence among Haitian, HIV-positive, female alcohol users. Theoretical Foundation and Research Questions: Using the Theory of Planned Behavior/Reasoned Action and the Information, Motivation, Behavior skills model as guiding theoretical frameworks, the study examined the effectiveness of an adapted cognitive behavioral stress management (CBSM-A) intervention in improving ART adherence. The effect of psychological factors (depression, anxiety, beliefs about medicine, and social support), social factors (stigma, relationship status, and educational attainment), and alcohol on adherence to ART was assessed. Methods: The sample consisted of 116 female ART patients who were randomly assigned to the CBSM-A intervention or the wait-list control group. Participants completed intervention sessions as well as pre- and post-test assessments. Analyses of variance, t-tests, and point biserial correlations were used to test hypotheses. Results: Surprisingly, ART adherence rates significantly decreased for both groups combined [F (1, 108) = 8.79, p = .004]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post assessment. On average, depression decreased significantly among participants in the CBSM-A group only [(t (62) = 5.54, p < .001)]. For both groups combined, alcohol use significantly decreased between baseline and post-assessment [(F (1, 78) = 34.70, p < .001)]; there was no significant difference between the intervention and control groups with regard to the magnitude of change between baseline and post-assessment. None of the variables were significantly correlated with ART adherence. Discussion: Adherence to ART did not improve in this sample, nor were any of the variables significantly associated with adherence. The findings suggest that additional supportive and psychological services may be needed in order to promote higher adherence to ART among HIV-positive females. More research may be needed on this sample; a focus on mental health issues, partner conflict, family and sexual history may allow for better targeting and more successful interventions.

FDOT District Six Pedestrian Safety Web GIS Application

A group of four applications including Top 20 Pedestrian Crash Locations: This application is designed to display top 20 pedestrian crash locations into both map- view and detailed information view. FDOT Crash Reporting Tool: This application is designed to simplify the usage and sharing of CAR data. The application can load raw data from CAR and display it into a web map interface. FDOT Online Document Portal: This application is designed for FDOT project managers to be able to share and manage documents through a user friendly, GIS enable web interface GIS Data Collection for Pedestrian Safety Tool: FIU-GIS Center was responsible for data collection and processing work for the project of Pedestrian Safety Tool Project. The outcome of this task is present by a simple web-GIS application design to host GIS by projects.