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Safety investigation of traffic crashes incorporating spatial correlation effects
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
TECHNIQUES FOR ASSESSING AND IMPROVING PERFORMANCE IN NAVIGATION AND WAYFINDING USING MOBILE AUGMENTED REALITY
Title
TECHNIQUES FOR ASSESSING AND IMPROVING PERFORMANCE IN NAVIGATION AND WAYFINDING USING MOBILE AUGMENTED REALITY.
Creator
Goldiez, Brian, Hancock, Peter, University of Central Florida
Abstract / Description
Augmented reality is a field of technology in which the real world is overlaid with additional information from a computer generated display. Enhancements to augmented reality technology presently support limited mobility which is expected to increase in the future to provide much greater real world functionality. This work reports on a set of experiments that investigate performance in search and rescue navigating tasks using augmented reality. Augmentation consisted of a spatially and...
Show moreAugmented reality is a field of technology in which the real world is overlaid with additional information from a computer generated display. Enhancements to augmented reality technology presently support limited mobility which is expected to increase in the future to provide much greater real world functionality. This work reports on a set of experiments that investigate performance in search and rescue navigating tasks using augmented reality. Augmentation consisted of a spatially and temporally registered map of a maze that was overlaid onto a real world maze. Participants were required to traverse the maze, answer spatially oriented questions in the maze, acquire a target object, and exit. Pre and post hoc questionnaires were administered. Time and accuracy data from one hundred twenty participants were collected across six treatments. The between subject treatments, which had an equal number of male and female participants, were a control condition with only a compass, a control condition with a paper map available prior to maze traversal and four experimental conditions consisting of combinations of egocentric and exocentric maps, and a continuously on and on demand map display. Data collected from each participant consisted of time to traverse the maze, percent of the maze covered, estimations of euclidian distance and direction, estimations of cardinal direction, and spatial recall. Data was also collected via pre and post hoc questionnaires. Results indicate that best performance with respect to time was in the control condition with a map. The small size of the maze could have facilitated this result through route memorization. Augmented reality can offer enhancement to performance as navigational tasks become more complex and saturate working memory. Augmented reality showed best performance in accuracy by facilitating participants' coverage of the maze. Exocentric maps generally exhibited better performance than egocentric maps. On demand displays also generally resulted in better performance than continuously on displays. Gender differences also were evident with males exhibiting better performance than females. Participants reporting an initial tendency to not rotate maps exhibited better performance than those reporting a tendency to rotate maps. Enhancements being made to augmented reality and related technologies will result in more features, improved form factor for users, and improved performance in the future. Guidelines provided in this work seek to ensure augmented reality systems continue to progress in enhancing performance
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Date Issued
2004
Identifier
CFE0000177, ucf:46157
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000177
Spatial distribution and abundance of large green turtles on foraging grounds in the Florida Keys, USA.
Title
Spatial distribution and abundance of large green turtles on foraging grounds in the Florida Keys, USA.
Creator
Welsh, Ryan, Mansfield, Kate, Quintana-Ascencio, Pedro, Gorham, Jonathan, University of Central Florida
Abstract / Description
Discerning distribution, density, and abundance of organisms is essential for conservation and management of imperiled species. However, simple counts of sampled individuals are often not adequate to make such estimates, this is especially true for large and highly mobile marine animals. Green turtles (Chelonia mydas) are a highly migratory, long-lived, late-maturing, marine megafauna, that is beginning to recover from severe global population declines. Distance sampling techniques can be...
Show moreDiscerning distribution, density, and abundance of organisms is essential for conservation and management of imperiled species. However, simple counts of sampled individuals are often not adequate to make such estimates, this is especially true for large and highly mobile marine animals. Green turtles (Chelonia mydas) are a highly migratory, long-lived, late-maturing, marine megafauna, that is beginning to recover from severe global population declines. Distance sampling techniques can be used to generate estimates of abundance of green turtles in foraging grounds which have been relatively unstudied in the Northeastern Atlantic basin, filling in important data gaps in a species that is of critical conservation concern. The Quicksands foraging grounds located west of Key West, Florida, USA is used by both sub-adult and adult green turtles. Standardized transects were performed 18 times between 2006 (-) 2018, and using the collected data; abundances, spatial distribution and evidence of spatial segregation were generated through density surface models and null mode analysis. Densities of foraging green turtles rival some of the largest densities known in the world. Spatial segregation of the two size classes is evident on the foraging ground and may be attributed to differing predator detection and avoidance strategies of the size classes Finally, given the high densities of animals found on the foraging grounds and the rise in general population levels of green turtles and drop in population of green turtle predators (i.e. large sharks), concern is raised for the long term sustainably of the Quicksands seagrass pastures.
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Date Issued
2019
Identifier
CFE0007874, ucf:52767
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007874
Integrating the macroscopic and microscopic traffic safety analysis using hierarchical models
Title
Integrating the macroscopic and microscopic traffic safety analysis using hierarchical models.
Creator
Cai, Qing, Abdel-Aty, Mohamed, Eluru, Naveen, Hasan, Samiul, Lee, JaeYoung, Yan, Xin, University of Central Florida
Abstract / Description
Crash frequency analysis is a crucial tool to investigate traffic safety problems. With the objective of revealing hazardous factors which would affect crash occurrence, crash frequency analysis has been undertaken at the macroscopic and microscopic levels. At the macroscopic level, crashes from a spatial aggregation (such as traffic analysis zone or county) are considered to quantify the impacts of socioeconomic and demographic characteristics, transportation demand and network attributes so...
Show moreCrash frequency analysis is a crucial tool to investigate traffic safety problems. With the objective of revealing hazardous factors which would affect crash occurrence, crash frequency analysis has been undertaken at the macroscopic and microscopic levels. At the macroscopic level, crashes from a spatial aggregation (such as traffic analysis zone or county) are considered to quantify the impacts of socioeconomic and demographic characteristics, transportation demand and network attributes so as to provide countermeasures from a planning perspective. On the other hand, the microscopic crashes on a segment or intersection are analyzed to identify the influence of geometric design, lighting and traffic flow characteristics with the objective of offering engineering solutions (such as installing sidewalk and bike lane, adding lighting). Although numerous traffic safety studies have been conducted, still there are critical limitations at both levels. In this dissertation, several methodologies have been proposed to alleviate several limitations in the macro- and micro-level safety research. Then, an innovative method has been suggested to analyze crashes at the two levels, simultaneously. At the macro-level, the viability of dual-state models (i.e., zero-inflated and hurdle models) were explored for traffic analysis zone based pedestrian and bicycle crash analysis. Additionally, spatial spillover effects were explored in the models by employing exogenous variables from neighboring zones. Both conventional single-state model (i.e., negative binomial) and dual-state models such as zero-inflated negative binomial and hurdle negative binomial models with and without spatial effects were developed. The model comparison results for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Then, the modifiable areal unit problem for macro-level crash analysis was discussed. Macro-level traffic safety analysis has been undertaken at different spatial configurations. However, clear guidelines for the appropriate zonal system selection for safety analysis are unavailable. In this study, a comparative analysis was conducted to determine the optimal zonal system for macroscopic crash modeling considering census tracts (CTs), traffic analysis zones (TAZs), and a newly developed traffic-related zone system labeled traffic analysis districts (TADs). Poisson lognormal models for three crash types (i.e., total, severe, and non-motorized mode crashes) were developed based on the three zonal systems without and with consideration of spatial autocorrelation. The study proposed a method to compare the modeling performance of the three types of geographic units at different spatial configuration through a grid based framework. Specifically, the study region was partitioned to grids of various sizes and the model prediction accuracy of the various macro models was considered within these grids of various sizes. These model comparison results for all crash types indicated that the models based on TADs consistently offer a better performance compared to the others. Besides, the models considering spatial autocorrelation outperformed the ones that do not consider it. Finally, based on the modeling results, it is recommended to adopt TADs for transportation safety planning.After determining the optimal traffic safety analysis zonal system, further analysis was conducted for non-motorist crashes (pedestrian and bicycle crashes). This study contributed to the literature on pedestrian and bicyclist safety by building on the conventional count regression models to explore exogenous factors affecting pedestrian and bicyclist crashes at the macroscopic level. In the traditional count models, effects of exogenous factors on non-motorist crashes were investigated directly. However, the vulnerable road users' crashes are collisions between vehicles and non-motorists. Thus, the exogenous factors can affect the non-motorist crashes through the non-motorists and vehicle drivers. To accommodate for the potentially different impact of exogenous factors we converted the non-motorist crash counts as the product of total crash counts and proportion of non-motorist crashes and formulated a joint model of the negative binomial (NB) model and the logit model to deal with the two parts, respectively. The formulated joint model was estimated using non-motorist crash data based on the Traffic Analysis Districts (TADs) in Florida. Meanwhile, the traditional NB model was also estimated and compared with the joint model. The results indicated that the joint model provides better data fit and could identify more significant variables. Subsequently, a novel joint screening method was suggested based on the proposed model to identify hot zones for non-motorist crashes. The hot zones of non-motorist crashes were identified and divided into three types: hot zones with more dangerous driving environment only, hot zones with more hazardous walking and cycling conditions only, and hot zones with both. At the microscopic level, crash modeling analysis was conducted for road facilities. This study, first, explored the potential macro-level effects which are always excluded or omitted in the previous studies. A Bayesian hierarchical model was proposed to analyze crashes on segments and intersection incorporating the macro-level data, which included both explanatory variables and total crashes of all segments and intersections. Besides, a joint modeling structure was adopted to consider the potentially spatial autocorrelation between segments and their connected intersections. The proposed model was compared with three other models: a model considering micro-level factors only, one hierarchical model considering macro-level effects with random terms only, and one hierarchical model considering macro-level effects with explanatory variables. The results indicated that models considering macro-level effects outperformed the model having micro-level factors only, which supports the idea to consider macro-level effects for micro-level crash analysis. Besides, the micro-level models were even further enhanced by the proposed model. Finally, significant spatial correlation could be found between segments and their adjacent intersections, supporting the employment of the joint modeling structure to analyze crashes at various types of road facilities. In addition to the separated analysis at either the macro- or micro-level, an integrated approach has been proposed to examine traffic safety problems at the two levels, simultaneously. If conducted in the same study area, the macro- and micro-level crash analyses should investigate the same crashes but aggregating the crashes at different levels. Hence, the crash counts at the two levels should be correlated and integrating macro- and micro-level crash frequency analyses in one modeling structure might have the ability to better explain crash occurrence by realizing the effects of both macro- and micro-level factors. This study proposed a Bayesian integrated spatial crash frequency model, which linked the crash counts of macro- and micro-levels based on the spatial interaction. In addition, the proposed model considered the spatial autocorrelation of different types of road facilities (i.e., segments and intersections) at the micro-level with a joint modeling structure. Two independent non-integrated models for macro- and micro-levels were also estimated separately and compared with the integrated model. The results indicated that the integrated model can provide better model performance for estimating macro- and micro-level crash counts, which validates the concept of integrating the models for the two levels. Also, the integrated model provides more valuable insights about the crash occurrence at the two levels by revealing both macro- and micro-level factors. Subsequently, a novel hotspot identification method was suggested, which enables us to detect hotspots for both macro- and micro-levels with comprehensive information from the two levels. It is expected that the proposed integrated model and hotspot identification method can help practitioners implement more reasonable transportation safety plans and more effective engineering treatments to proactively enhance safety.
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Date Issued
2017
Identifier
CFE0006724, ucf:51891
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006724
Hierarchical Corridor Safety Analysis Using Multiple Approaches
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
Development of Traffic Safety Zones and Integrating Macroscopic and Microscopic Safety Data Analytics for Novel Hot Zone Identification
Title
Development of Traffic Safety Zones and Integrating Macroscopic and Microscopic Safety Data Analytics for Novel Hot Zone Identification.
Creator
Lee, JaeYoung, Abdel-Aty, Mohamed, Radwan, Ahmed, Nam, Boo Hyun, Kuo, Pei-Fen, Choi, Keechoo, University of Central Florida
Abstract / Description
Traffic safety has been considered one of the most important issues in the transportation field. With consistent efforts of transportation engineers, Federal, State and local government officials, both fatalities and fatality rates from road traffic crashes in the United States have steadily declined from 2006 to 2011.Nevertheless, fatalities from traffic crashes slightly increased in 2012 (NHTSA, 2013). We lost 33,561 lives from road traffic crashes in the year 2012, and the road traffic...
Show moreTraffic safety has been considered one of the most important issues in the transportation field. With consistent efforts of transportation engineers, Federal, State and local government officials, both fatalities and fatality rates from road traffic crashes in the United States have steadily declined from 2006 to 2011.Nevertheless, fatalities from traffic crashes slightly increased in 2012 (NHTSA, 2013). We lost 33,561 lives from road traffic crashes in the year 2012, and the road traffic crashes are still one of the leading causes of deaths, according to the Centers for Disease Control and Prevention (CDC). In recent years, efforts to incorporate traffic safety into transportation planning has been made, which is termed as transportation safety planning (TSP). The Safe, Affordable, Flexible Efficient, Transportation Equity Act (-) A Legacy for Users (SAFETEA-LU), which is compliant with the United States Code, compels the United States Department of Transportation to consider traffic safety in the long-term transportation planning process. Although considerable macro-level studies have been conducted to facilitate the implementation of TSP, still there are critical limitations in macroscopic safety studies are required to be investigated and remedied. First, TAZ (Traffic Analysis Zone), which is most widely used in travel demand forecasting, has crucial shortcomings for macro-level safety modeling. Moreover, macro-level safety models have accuracy problem. The low prediction power of the model may be caused by crashes that occur near the boundaries of zones, high-level aggregation, and neglecting spatial autocorrelation.In this dissertation, several methodologies are proposed to alleviate these limitations in the macro-level safety research. TSAZ (Traffic Safety Analysis Zone) is developed as a new zonal system for the macroscopic safety analysis and nested structured modeling method is suggested to improve the model performance. Also, a multivariate statistical modeling method for multiple crash types is proposed in this dissertation. Besides, a novel screening methodology for integrating two levels is suggested. The integrated screening method is suggested to overcome shortcomings of zonal-level screening, since the zonal-level screening cannot take specific sites with high risks into consideration. It is expected that the integrated screening approach can provide a comprehensive perspective by balancing two aspects: macroscopic and microscopic approaches.
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Date Issued
2014
Identifier
CFE0005195, ucf:50653
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005195
A mathematical model for feral cat ecology with application to disease.
Title
A mathematical model for feral cat ecology with application to disease.
Creator
Sharpe, Jeff, Nevai, A, Shuai, Zhisheng, Qi, Yuanwei, Quintana-Ascencio, Pedro, University of Central Florida
Abstract / Description
We formulate and analyze a mathematical model for feral cats living in an isolated colony. The model contains compartments for kittens, adult females and adult males. Kittens are born at a rate proportional to the population of adult females and mature at equal rates into adult females and adult males. Adults compete with each other in a manner analogous to Lotka-Volterra competition. This competition comes in four forms, classified by gender. Native house cats, and their effects are also...
Show moreWe formulate and analyze a mathematical model for feral cats living in an isolated colony. The model contains compartments for kittens, adult females and adult males. Kittens are born at a rate proportional to the population of adult females and mature at equal rates into adult females and adult males. Adults compete with each other in a manner analogous to Lotka-Volterra competition. This competition comes in four forms, classified by gender. Native house cats, and their effects are also considered, including additional competition and abandonment into the feral population. Control measures are also modeled in the form of per-capita removal rates. We compute the net reproduction number (R_0) for the colony and consider its influence. In the absence of abandonment, if R_0(>)1, the population always persists at a positive equilibrium and if R_0 (<)= 1, the population always tends toward local extinction. This work will be referred to as the core model.The model is then expanded to include a set of colonies (patches) such as those in the core model (this time neglecting the effect of abandonment). Adult females and kittens remain in their native patch while adult males spend a fixed proportion of their time in each patch. Adult females experience competition from both the adult females living in the same patch as well as the visiting adult males. The proportion of adult males in patch j suffer competition from both adult females resident to that patch as well the proportion of adult males also in the patch. We formulate a net reproduction number for each patch (a patch reproduction number) R_j. If R_j(>)1 for at least one patch, then the collective population always persists at some nontrivial (but possibly semitrivial) steady state. We consider the number of possible steady states and their properties. This work will be referred to as the patch model.Finally, the core model is expanded to include the introduction of the feline leukemia virus. Since this disease has many modes of transmission, each of which depends on the host's gender and life-stage, we regard this as a model disease. A basic reproduction number R_0 for the disease is defined and analyzed. Vaccination terms are included and their role in disease propagation is analyzed. Necessary and sufficient conditions are given under which the disease-free equilibrium is stable.
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Date Issued
2016
Identifier
CFE0006502, ucf:51389
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006502