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- Title
- Integrating the macroscopic and microscopic traffic safety analysis using hierarchical models.
- Creator
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Cai, Qing, Abdel-Aty, Mohamed, Eluru, Naveen, Hasan, Samiul, Lee, JaeYoung, Yan, Xin, University of Central Florida
- Abstract / Description
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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.
Show less - Date Issued
- 2017
- Identifier
- CFE0006724, ucf:51891
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006724
- 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.
Show less - Date Issued
- 2018
- Identifier
- CFE0007148, ucf:52324
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007148
- Title
- USING GIS TO DETERMINE THE INFLUENCE OF WETLANDS ON CAYUGA IROQUOIS SETTLEMENT LOCATION STRATEGIES.
- Creator
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Birnbaum, David, Walker, John, University of Central Florida
- Abstract / Description
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The archaeological record of the Iroquois supports that settlements were regularly relocated during the protohistoric period (1500-1650 A.D.). With the use of Geographic Information Systems (GIS) computer software, archaeologists may analyze variables potentially resulting in or influencing the movement of settlements. Through the use of spatial analysis, I argue that Cayuga Iroquois settlement locations were influenced by the environmental characteristics of their surrounding landscape....
Show moreThe archaeological record of the Iroquois supports that settlements were regularly relocated during the protohistoric period (1500-1650 A.D.). With the use of Geographic Information Systems (GIS) computer software, archaeologists may analyze variables potentially resulting in or influencing the movement of settlements. Through the use of spatial analysis, I argue that Cayuga Iroquois settlement locations were influenced by the environmental characteristics of their surrounding landscape. Specifically, wetlands are believed to have influenced settlement location choices in central New York state. This study examines the spatial relationships between wetland habitats and protohistoric period Cayuga Iroquois settlements where swidden maize agriculture comprised most of the diet. Considering previous research that has linked the movement of settlements to Iroquois agricultural practices, I hypothesize that wetlands played a significant role in the Iroquois subsistence system by providing supplementary plant and animal resources to a diet primarily characterized by maize consumption, and thereby influenced the strategy behind settlement relocation. Nine Cayuga Iroquois settlements dating to the protohistoric period were selected for analysis using GIS. Two control groups, each consisting of nine random points, were generated for comparison. Distance buffers show the amount of wetlands that are situated within 1-, 2.5-, and 5-kilometers from Cayuga settlements and random points. The total number of wetlands within proximity of these distances to the settlements and random points are recorded and analyzed. The results indicate a statistical significance regarding the prominence of wetlands within the landscape which pertains to the Cayuga Iroquois settlement strategy.
Show less - Date Issued
- 2011
- Identifier
- CFH0004118, ucf:44873
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004118
- Title
- Spatial distribution and abundance of large green turtles on foraging grounds in the Florida Keys, USA.
- Creator
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Welsh, Ryan, Mansfield, Kate, Quintana-Ascencio, Pedro, Gorham, Jonathan, University of Central Florida
- Abstract / Description
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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.
Show less - Date Issued
- 2019
- Identifier
- CFE0007874, ucf:52767
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007874
- Title
- HEDONIC PROPERTY VALUE MODELING OF WATER QUALITY, LAKE PROXIMITY, AND SPATIAL DEPENDENCE IN CENTRAL FLORIDA.
- Creator
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Walsh, Patrick, Milon, J. Walter, University of Central Florida
- Abstract / Description
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Hedonic property value analysis is one of the leading methods of environmental valuation. This non-market technique uses variation in home sales to infer the values of amenities or disamenities. While there have been numerous studies about air quality and hazardous waste, the number of papers focusing on water quality is much smaller. Consequently, there are still many unanswered questions about the proper handling of water quality through hedonic methods. Furthermore, estimates from hedonic...
Show moreHedonic property value analysis is one of the leading methods of environmental valuation. This non-market technique uses variation in home sales to infer the values of amenities or disamenities. While there have been numerous studies about air quality and hazardous waste, the number of papers focusing on water quality is much smaller. Consequently, there are still many unanswered questions about the proper handling of water quality through hedonic methods. Furthermore, estimates from hedonic property price analyses are rarely used in government cost benefit analyses. This dissertation investigates several important hedonic issues in a large analysis of water quality in central Florida. The first chapter of this paper explores the extent of water quality benefits. Almost all past studies have focused exclusively on waterfront homes. The present paper includes non-waterfront homes and investigates three hypotheses about the marginal impact of water quality. The first hypothesis is that non-waterfront homes are positively affected by water quality, but by a smaller amount than waterfront homes. The second hypothesis is about the effect of lake distance on the relationship between water quality and property prices: this relationship should be negative. The third hypothesis states that properties near larger lakes have a higher implicit price for water quality than homes around smaller lakes, all else constant. These three hypotheses are investigated in each chapter of the dissertation, and provide a unifying theme to the paper. Results from Chapter 1 support all three hypotheses. Most importantly, the empirical estimates indicate that water quality benefits extend beyond the waterfront in a declining gradient. Excluding non-lakefront homes from the analysis can therefore substantially underestimate the total benefits of a water quality improvement. Estimates of the total property price benefits from a one foot increase in water quality were found to double with the addition of non-waterfront homes. The second chapter examines the sensitivity of results to several spatial specifications. Spatial issues can be a problem in analyses of real estate data because of spatially correlated variables, unobservable neighborhood codes and covenants, identical or similar builders, and property appraisal valuation techniques. The focus of the chapter is on the spatial weights matrix (SWM). Six different SWM's are constructed, which are based on popular specifications encountered in the current spatial hedonic literature. An out-of-sample forecasting exercise is used to compare multiple spatial specifications. Results indicate that certain spatial models may be sensitive to the specification of the weights matrix. Furthermore, many popular models currently used in the literature could be improved by allowing more non-zero elements in the SWM. The third chapter investigates the definition of "water quality" and uses several additional quality indicators. Choosing the proper pollution indicator is an issue that has plagued many areas of the valuation literature. While clarity indicators have become popular in hedonic property price analysis, they are not used for the purposes of regulation by many state environmental departments. This chapter uses several indicators that are used by the state of Florida to classify lakes and implement policy. Implicit prices are computed for all of the indicators and issues of benefit extent and total benefits are explored. Instead of finding an optimal indicator for all situations, results indicate that the use of at least two types of indicators may capture a larger range of the true total benefits. The final chapter uses a repeat sales model to address potential problems with omitted variable bias. Due to the size of the data set in this paper, there are a substantial number of homes that have sold more than once. The repeat sales model analyzes differences in property sales prices for the same home over time. The three hypotheses of the first chapter are explored in this alternative model. The implicit price obtained from the repeat sales model is much larger than the regular hedonic model. However, there are some concerns with the smaller population of repeat sales.
Show less - Date Issued
- 2009
- Identifier
- CFE0002717, ucf:48154
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002717
- Title
- Domestic Stalking, Violation of Protective Orders, and Homicide in Chicago: The Influence of Social Disorganization and Gender Inequality.
- Creator
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Sacra, Sarah, Corzine, Harold, Huff-Corzine, Lin, Gay, David, McCutcheon, James, University of Central Florida
- Abstract / Description
-
Domestic violence has been considered a serious issue for many decades. This problem manifests itself physically, sexually, and emotionally and can affect anyone. However, most of the domestic violence literature focuses specifically on physical intimate partner violence. Various theoretical frameworks have been utilized to explain the occurrence of domestic violence including social disorganization theory and gender inequality. These explanations are limited, however, with the former...
Show moreDomestic violence has been considered a serious issue for many decades. This problem manifests itself physically, sexually, and emotionally and can affect anyone. However, most of the domestic violence literature focuses specifically on physical intimate partner violence. Various theoretical frameworks have been utilized to explain the occurrence of domestic violence including social disorganization theory and gender inequality. These explanations are limited, however, with the former primarily extended to physical assault and the latter focusing on violence against women. This study is important as it extends our knowledge of how these two perspectives can be applied to domestic violence through the analysis of domestic stalking, violation of protective orders, and homicide at a structural level. Incident data for these crimes that occurred in 2016 were obtained from the Chicago data portal and demographic data were obtained from the 2016 American Community Survey's 5-year estimates. Univariate, multivariate, and spatial analyses were conducted at the census tract level to determine the associations between the two theoretical frameworks and each crime. Statistical results indicate that social disorganization theory and gender inequality can partially explain the occurrence of domestic stalking, violation of protective orders, and homicide. Concentrated disadvantage was one of the most consistent predictors of domestic violence, but the direction of the relationship varied across models. There were significant gender inequality factors, but the directions also varied. Spatial results demonstrate clustering of the crimes in areas characterized by increased social disorganization as well as areas possessive of certain indicators of gender inequality. This study is unique as it employed both social disorganization and gender inequality frameworks at a structural level, employed various spatial analysis and mapping techniques, and it analyzed understudied acts of domestic violence to set precedent and open doors for future inquiry.
Show less - Date Issued
- 2018
- Identifier
- CFE0007089, ucf:51936
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007089
- Title
- A GIS SAFETY STUDY AND A COUNTY-LEVEL SPATIAL ANALYSIS OF CRASHES IN THE STATE OF FLORIDA.
- Creator
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Darwiche, Ali, Abdel-Aty, Mohamed, University of Central Florida
- Abstract / Description
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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.
Show less - Date Issued
- 2009
- Identifier
- CFE0002623, ucf:48204
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002623
- Title
- Development of Traffic Safety Zones and Integrating Macroscopic and Microscopic Safety Data Analytics for Novel Hot Zone Identification.
- Creator
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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.
Show less - Date Issued
- 2014
- Identifier
- CFE0005195, ucf:50653
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005195
- Title
- ARCHAEOLOGICAL GIS ANALYSIS OF RAISED FIELD AGRICULTURE IN THE BOLIVIAN AMAZON.
- Creator
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Lee, Thomas W, Walker, John, University of Central Florida
- Abstract / Description
-
Modern agricultural systems have been criticized for their detrimental effects on the environment and a general emphasis on crop yield rather than long-term sustainability. Traditional forms of agriculture may provide case-specific examples of sustainable alternatives for contemporary societies. In the seasonally inundated savannas of the Llanos de Mojos, pre-Columbian Indians piled earth into 'large raised field platforms' elevated high enough above the floodplain to allow crops to grow....
Show moreModern agricultural systems have been criticized for their detrimental effects on the environment and a general emphasis on crop yield rather than long-term sustainability. Traditional forms of agriculture may provide case-specific examples of sustainable alternatives for contemporary societies. In the seasonally inundated savannas of the Llanos de Mojos, pre-Columbian Indians piled earth into 'large raised field platforms' elevated high enough above the floodplain to allow crops to grow. Archaeological evidence indicates that raised field agriculture supported much larger populations than those found in the Beni today. The examination of satellite imagery has revealed more than 40,000 individual fields spread across an area of approximately 7,500 square kilometers. This study created a digitized map of large raised fields to search for spatial patterns in their distribution. A GIS analysis was conducted in which fields were distributed into organizational groups based on characteristics such as proximity and orientation to cardinal direction. These groups represent potential 'social units' involved in the organization of labor required to construct raised fields. This study demonstrated the consistent presence of these units throughout the entirety of the agricultural system. Patterns in the distribution of these groups allowed the study area to be divided into two distinct regions representing a larger scale of organization within a seemingly uniform system. A transitional zone between these two regions was identified on the river Omi, providing a clear area of interest to target in future archaeological excavations. Further archaeological investigations of raised field agriculture have the potential of demonstrating the overall productivity of the system as well as how it was incorporated into the social systems of those who managed it.
Show less - Date Issued
- 2017
- Identifier
- CFH2000192, ucf:45990
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000192
- 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
Show less - Date Issued
- 2018
- Identifier
- CFE0006967, ucf:51666
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006967
