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Title: Pre and Post Implementation Evaluation of an Emergency Department Severe Sepsis Alert and Practice Protocol.
Creator: Williams, Darleen, Andrews, Diane, Sole, Mary Lou, Parrish, Gary, University of Central Florida
Abstract / Description: ABSTRACTSevere sepsis kills an estimated 1,400 people worldwide every day. This often fatal infectious process accounts for an estimated 215,000 deaths in the United States (US) annually. The main goal of this project was to evaluate the impact of the Emergency Department Severe Sepsis Alert and Practice Protocol (EDSSAPP) post implementation, on time to first antibiotic administration, length of stay, and mortality in patients admitted via the ORMC ED with severe sepsis.This study evaluated...
Show moreABSTRACTSevere sepsis kills an estimated 1,400 people worldwide every day. This often fatal infectious process accounts for an estimated 215,000 deaths in the United States (US) annually. The main goal of this project was to evaluate the impact of the Emergency Department Severe Sepsis Alert and Practice Protocol (EDSSAPP) post implementation, on time to first antibiotic administration, length of stay, and mortality in patients admitted via the ORMC ED with severe sepsis.This study evaluated the time to first antibiotic administration, total ED and hospital length of stay (LOS) and mortality of severe sepsis patients either with a severe sepsis alert (SSA) activated or no alert activated that were admitted to the hospital through the ED. A retrospective review of the electronic medical record (EMR) was conducted to gather the required data across three time cohorts: base line/time zero (T0), six months prior to the implementation of EDSSAPP; Time one (T1) the first six months following initial EDSSAPP implementation; and Time two (T2), six months following reinstatement of the corporate sepsis committee. The most significant finding of this study was the increased number of Severe Sepsis Alerts activated in time cohort T2 (n=113) compared to T1 (n=19). Another important finding was the decreased mortality in T2 (16.4%) compared to T0 (22.7%) and T1 (33%). Overall, the number of ED patients with severe sepsis who received antibiotics within the EDSSAPP required 60 minutes did not consistently improve across the three time cohorts, T0 (81.8%), T1 (71.7%) and T2 (80.6%).The hospital LOS of stay was increased by almost 1.5 days between those patients with a severe sepsis alert activated in T1 (9.00 days) compared to time T2 (10.48 days). There was no significant decrease in the ED LOS across time cohorts and between groups of patients who had a SSA activated versus no alert activated. However, there was a 1 hour and 28 minute decrease in ED LOS in patients who had a severe sepsis alert activated in T1 compared to T0. In addition, there was a 1 hour and 52 minutes decrease in ED LOS between patients who had a SSA activated compared to those who had no alert activated in T2.While EDSSAPP data does not demonstrate the statistically significant results that was expected, the challenges related to adherence by providers to EDSSAPP is as it is seen in the literature. Increased awareness via consistent communication of on-going audit results to ED personnel will heighten their awareness for severe sepsis and EDSSAPP. Improved collaborative efforts with the interdisciplinary team are needed to refocus everyone's efforts to increase early recognition that is followed by appropriate treatment interventions and documentation is essential. Lastly, the development of a formal process to follow up with individual providers as close to real time as possible following a SSA that includes accountability for care provided and related documentation would also contribute to both awareness and adherence.
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Date Issued: 2015
Identifier: CFE0005739, ucf:50075
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005739

Title: Conceptualizing the Role of Severity in Counterproductive Work Behavior: Predicting Employee Engagement in Minor and Severe CWBs.
Creator: Ciarlante, Katherine, Shoss, Mindy, Bennett, Rebecca, Jex, Steve, University of Central Florida
Abstract / Description: Counterproductive work behaviors (CWBs) have been identified as pervasive employee behaviors with the potential to cause significant harm in the workplace (e.g., Sackett (&) DeVore, 2001). Because of the considerable threat CWBs pose to organizational and employee well-being, a literature has emerged to better understand the structure of these behaviors and identify the factors and conditions that effect employee engagement in counterproductive acts. While past research has distinguished...
Show moreCounterproductive work behaviors (CWBs) have been identified as pervasive employee behaviors with the potential to cause significant harm in the workplace (e.g., Sackett (&) DeVore, 2001). Because of the considerable threat CWBs pose to organizational and employee well-being, a literature has emerged to better understand the structure of these behaviors and identify the factors and conditions that effect employee engagement in counterproductive acts. While past research has distinguished between types of CWBs, i.e., theft, sabotage, withdrawal, less attention has been paid to the specific forms these behaviors take. For example, being two hours late to work is more serious and harmful than being five minutes late, and traditional frequency-based measures fail to distinguish between these behaviors. In order to understand and account for the full range of variation in employee CWBs, research must advance in ways that incorporates severity. The current study introduces a novel conceptualization of CWB severity that distinguishes between intra-behavioral differences and develops modified versions of the CWB-C (Spector et al., 2006; Bennett (&) Robinson, 2000) which assess engagement in low and high severity versions of each CWB. These new measures are utilized to test a hypothesized model of CWB severity that predicts how individual (negative affect) and contextual factors (self-control (&) perceived consequences) interact to predict low and high severity CWBs. This research seeks to expand our understanding of the diverse ways employees respond to stressful work conditions and represents an important first step in identifying the types of employees and work environments that are associated with the most harmful, high severity, CWBs. Implications for future CWB research are discussed.
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Date Issued: 2019
Identifier: CFE0007616, ucf:52557
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007616

Title: DOES MENTAL STATUS MODERATE THE RELATIONSHIP BETWEEN TRAUMATIC BRAIN INJURY HISTORY AND LIFE SATISFACTION?.
Creator: Payne, Charlotte A, Bedwell, Jeffrey, University of Central Florida
Abstract / Description: Traumatic brain injury (TBI) history has been linked to damaged cognition and poorer quality of life. While this link has been established, there is not much known about this relationship in older adult populations experiencing normal cognitive decline. In the current study, mental status was predicted to moderate the relationship between TBI history and life satisfaction among older adults. Additionally, details of the injury - years since injury and time spent unconscious - were expected to...
Show moreTraumatic brain injury (TBI) history has been linked to damaged cognition and poorer quality of life. While this link has been established, there is not much known about this relationship in older adult populations experiencing normal cognitive decline. In the current study, mental status was predicted to moderate the relationship between TBI history and life satisfaction among older adults. Additionally, details of the injury - years since injury and time spent unconscious - were expected to play a role in this relationship. Per analyses, there was no relationship found between TBI history, mental status, and life satisfaction. Moreover, there was no link found between time since injury, time spent unconscious, mental status and life satisfaction. While insignificant, these results yield important findings. The results lend support to more positive long-term outcomes for those with a history of TBI than initially expected, especially if the TBI was mild and resulted in no loss of consciousness or a loss of consciousness less than 5 hours.
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Date Issued: 2019
Identifier: CFH2000475, ucf:45896
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH2000475

Title: IBULLY: THE IMPACT OF GENDER OF BULLY AND VICTIM ON PERCEPTION OF CYBERBULLYING AND ITS CONSEQUENCES.
Creator: Sharpe, Christopher, Mottarella, Karen, University of Central Florida
Abstract / Description: In today's technologically sophisticated world, people have many electronic methods of exchanging information and communicating. Unfortunately, these methods are not always used in positive ways; they can also be used to convey aggression and bullying. Recently, such acts of aggression have been labeled many things from cyberbullying to online social cruelty, and have received much media attention due to their tragic consequences including victim suicide. This study explores the impact of...
Show moreIn today's technologically sophisticated world, people have many electronic methods of exchanging information and communicating. Unfortunately, these methods are not always used in positive ways; they can also be used to convey aggression and bullying. Recently, such acts of aggression have been labeled many things from cyberbullying to online social cruelty, and have received much media attention due to their tragic consequences including victim suicide. This study explores the impact of victim and bully gender in relation to perception of bully likability, punishment, impact on victim, and victim responses. Participants reviewed a Cyberbullying scenario in which the gender of the victim and perpetrator were manipulated. All scenarios were identical except for the gender pairs of the victim and perpetrator: Male (bully)-Male (victim), Male (bully)-Female (victim), Female (bully)-Female (victim), and Female (bully)-Male (victim). Participants then completed the Likability of Bully, Punishment for Bully, Impact on Victim, and Victim Response scales. A main effect of gender on the Punishment Scale for the gender of bully indicated that participants desired lighter punishment for females independent of the gender of the victim. The results of this study suggest that increasing awareness of the seriousness of all cyberbullying regardless of gender of bully is important.
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Date Issued: 2011
Identifier: CFH0003805, ucf:44736
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH0003805

Title: REDUCED VISIBILITY RELATED CRASHES IN FLORIDA: CRASH CHARACTERISTICS, SPATIAL ANALYSIS AND INJURY SEVERITY.
Creator: EKRAM, AL-AHAD, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: Roadway crashes related to vision obstruction due to fog/smoke (FS) conditions constitute a challenge for traffic engineers. Previous research efforts mostly concentrated on the snow and rain related crashes. Statistics show that Florida is among the top three states in terms of crashes due to vision obstruction by FS. This research culminated in a comprehensive study of fog and smoke related crashes in the state of Florida. The analysis took into account the crashes that occurred between...
Show moreRoadway crashes related to vision obstruction due to fog/smoke (FS) conditions constitute a challenge for traffic engineers. Previous research efforts mostly concentrated on the snow and rain related crashes. Statistics show that Florida is among the top three states in terms of crashes due to vision obstruction by FS. This research culminated in a comprehensive study of fog and smoke related crashes in the state of Florida. The analysis took into account the crashes that occurred between 2003 and 2007 on Florida state roads. Spatial analysis and injury severity analysis have been conducted and significant results have been identified. The spatial analysis by GIS examines the locations of high trends of FS related crashes on state roads in the State of Florida. Statistical features of the GIS tool, which is used efficiently in traffic safety research, has been used to find the crash clusters for the particular types of crashes that occur due to vision obstruction by FS. Several segmentation processes have been used, and the best segmentation for this study was found to be dividing the state roads into 1 mile segments, keeping the roadway characteristics uniform. Taking into account the entire state road network, ten distinct clusters were found that can be clearly associated with these types of crashes. However, no clear pattern in terms of area was observed, as it was seen that the percentage of FS related crashes in rural and urban areas are close. The general characteristics of FS related crashes have been investigated in detail. For the comparison to clear visibility conditions, simple odds ratios (in terms of crash frequencies) have been introduced. The morning hours in the months of December to February are found to be the prevalent time for fog related crashes, while for the smoke related crashes the dangerous time was found to be morning to midday in the month of May. Compared to crashes under clear-visibility conditions, the fog crashes tend to result in more severe injuries and involve more vehicles. Head-on and rear-end crashes are the two most common crash types in terms of crash frequency and severe crashes. For the injury severity analysis, a random effect ordered logistic model was used. The model in brief illustrates that the head-on and rear-end crash types are the two most prevalent crash types in FS conditions. Moreover, these severe crashes mainly occurred at higher speeds. Also they mostly took place on undivided roads, roadways without any sidewalk and two-lane rural roads. Increase of average daily traffic decrease the severity of FS related crashes. Overall, this study provides the Florida Department of Transportation (FDOT) with specific information on where improvements could be made to have better safety conditions in terms of vision obstruction due to FS in the state roads of Florida. Also it suggests the times and seasons that the safety precautions must be taken or the FS warning systems to be installed, and the controlling roadway geometries that can be improved or modified to reduce injury severity of a crash due to FS related vision obstruction.
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Date Issued: 2009
Identifier: CFE0002903, ucf:48008
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002903

Title: An Analysis of Choice-Making as A Means To Decrease The Frequency of Self-Injurious Behaviors in Students with Severe Disabilities.
Creator: Olson, Melanie, Marino, Matthew, Vasquez, Eleazar, Hines, Rebecca, University of Central Florida
Abstract / Description: This single case multiple baseline research study examined choice-making as a means to decrease the frequency of self-injurious behaviors in six students with severe disabilities. Five males and one female between the ages of 14 and 21 participated in the five-week intervention. The following research questions were addressed: 1) Does the choice-making intervention reduce hitting, biting, and self-injurious behaviors? 2) How much time does the choice-making intervention add to the classroom...
Show moreThis single case multiple baseline research study examined choice-making as a means to decrease the frequency of self-injurious behaviors in six students with severe disabilities. Five males and one female between the ages of 14 and 21 participated in the five-week intervention. The following research questions were addressed: 1) Does the choice-making intervention reduce hitting, biting, and self-injurious behaviors? 2) How much time does the choice-making intervention add to the classroom teacher's preparation? 3) What costs are associated with the choice-making intervention during an average lesson? The choice-making intervention was associated with positive behavioral outcomes for all of the students. The intervention added both time and cost to the lessons. Implications and areas for future research are discussed.
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Date Issued: 2018
Identifier: CFE0007352, ucf:52086
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007352

Title: A Comprehensive Severity Analysis of Large Vehicle Crashes.
Creator: Laman, Haluk, Abdel-Aty, Mohamed, Tatari, Mehmet, Ahmed, Mohamed, University of Central Florida
Abstract / Description: The goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large...
Show moreThe goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large vehicle crashes.Using the crashes involving large vehicles, a model comparison between binary logit model and a Chi-squared Automatic Interaction Detection (CHAID) decision tree model is provided. There were 13 significant factors (i.e. crash type with respect to vehicle types, residency of driver, DUI, rural-urban, etc.) found significant in the logistic procedure while 7 factors found (i.e. posted speed limit, intersection, etc.) in the CHAID model. The model comparison results indicate that the logit analysis procedure is better in terms of prediction power.The following analysis is a modeling structure involving three binary logit models. The first model was conducted to estimate the crash severity of crashes that involved only personal vehicles (PV). Second model uses the crashes that involved large vehicles (LV) and passenger vehicles (PV). The final model estimated the severity level of crashes involving only large vehicles (LV). Significant differences with respect to various risk factors including driver, vehicle, environmental, road geometry and traffic characteristics were found to exist between those crash types and models. For example, driving under the influence of Alcohol (DUI) has positive effect on the severity of PV vs. PV and LV vs. PV while it has no effect on LV vs. LV. As a result, 4 of the variables found to be significant were similar in all three models (although often with quite different impact) and there were 11 variables that significantly influenced crash injury severity in PV vs. PV crashes, and 9 variables that significantly influenced crash injury severity in LV vs. PV crashes.Based on the significant variables, maximum posted speed, number of vehicles involved, and intersections are among the factors that have major impact on injury severity. These results could be used to identify potential countermeasures to reduce crash severity in general, and for LVs in particular. For example, restricting the speed limits and enforcing it for large vehicles could be a suggested countermeasure based on this study.
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Date Issued: 2012
Identifier: CFE0004566, ucf:49216
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004566

Title: COMPREHENSIVE ANALYTICAL INVESTIGATION OF THE SAFETY OF UNSIGNALIZED INTERSECTIONS.
Creator: Haleem, Kirolos, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: According to documented statistics, intersections are among the most hazardous locations on roadway systems. Many studies have extensively analyzed safety of signalized intersections, but did not put their major focus on the most frequent type of intersections, unsignalized intersections. Unsignalized intersections are those intersections with stop control, yield control and no traffic control. Unsignalized intersections can be differentiated from their signalized counterparts in that their...
Show moreAccording to documented statistics, intersections are among the most hazardous locations on roadway systems. Many studies have extensively analyzed safety of signalized intersections, but did not put their major focus on the most frequent type of intersections, unsignalized intersections. Unsignalized intersections are those intersections with stop control, yield control and no traffic control. Unsignalized intersections can be differentiated from their signalized counterparts in that their operational functions take place without the presence of a traffic signal. In this dissertation, multiple approaches of analyzing safety at unsignalized intersections were conducted. This was investigated in this study by analyzing total crashes, the most frequent crash types at unsignalized intersections (rear-end as well as angle crashes) and crash injury severity. Additionally, an access management analysis was investigated with respect to the different median types identified in this study. Some of the developed methodological techniques in this study are considered recent, and have not been extensively applied. In this dissertation, the most extensive data collection effort for unsignalized intersections was conducted. There were 2500 unsignalized intersections collected from six counties in the state of Florida. These six counties were Orange, Seminole, Hillsborough, Brevard, Leon and Miami-Dade. These selected counties are major counties representing the central, western, eastern, northern and southern parts in Florida, respectively. Hence, a geographic representation of the state of Florida was achieved. Important intersections' geometric and roadway features, minor approach traffic control, major approach traffic flow and crashes were obtained. The traditional negative binomial (NB) regression model was used for modeling total crash frequency for two years at unsignalized intersections. This was considered since the NB technique is well accepted for modeling crash count data suffering from over-dispersion. The NB models showed several important variables affecting safety at unsignalized intersections. These include the traffic volume on the major road and the existence of stop signs, and among the geometric characteristics, the configuration of the intersection, number of right and/or left turn lanes, median type on the major road, and left and right shoulder widths. Afterwards, a new approach of applying the Bayesian updating concept for better crash prediction was introduced. Different non-informative and informative prior structures using the NB and log-gamma distributions were attempted. The log-gamma distribution showed the best prediction capability. Crash injury severity at unsignalized intersections was analyzed using the ordered probit, binary probit and nested logit frameworks. The binary probit method was considered the best approach based on its goodness-of-fit statistics. The common factors found in the fitted probit models were the logarithm of AADT on the major road, and the speed limit on the major road. It was found that higher severity (and fatality) probability is always associated with a reduction in AADT, as well as an increase in speed limit. A recently developed data mining technique, the multivariate adaptive regression splines (MARS) technique, which is capable of yielding high prediction accuracy, was used to analyze rear-end as well as angle crashes. MARS yielded the best prediction performance while dealing with continuous responses. Additionally, screening the covariates using random forest before fitting MARS model was very encouraging. Finally, an access management analysis was performed with respect to six main median types associated with unsignalized intersections/access points. These six median types were open, closed, directional (allowing access from both sides), two-way left turn lane, undivided and mixed medians (e.g., directional median, but allowing access from one side only). Also, crash conflict patterns at each of these six medians were identified and applied to a dataset including median-related crashes. In this case, separating median-related and intersection-related crashes was deemed significant in the analysis. From the preliminary analysis, open medians were considered the most hazardous median type, and closed and undivided medians were the safest. The binomial logit and bivariate probit models showed significant median-related variables affecting median-related crashes, such as median width, speed limit on the major road, logarithm of AADT, logarithm of the upstream and downstream distances to the nearest signalized intersection and crash pattern. The results from the different methodological approaches introduced in this study could be applicable to diagnose safety deficiencies identified. For example, to reduce crash severity, prohibiting left turn maneuvers from minor intersection approaches is recommended. To reduce right-angle crashes, avoiding installing two-way left turn lanes at 4-legged intersections is essential. To reduce conflict points, closing median openings across from intersections is recommended. Since left-turn and angle crash patterns were the most dominant at undivided medians, it is recommended to avoid left turn maneuvers at unsignalized intersections having undivided medians at their approach. This could be enforced by installing a left-turn prohibition sign on both major and minor approaches.
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Date Issued: 2009
Identifier: CFE0002900, ucf:48011
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002900

Title: SAFETY ANALYSES AT SIGNALIZED INTERSECTIONS CONSIDERING SPATIAL, TEMPORAL AND SITE CORRELATION.
Creator: Wang, Xuesong, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: Statistics show that signalized intersections are among the most dangerous locations of a roadway network. Different approaches including crash frequency and severity models have been used to establish the relationship between crash occurrence and intersection characteristics. In order to model crash occurrence at signalized intersections more efficiently and eventually to better identify the significant factors contributing to crashes, this dissertation investigated the temporal, spatial,...
Show moreStatistics show that signalized intersections are among the most dangerous locations of a roadway network. Different approaches including crash frequency and severity models have been used to establish the relationship between crash occurrence and intersection characteristics. In order to model crash occurrence at signalized intersections more efficiently and eventually to better identify the significant factors contributing to crashes, this dissertation investigated the temporal, spatial, and site correlations for total, rear-end, right-angle and left-turn crashes. Using the basic regression model for correlated crash data leads to invalid statistical inference, due to incorrect test statistics and standard errors based on the misspecified variance. In this dissertation, the Generalized Estimating Equations (GEEs) were applied, which provide an extension of generalized linear models to the analysis of longitudinal or clustered data. A series of frequency models are presented by using the GEE with a Negative Binomial as the link function. The GEE models for the crash frequency per year (using four correlation structures) were fitted for longitudinal data; the GEE models for the crash frequency per intersection (using three correlation structures) were fitted for the signalized intersections along corridors; the GEE models were applied for the rear-end crash data with temporal or spatial correlation separately. For right-angle crash frequency, models at intersection, roadway, and approach levels were fitted and the roadway and approach level models were estimated by using the GEE to account for the "site correlation"; and for left-turn crashes, the approach level crash frequencies were modeled by using the GEE with a Negative Binomial link function for most patterns and using a binomial logit link function for the pattern having a higher proportion of zeros and ones in crash frequencies. All intersection geometry design features, traffic control and operational features, traffic flows, and crashes were obtained for selected intersections. Massive data collection work has been done. The autoregression structure is found to be the most appropriate correlation structure for both intersection temporal and spatial analyses, which indicates that the correlation between the multiple observations for a certain intersection will decrease as the time-gap increase and for spatially correlated signalized intersections along corridors the correlation between intersections decreases as spacing increases. The unstructured correlation structure was applied for roadway and approach level right-angle crashes and also for different patterns of left-turn crashes at the approach level. Usually two approaches at the same roadway have a higher correlation. At signalized intersections, differences exist in traffic volumes, site geometry, and signal operations, as well as safety performance on various approaches of intersections. Therefore, modeling the total number of left-turn crashes at intersections may obscure the real relationship between the crash causes and their effects. The dissertation modeled crashes at different levels. Particularly, intersection, roadway, and approach level models were compared for right-angle crashes, and different crash assignment criteria of "at-fault driver" or "near-side" were applied for disaggregated models. It shows that for the roadway and approach level models, the "near-side" models outperformed the "at-fault driver" models. Variables in traffic characteristics, geometric design features, traffic control and operational features, corridor level factor, and location type have been identified to be significant in crash occurrence. In specific, the safety relationship between crash occurrence and traffic volume has been investigated extensively at different studies. It has been found that the logarithm of traffic volumes per lane for the entire intersection is the best functional form for the total crashes in both the temporal and spatial analyses. The studies of right-angle and left-turn crashes confirm the assumption that the frequency of collisions is related to the traffic flows to which the colliding vehicles belong and not to the sum of the entering flows; the logarithm of the product of conflicting flows is usually the most significant functional form in the model. This study found that the left-turn protection on the minor roadway will increase rear-end crash occurrence, while the left-turn protection on the major roadway will reduce rear-end crashes. In addition, left-turn protection reduces Pattern 5 left-turn crashes (left-turning traffic collides with on-coming through traffic) specifically, but it increases Pattern 8 left-turn crashes (left-turning traffic collides with near-side crossing through traffic), and it has no significant effect on other patterns of left-turn crashes. This dissertation also investigated some other factors which have not been considered before. The safety effectiveness of many variables identified in this dissertation is consistent with previous studies. Some variables have unexpected signs and a justification is provided. Injury severity also has been studied for Patterns 5 left-turn crashes. Crashes were located to the approach with left-turning vehicles. The "site correlation" among the crashes occurred at the same approach was considered since these crashes may have similar propensity in crash severity. Many methodologies and applications have been attempted in this dissertation. Therefore, the study has both theoretical and implementational contribution in safety analysis at signalized intersections.
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Date Issued: 2006
Identifier: CFE0001497, ucf:47078
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001497

Title: SEVERITY ANALYSIS OF DRIVER CRASH INVOLVEMENTS ON MULTILANE HIGH SPEED ARTERIAL CORRIDORS.
Creator: Nevarez-Pagan, Alexis, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: Arterial roads constitute the majority of the centerline miles of the Florida State Highway System. Severe injury involvements on these roads account for a quarter of the total severe injuries reported statewide. This research focuses on driver injury severity analysis of statewide multilane high speed arterials using crash data for the years 2002 to 2004. The first goal is to test different ways of analyzing crash data (by road entity and crash types) and find the best method of driver...
Show moreArterial roads constitute the majority of the centerline miles of the Florida State Highway System. Severe injury involvements on these roads account for a quarter of the total severe injuries reported statewide. This research focuses on driver injury severity analysis of statewide multilane high speed arterials using crash data for the years 2002 to 2004. The first goal is to test different ways of analyzing crash data (by road entity and crash types) and find the best method of driver injury severity analysis. A second goal is to find driver, vehicle, road and environment related factors that contribute to severe involvements on multilane arterials. Exploratory analysis using one year of crash data (2004) using binary logit regression was used to measure the risk of driver severe injury given that a crash occurs. A preliminary list of significant factors was obtained. A massive data preparation effort was undertaken and a random sample of multivehicle crashes was selected for final analysis. The final injury severity analysis consisted of six road entity models and twenty crash type models. The data preparation and sampling was successful in allowing a robust dataset. The overall model was a good candidate for the analysis of driver injury severity on multilane high speed roads. Driver injury severity resulting from angle and left turn crashes were best modeled by separate non-signalized intersection crash analysis. Injury severity from rear end and fixed object crashes was best modeled by combined analysis of pure segment and non-signalized intersection crashes. The most important contributing factors found in the overall analysis included driver related variables such as age, gender, seat belt use, at-fault driver, physical defects and speeding. Crash and vehicle related contributing factors included driver ejection, collision type (harmful event), contributing cause, type of vehicle and off roadway crash. Multivehicle crashes and interactions with intersection and off road crashes were also significant. The most significant roadway related variables included speed limit, ADT per lane, access class, lane width, roadway curve, sidewalk width, non-high mast lighting density, type of friction course and skid resistance. The overall model had a very good fit but some misspecification symptoms appeared due to major differences in road entities and crash types by land use. Two additional models of crashes for urban and rural areas were successfully developed. The land use models' goodness of fit was substantially better than any other combination by road entity or the overall model. Their coefficients were substantially robust and their values agreed with scientific or empirical principles. Additional research is needed to prove these results for crash type models found most reliable by this investigation. A framework for injury severity analysis and safety improvement guidelines based on the results is presented. Additional integration of road characteristics (especially intersection) data is recommended for future research. Also, the use of statistical methods that account for correlation among crashes and locations are suggested for use in future research.
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Date Issued: 2008
Identifier: CFE0002080, ucf:47591
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002080

Title: ANALYSES OF CRASH OCCURENCE AND INURY SEVERITIES ON MULTI LANE HIGHWAYS USING MACHINE LEARNING ALGORITHMS.
Creator: Das, Abhishek, Abdel-Aty, Mohamed A., University of Central Florida
Abstract / Description: Reduction of crash occurrence on the various roadway locations (mid-block segments; signalized intersections; un-signalized intersections) and the mitigation of injury severity in the event of a crash are the major concerns of transportation safety engineers. Multi lane arterial roadways (excluding freeways and expressways) account for forty-three percent of fatal crashes in the state of Florida. Significant contributing causes fall under the broad categories of aggressive driver behavior;...
Show moreReduction of crash occurrence on the various roadway locations (mid-block segments; signalized intersections; un-signalized intersections) and the mitigation of injury severity in the event of a crash are the major concerns of transportation safety engineers. Multi lane arterial roadways (excluding freeways and expressways) account for forty-three percent of fatal crashes in the state of Florida. Significant contributing causes fall under the broad categories of aggressive driver behavior; adverse weather and environmental conditions; and roadway geometric and traffic factors. The objective of this research was the implementation of innovative, state-of-the-art analytical methods to identify the contributing factors for crashes and injury severity. Advances in computational methods render the use of modern statistical and machine learning algorithms. Even though most of the contributing factors are known a-priori, advanced methods unearth changing trends. Heuristic evolutionary processes such as genetic programming; sophisticated data mining methods like conditional inference tree; and mathematical treatments in the form of sensitivity analyses outline the major contributions in this research. Application of traditional statistical methods like simultaneous ordered probit models, identification and resolution of crash data problems are also key aspects of this study. In order to eliminate the use of unrealistic uniform intersection influence radius of 250 ft, heuristic rules were developed for assigning crashes to roadway segments, signalized intersection and access points using parameters, such as 'site location', 'traffic control' and node information. Use of Conditional Inference Forest instead of Classification and Regression Tree to identify variables of significance for injury severity analysis removed the bias towards the selection of continuous variable or variables with large number of categories. For the injury severity analysis of crashes on highways, the corridors were clustered into four optimum groups. The optimum number of clusters was found using Partitioning around Medoids algorithm. Concepts of evolutionary biology like crossover and mutation were implemented to develop models for classification and regression analyses based on the highest hit rate and minimum error rate, respectively. Low crossover rate and higher mutation reduces the chances of genetic drift and brings in novelty to the model development process. Annual daily traffic; friction coefficient of pavements; on-street parking; curbed medians; surface and shoulder widths; alcohol / drug usage are some of the significant factors that played a role in both crash occurrence and injury severities. Relative sensitivity analyses were used to identify the effect of continuous variables on the variation of crash counts. This study improved the understanding of the significant factors that could play an important role in designing better safety countermeasures on multi lane highways, and hence enhance their safety by reducing the frequency of crashes and severity of injuries. Educating young people about the abuses of alcohol and drugs specifically at high schools and colleges could potentially lead to lower driver aggression. Removal of on-street parking from high speed arterials unilaterally could result in likely drop in the number of crashes. Widening of shoulders could give greater maneuvering space for the drivers. Improving pavement conditions for better friction coefficient will lead to improved crash recovery. Addition of lanes to alleviate problems arising out of increased ADT and restriction of trucks to the slower right lanes on the highways would not only reduce the crash occurrences but also resulted in lower injury severity levels.
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Date Issued: 2009
Identifier: CFE0002928, ucf:48007
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002928

Title: Safety investigation of traffic crashes incorporating spatial correlation effects.
Creator: Alkahtani, Khalid, Abdel-Aty, Mohamed, Radwan, Essam, Eluru, Naveen, Lee, JaeYoung, Zheng, Qipeng, University of Central Florida
Abstract / Description: One main interest in crash frequency modeling is to predict crash counts over a spatial domain of interest (e.g., traffic analysis zones (TAZs)). The macro-level crash prediction models can assist transportation planners with a comprehensive perspective to consider safety in the long-range transportation planning process. Most of the previous studies that have examined traffic crashes at the macro-level are related to high-income countries, whereas there is a lack of similar studies among...
Show moreOne main interest in crash frequency modeling is to predict crash counts over a spatial domain of interest (e.g., traffic analysis zones (TAZs)). The macro-level crash prediction models can assist transportation planners with a comprehensive perspective to consider safety in the long-range transportation planning process. Most of the previous studies that have examined traffic crashes at the macro-level are related to high-income countries, whereas there is a lack of similar studies among lower- and middle-income countries where most road traffic deaths (90%) occur. This includes Middle Eastern countries, necessitating a thorough investigation and diagnosis of the issues and factors instigating traffic crashes in the region in order to reduce these serious traffic crashes. Since pedestrians are more vulnerable to traffic crashes compared to other road users, especially in this region, a safety investigation of pedestrian crashes is crucial to improving traffic safety. Riyadh, Saudi Arabia, which is one of the largest Middle East metropolises, is used as an example to reflect the representation of these countries' characteristics, where Saudi Arabia has a rather distinct situation in that it is considered a high-income country, and yet it has the highest rate of traffic fatalities compared to their high-income counterparts. Therefore, in this research, several statistical methods are used to investigate the association between traffic crash frequency and contributing factors of crash data, which are characterized by 1) geographical referencing (i.e., observed at specific locations) or spatially varying over geographic units when modeled; 2) correlation between different response variables (e.g., crash counts by severity or type levels); and 3) temporally correlated. A Bayesian multivariate spatial model is developed for predicting crash counts by severity and type. Therefore, based on the findings of this study, policy makers would be able to suggest appropriate safety countermeasures for each type of crash in each zone.
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Date Issued: 2018
Identifier: CFE0007148, ucf:52324
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007148

Title: LEVEL-OF-SERVICE AND TRAFFIC SAFETY RELATIONSHIP: AN EXPLORATORY ANALYSIS OF SIGNALIZED INTERSECTIONS AND MULTILANE HIGH-SPEED ARTERIAL CORRIDORS.
Creator: Almonte-Valdivia, Ana, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: Since its inception in 1965, the Level-of-Service (LOS) has proved to be an important and practical "quality of service" indicator for transportation facilities around the world, widely used in the transportation and planning fields. The LOS rates these facilities' traffic operating conditions through the following delay-based indicators (ordered from best to worst conditions): A, B, C, D, E and F. This LOS rating has its foundation on quantifiable measures of effectiveness (MOEs) and on...
Show moreSince its inception in 1965, the Level-of-Service (LOS) has proved to be an important and practical "quality of service" indicator for transportation facilities around the world, widely used in the transportation and planning fields. The LOS rates these facilities' traffic operating conditions through the following delay-based indicators (ordered from best to worst conditions): A, B, C, D, E and F. This LOS rating has its foundation on quantifiable measures of effectiveness (MOEs) and on road users' perceptions; altogether, these measures define a LOS based on acceptable traffic operating conditions for the road user, implying that traffic safety is inherent to this definition. However, since 1994 safety has been excluded from the LOS definition since it cannot be quantified nor explicitly defined. The latter has been the motivation for research based on the LOS-Safety relationship, conducted at the University of Central Florida (UCF). Using data from two of the most studied transportation facility types within the field of traffic safety, signalized intersections and multilane high-speed arterial corridors, the research conducted has the following main objectives: to incorporate the LOS as a parameter in several traffic safety models, to extend the methodology adopted in previous studies to the subject matter, and to provide a platform for future transportation-related research on the LOS-Safety relationship. A meticulous data collection and preparation process was performed for the two LOS-Safety studies comprising this research. Apart from signalized intersections' and multilane-high speed arterial corridors' data, the other required types of information corresponded to crashes and road features, both obtained from FDOT's respective databases. In addition, the Highway Capacity Software (HCS) and the ArcGIS software package were extensively used for the data preparation. The result was a representative and robust dataset for each LOS-Safety study, to be later tested and analyzed with appropriate statistical methods. Regarding the LOS-Safety study for signalized intersections, two statistical techniques were used. The Generalized Estimating Equations (GEEs), the first technique, was used for the analyses considering all periods of a regular weekday (i.e. Monday through Friday): Early Morning, A.M. Peak, Midday, P.M. Peak and Late Evening; the second technique considered was the Negative Binomial, which was used for performing an individual analysis per period of the day. On the other hand, the LOS-Safety study for multilane high-speed arterial corridors made exclusive use of the Negative Binomial technique. An appropriate variable selection process was required for the respective model building and calibration procedures; the resulting models were built upon the six following response variables: total crashes, severe crashes, as well as rear-end, sideswipe, head-on and angle plus left-turn crashes. The final results proved to be meaningful for the understanding of traffic congestion effects on road safety, and on how they could be useful within the transportation planning scope. Overall, it was found that the risk for crash occurrence at signalized intersections and multilane high-speed arterial corridors is quite high between stable and unacceptable operating conditions; it was also found that this risk increases as it becomes later in the day. Among the significant factors within the signalized intersection-related models were LOS for the intersection as a whole, cycle length, lighting conditions, land use, traffic volume (major and minor roads), left-turn traffic volume (major road only), posted speed limit (major and minor roads), total number of through lanes (major and minor roads), overall total and total number of left-turn lanes (major road only), as well as county and period of the day (dummy variables). For multilane-high speed arterial corridors, the final models included LOS for the road section, average daily traffic (ADT), total number of through lanes in a single direction, total length of the road section, pavement surface type, as well as median and inside shoulder widths. A summary of the overall results per study, model implications and each LOS indicator is presented. Some of the final recommendations are to develop models for other crash types, to perform a LOS-Safety analysis at the approach-level for signalized intersections, as well as one that incorporates intersections within the arterial corridors' framework.
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Date Issued: 2009
Identifier: CFE0002615, ucf:48285
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002615

Title: A GIS SAFETY STUDY AND A COUNTY-LEVEL SPATIAL ANALYSIS OF CRASHES IN THE STATE OF FLORIDA.
Creator: Darwiche, Ali, Abdel-Aty, Mohamed, University of Central Florida
Abstract / Description: The research conducted in this thesis consists of a Geographic Information Systems (GIS) based safety study and a spatial analysis of vehicle crashes in the State of Florida. The GIS safety study is comprised of a County and Roadway Level GIS analysis of multilane corridors. The spatial analysis investigated the use of county-level vehicle crash models, taking spatial effects into account. The GIS safety study examines the locations of high trends of severe crashes (includes incapacitating...
Show moreThe research conducted in this thesis consists of a Geographic Information Systems (GIS) based safety study and a spatial analysis of vehicle crashes in the State of Florida. The GIS safety study is comprised of a County and Roadway Level GIS analysis of multilane corridors. The spatial analysis investigated the use of county-level vehicle crash models, taking spatial effects into account. The GIS safety study examines the locations of high trends of severe crashes (includes incapacitating and fatal crashes) on multilane corridors in the State of Florida at two levels, county level and roadway level. The GIS tool, which is used frequently in traffic safety research, was utilized to visually display those locations. At the county level, several maps of crash trends were generated. It was found that counties with high population and large metropolitan areas tend to have more crash occurrences. It was also found that the most severe crashes occurred in counties with more urban than rural roads. The neighboring counties of Pasco, Pinellas and Hillsborough had high severe crash rate per mile. At the roadway level, seven counties were chosen for the analysis based on their high severe crash trends, metropolitan size and geographical location. Several GIS maps displaying the safety level of multilane corridors in the seven counties were generated. The GIS maps were based on a ranking methodology that was developed in research that evaluated the safety condition of road segments and signalized intersections separately. The GIS maps were supported by Excel tables which provided details on the most hazardous locations on the roadways. The results of the roadway level analysis found that the worst corridors were located in Pasco, Pinellas and Hillsborough Counties. Also, a sliding window approach was developed and performed on the ten most hazardous corridors of the seven counties. The results were graphs locating the most dangerous 0.5 miles on a corridor. For the spatial analysis of crashes, the exploratory Moran's I statistic test revealed that crash related spatial clustering existed at the county level. For crash modeling, a full Bayesian (FB) hierarchical model is proposed to account for the possible spatial correlation among crash occurrence of adjacent counties. The spatial correlation is realized by specifying a Conditional Auto-regressive prior to the residual term of the link function in standard Poisson regression. Two FB models were developed, one for total crashes and one for severe crashes. The variables used include traffic related factors and socio-economic factors. Counties with higher road congestion levels, higher densities of arterials and intersections, higher percentage of population in the 15-24 age group and higher income levels have increased crash risk. Road congestion and higher education levels, however, were negatively correlated with the risk of severe crashes. The analysis revealed that crash related spatial correlation existed among the counties. The FB models were found to fit the data better than traditional methods such as Negative Binomial and that is primarily due to the existence of spatial correlation. Overall, this study provides the Transportation Agencies with specific information on where improvements must be implemented to have better safety conditions on the roads of Florida. The study also proves that neighboring counties are more likely to have similar crash trends than the more distant ones.
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Date Issued: 2009
Identifier: CFE0002623, ucf:48204
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002623

Title: Pedestrian Safety Analysis through Effective Exposure Measures and Examination of Injury Severity.
Creator: Shah, Md Imran, Abdel-Aty, Mohamed, Eluru, Naveen, Lee, JaeYoung, University of Central Florida
Abstract / Description: Pedestrians are considered the most vulnerable road users who are directly exposed to traffic crashes. In 2014, there were 4,884 pedestrians killed and 65,000 injured in the United States. Pedestrian safety is a growing concern in the development of sustainable transportation system. But often it is found that safety analysis suffers from lack of accurate pedestrian trip information. In such cases, determining effective exposure measures is the most appropriate safety analysis approach. Also...
Show morePedestrians are considered the most vulnerable road users who are directly exposed to traffic crashes. In 2014, there were 4,884 pedestrians killed and 65,000 injured in the United States. Pedestrian safety is a growing concern in the development of sustainable transportation system. But often it is found that safety analysis suffers from lack of accurate pedestrian trip information. In such cases, determining effective exposure measures is the most appropriate safety analysis approach. Also it is very important to clearly understand the relationship between pedestrian injury severity and the factors contributing to higher injury severity. Accurate safety analysis can play a vital role in the development of appropriate safety countermeasures and policies for pedestrians.Since pedestrian volume data is the most important information in safety analysis but rarely available, the first part of the study aims at identifying surrogate measures for pedestrian exposure at intersections. A two-step process is implemented: the first step is the development of Tobit and Generalized Linear Models for predicting pedestrian trips (i.e., exposure models). In the second step, Negative Binomial and Zero Inflated Negative Binomial crash models were developed using the predicted pedestrian trips. The results indicate that among various exposure models the Tobit model performs the best in describing pedestrian exposure. The identified exposure relevant factors are the presence of schools, car-ownership, pavement condition, sidewalk width, bus ridership, intersection control type and presence of sidewalk barrier. The t-test and Wilcoxon signed-rank test results show that there is no significant difference between the observed and the predicted pedestrian trips. The process implemented can help in estimating reliable safety performance functions even when pedestrian trip data is unavailable.The second part of the study focuses on analyzing pedestrian injury severity for the nine counties in Central Florida. The study region covers the Orlando area which has the second-worst pedestrian death rate in the country. Since the dependent variable 'Injury' is ordinal, an 'Ordered Logit' model was developed to identify the factors of pedestrian injury severity. The explanatory variables can be classified as pedestrian/driver characteristics (e.g., age, gender, etc.), roadway traffic and geometric conditions (e.g.: shoulder presence, roadway speed etc.) and crash environment (e.g., light, road surface, work zone, etc.) characteristics. The results show that drug/alcohol involvement, pedestrians in a hurry, roadway speed limit 40 mph or more, dark condition (lighted and unlighted) and presence of elder pedestrians are the primary contributing factors of severe pedestrian crashes in Central Florida. Crashes within the presence of intersections and local roads result in lower injury severity. The area under the ROC (Receiver Operating Characteristic) curve has a value of 0.75 that indicates the model performs reasonably well. Finally the study validated the model using k-fold cross validation method. The results could be useful for transportation officials for further pedestrian safety analysis and taking the appropriate safety interventions.Walking is cost-effective, environmentally friendly and possesses significant health benefits. In order to get these benefits from walking, the most important task is to ensure safer roads for pedestrians.
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Date Issued: 2017
Identifier: CFE0006656, ucf:51224
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006656

Title: Hierarchical Corridor Safety Analysis Using Multiple Approaches.
Creator: Alarifi, Saif, Abdel-Aty, Mohamed, Tatari, Omer, Kuo, Pei-Fen, University of Central Florida
Abstract / Description: Traffic crashes are a major cause of concern globally. Extensive efforts from transportation professionals have been made to investigate new methods to identify the contributing factors to crashes at various locations on the road network. Corridors, among other road network's components, play a vital role in moving people and goods between primary zones in different areas, and the safety and operational improvements of them have been the focus of many studies since they carry the most traffic...
Show moreTraffic crashes are a major cause of concern globally. Extensive efforts from transportation professionals have been made to investigate new methods to identify the contributing factors to crashes at various locations on the road network. Corridors, among other road network's components, play a vital role in moving people and goods between primary zones in different areas, and the safety and operational improvements of them have been the focus of many studies since they carry the most traffic on the road network. Corridors contain mainly intersections and segments, and previous corridor studies have focused on a sole type of road entity. Having both components while analyzing corridors in addition to corridor-level variables in a hierarchical joint model framework would provide a comprehensive understanding of the existing safety problems along corridors. Therefore, this research aims to provide a complete understanding of the contributing factors to crashes at intersections and segments along corridors. In addition, it explores the associated crash risk factors with crash counts of different types and severity levels. The results reveal that accounting for the variations in traffic volumes and roadway characteristics, by estimating the model with random parameters, across corridors improved the model's performance. Also, the results confirm the importance of accounting for the spatial autocorrelation between road entities along the same corridor, and the adjacency-based first-order neighboring structure provides the best fit for the data among the other neighboring structures. Furthermore, it was found that the significant variables and their magnitudes are different across crash types and severity levels. Also, road designers and engineers should carefully identify the optimal number and location of driveways, median openings, and access points within the influence area of intersections since they significantly affect crashes along corridors. Lastly, this research suggests and justifies considering the proposed hierarchical joint model for future corridor studies
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Date Issued: 2018
Identifier: CFE0006967, ucf:51666
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006967

severity (4)	+ -
crash severity (2)	+ -
safety (2)	+ -
3-legged intersection (1)	+ -
4-legged intersection (1)	+ -

ARTERIAL CORRIDORS (1)	+ -
Bayesian models (1)	+ -
Behavior Intervention (1)	+ -
Bullying (1)	+ -
CAR (1)	+ -
Choice-making (1)	+ -
Corridor Safety Analysis (1)	+ -
Crash (1)	+ -
Crash Severity level (1)	+ -
Crash Type. (1)	+ -
Crash severity models (1)	+ -
Crash type models (1)	+ -
Cyberbullying (1)	+ -
DRIVER INJURY (1)	+ -
Emergency Department (1)	+ -
Fog (1)	+ -
GIS (1)	+ -
Gender (1)	+ -
Generalized Estimating Equations (1)	+ -
Hierarchical Joint Model (1)	+ -
INVOLVEMENTS (1)	+ -
Injury severity (1)	+ -
LOGISTIC REGRESSION (1)	+ -
Level-of-Service (LOS) (1)	+ -
Likeability (1)	+ -

ETD Collection (14)	+ -
Honors Collection (2)	+ -

University of Central Florida (16)	+ -
Abdel-Aty, Mohamed (10)	+ -
Eluru, Naveen (2)	+ -
Lee, JaeYoung (2)	+ -
Abdel-Aty, Mohamed A. (1)	+ -

Ahmed, Mohamed (1)	+ -
Alarifi, Saif (1)	+ -
Alkahtani, Khalid (1)	+ -
Almonte-Valdivia, Ana (1)	+ -
Andrews, Diane (1)	+ -
Bedwell, Jeffrey (1)	+ -
Bennett, Rebecca (1)	+ -
Ciarlante, Katherine (1)	+ -
Darwiche, Ali (1)	+ -
Das, Abhishek (1)	+ -
EKRAM, AL-AHAD (1)	+ -
Haleem, Kirolos (1)	+ -
Hines, Rebecca (1)	+ -
Jex, Steve (1)	+ -
Kuo, Pei-Fen (1)	+ -
Laman, Haluk (1)	+ -
Marino, Matthew (1)	+ -
Mottarella, Karen (1)	+ -
Nevarez-Pagan, Alexis (1)	+ -
Olson, Melanie (1)	+ -
Parrish, Gary (1)	+ -
Payne, Charlotte A (1)	+ -
Radwan, Essam (1)	+ -
Shah, Md Imran (1)	+ -
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