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REDUCED VISIBILITY RELATED CRASHES IN FLORIDA: CRASH CHARACTERISTICS, SPATIAL ANALYSIS AND INJURY SEVERITY
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
SAFETY ANALYSES AT SIGNALIZED INTERSECTIONS CONSIDERING SPATIAL, TEMPORAL AND SITE CORRELATION
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
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
LEVEL-OF-SERVICE AND TRAFFIC SAFETY RELATIONSHIP: AN EXPLORATORY ANALYSIS OF SIGNALIZED INTERSECTIONS AND MULTILANE HIGH-SPEED ARTERIAL CORRIDORS
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
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
A GIS SAFETY STUDY AND A COUNTY-LEVEL SPATIAL ANALYSIS OF CRASHES IN THE STATE OF FLORIDA
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
Pedestrian Safety Analysis through Effective Exposure Measures and Examination of Injury Severity
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