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Title: Real-time traffic safety evaluation models and their application for variable speed limits.
Creator: Yu, Rongjie, Abdel-Aty, Mohamed, Radwan, Ahmed, Madani Larijani, Kaveh, Ahmed, Mohamed, Wang, Xuesong, University of Central Florida
Abstract / Description: Traffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly...
Show moreTraffic safety has become the first concern in the transportation area. Crashes have cause extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence at both the aggregate (targeting crash frequency per segment, intersection, etc.,) and disaggregate levels (analyzing each crash event). The aggregate traffic safety studies, mainly developing safety performance functions (SPFs), are being conducted for the purpose of unveiling crash contributing factors for the interest locations. Results of the aggregate traffic safety studies can be used to identify crash hot spots, calculate crash modification factors (CMF), and improve geometric characteristics. Aggregate analyses mainly focus on discovering the hazardous factors that are related to the frequency of total crashes, of specific crash type, or of each crash severity level. While disaggregate studies benefit from the reliable surveillance systems which provide detailed real-time traffic and weather data. This information could help in capturing microlevel influences of the hazardous factors which might lead to a crash. The disaggregate traffic safety models, also called real-time crash risk evaluation models, can be used in monitoring crash hazardousness with the real-time field data fed in. One potential use of real-time crash risk evaluation models is to develop Variable Speed Limits (VSL) as a part of a freeway management system. Models have been developed to predict crash occurrence to proactively improve traffic safety and prevent crash occurrence.In this study, first, aggregate safety performance functions were estimated to unveil the different risk factors affecting crash occurrence for a mountainous freeway section. Then disaggregate real-time crash risk evaluation models have been developed for the total crashes with both the machine learning and hierarchical Bayesian models. Considering the need for analyzing both aggregate and disaggregate aspects of traffic safety, systematic multi-level traffic safety studies have been conducted for single- and multi-vehicle crashes, and weekday and weekend crashes. Finally, the feasibility of utilizing a VSL system to improve traffic safety on freeways has been investigated. This research was conducted based on data obtained from a 15-mile mountainous freeway section on I-70 in Colorado. The data contain historical crash data, roadway geometric characteristics, real-time weather data, and real-time traffic data. Real-time weather data were recorded by 6 weather stations installed along the freeway section, while the real-time traffic data were obtained from the Remote Traffic Microwave Sensor (RTMS) radars and Automatic Vechicle Identification (AVI) systems. Different datasets have been formulated from various data sources, and prepared for the multi-level traffic safety studies. In the aggregate traffic safety investigation, safety performance functions were developed to identify crash occurrence hazardous factors. For the first time real-time weather and traffic data were used in SPFs. Ordinary Poisson model and random effects Poisson models with Bayesian inference approach were employed to reveal the effects of weather and traffic related variables on crash occurrence. Two scenarios were considered: one seasonal based case and one crash type based case. Deviance Information Criterion (DIC) was utilized as the comparison criterion; and the correlated random effects Poisson models outperform the others. Results indicate that weather condition variables, especially precipitation, play a key role in the safety performance functions. Moreover, in order to compare with the correlated random effects Poisson model, Multivariate Poisson model and Multivariate Poisson-lognormal model have been estimated. Conclusions indicate that, instead of assuming identical random effects for the homogenous segments, considering the correlation effects between two count variables would result in better model fit. Results from the aggregate analyses shed light on the policy implication to reduce crash frequencies. For the studied roadway segment, crash occurrence in the snow season have clear trends associated with adverse weather situations (bad visibility and large amount of precipitation); weather warning systems can be employed to improve road safety during the snow season. Furthermore, different traffic management strategies should be developed according to the distinct seasonal influence factors. In particular, sites with steep slopes need more attention from the traffic management center and operators especially during snow seasons to control the excess crash occurrence. Moreover, distinct strategy of freeway management should be designed to address the differences between single- and multi-vehicle crash characteristics.In addition to developing safety performance functions with various modeling techniques, this study also investigates four different approaches of developing informative priors for the independent variables. Bayesian inference framework provides a complete and coherent way to balance the empirical data and prior expectations; merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance Information Criterion, R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparisons across the models indicate that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies.In addition to the aggregate analyses, real-time crash risk evaluation models have been developed to identify crash contributing factors at the disaggregate level. Support Vector Machine (SVM), a recently proposed statistical learning model and Hierarchical Bayesian logistic regression models were introduced to evaluate real-time crash risk. Classification and regression tree (CART) model has been developed to select the most important explanatory variables. Based on the variable selection results, Bayesian logistic regression models and SVM models with different kernel functions have been developed. Model comparisons based on receiver operating curves (ROC) demonstrate that the SVM model with Radial basis kernel function outperforms the others. Results from the models demonstrated that crashes are likely to happen during congestion periods (especially when the queuing area has propagated from the downstream segment); high variation of occupancy and/or volume would increase the probability of crash occurrence.Moreover, effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types have been investigated. Crashes have been categorized as rear-end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristics data were utilized as explanatory variables. Conclusions from this study imply that different active traffic management (ATM) strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects. Based on the abovementioned results, real-time crash risk evaluation models have been developed separately for multi-vehicle and single-vehicle crashes, and weekday and weekend crashes. Hierarchical Bayesian logistic regression models (random effects and random parameter logistic regression models) have been introduced to address the seasonal variations, crash unit level's diversities, and unobserved heterogeneity caused by geometric characteristics. For the multi-vehicle crashes: congested conditions at downstream would contribute to an increase in the likelihood of multi-vehicle crashes; multi-vehicle crashes are more likely to occur during poor visibility conditions and if there is a turbulent area that exists downstream. Drivers who are unable to reduce their speeds timely are prone to causing rear-end crashes. While for the single-vehicle crashes: slow moving traffic platoons at the downstream detector of the crash occurrence locations would increase the probability of single-vehicle crashes; large variations of occupancy downstream would also increase the likelihood of single-vehicle crash occurrence.Substantial efforts have been dedicated to revealing the hazardous factors that affect crash occurrence from both the aggregate and disaggregate level in this study, however, findings and conclusions from these research work need to be transferred into applications for roadway design and freeway management. This study further investigates the feasibility of utilizing Variable Speed Limits (VSL) system, one key part of ATM, to improve traffic safety on freeways. A proactive traffic safety improvement VSL control algorithm has been proposed. First, an extension of the traffic flow model METANET was employed to predict traffic flow while considering VSL's impacts on the flow-density diagram; a real-time crash risk evaluation model was then estimated for the purpose of quantifying crash risk; finally, the optimal VSL control strategies were achieved by employing an optimization technique of minimizing the total predicted crash risks along the VSL implementation area. Constraints were set up to limit the increase of the average travel time and differences between posted speed limits temporarily and spatially. The proposed VSL control strategy was tested for a mountainous freeway bottleneck area in the microscopic simulation software VISSIM. Safety impacts of the VSL system were quantified as crash risk improvements and speed homogeneity improvements. Moreover, three different driver compliance levels were modeled in VISSIM to monitor the sensitivity of VSL's safety impacts on driver compliance levels. Conclusions demonstrate that the proposed VSL system could effectively improve traffic safety by decreasing crash risk, enhancing speed homogeneity, and reducing travel time under both high and moderate driver compliance levels; while the VSL system does not have significant effects on traffic safety enhancement under the low compliance scenario. Future implementations of VSL control strategies and related research topics were also discussed.
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Date Issued: 2013
Identifier: CFE0005283, ucf:50556
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005283

Title: A Framework for Assessing Sustainability Impacts of Truck Routing Strategies.
Creator: Laman, Haluk, Abdel-Aty, Mohamed, Tatari, Omer, Ahmed, Mohamed, University of Central Florida
Abstract / Description: The impact of freight on our transportation system is further accentuated by the fact that trucks consume greater roadway capacity and therefore cause more significant problems including traffic congestion, delay, crashes, air pollution, fuel consumption, and pavement damage. Assessing the actual effects of truck traffic is a growing need to support the ability to safely and efficiently move goods and people in areas where roadway expansion is not the best option. On one hand, trucks need to...
Show moreThe impact of freight on our transportation system is further accentuated by the fact that trucks consume greater roadway capacity and therefore cause more significant problems including traffic congestion, delay, crashes, air pollution, fuel consumption, and pavement damage. Assessing the actual effects of truck traffic is a growing need to support the ability to safely and efficiently move goods and people in areas where roadway expansion is not the best option. On one hand, trucks need to efficiently serve commerce and industry, while at the same time their activities need not contribute to a decline in the quality or public safety. In the current practice, to the best of the authors' knowledge, there is no framework methodology for real-time management of traffic, specifically on truck routes, to reduce travel duration and avoid truck travel delays due to non-recurring congestion (i.e. traffic incidents) and to estimate impacts on traffic flows, economy, and environment. The objective of this study is to develop a truck routing strategy and to quantify its' impacts on travel time, emissions and consequently assess the effects on the economy and environment. In order to estimate non-recurrent congestion based travel delay and fuel consumption by real-time truck routing simulation models, significant corridors with high truck percentages were selected. Furthermore, tailpipe emissions (on-site) due to traveled distance and idling are estimated via MOVES emissions simulator software. Economic Input Output-Life Cycle Assessment Model is utilized to gather fuel consumption related upstream (off-site) emissions. Simulation results of various scenarios indicated that potential annual value of time savings can reach up to $1.67 million per selected corridor. Consistently, fuel costs and emission values are lower, even though extra miles are traveled on the alternative route. In conclusion, our study confirms that truck routing strategies in incident conditions have high economic and environmental impacts.
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Date Issued: 2018
Identifier: CFE0007577, ucf:52570
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007577

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

Title: ELECTIMIZE: A NEW EVOLUTIONARY ALGORITHM FOR OPTIMIZATION WITH APPLICATIONS IN CONSTRUCTION ENGINEERING.
Creator: Abdel-Raheem, Mohamed, Khalafallah, Ahmed, University of Central Florida
Abstract / Description: Optimization is considered an essential step in reinforcing the efficiency of performance and economic feasibility of construction projects. In the past few decades, evolutionary algorithms (EAs) have been widely utilized to solve various types of construction-related optimization problems due to their efficiency in finding good solutions in relatively short time periods. However, in many cases, these existing evolutionary algorithms failed to identify the optimal solution to several...
Show moreOptimization is considered an essential step in reinforcing the efficiency of performance and economic feasibility of construction projects. In the past few decades, evolutionary algorithms (EAs) have been widely utilized to solve various types of construction-related optimization problems due to their efficiency in finding good solutions in relatively short time periods. However, in many cases, these existing evolutionary algorithms failed to identify the optimal solution to several optimization problems. As such, it is deemed necessary to develop new approaches in order to help identify better-quality solutions. This doctoral research presents the development of a new evolutionary algorithm, named "Electimize," that is based on the simulation of the flow of electric current in the branches of an electric circuit. The main motive in this research is to provide the construction industry with a robust optimization tool that overcomes some of the shortcomings of existing EAs. In solving optimization problems using Electimize, a number of wires (solution strings) composed of a number of segments are fabricated randomly. Each segment corresponds to a decision variable in the objective function. The wires are virtually connected in parallel to a source of an electricity to represent an electric circuit. The electric current passing through each wire is calculated by substituting the values of the segments in the objective function. The quality of the wire is based on its global resistance, which is calculated using Ohm's law. The main objectives of this research are to 1) develop an optimization methodology that is capable of evaluating the quality of decision variable values in the solution string independently; 2) devise internal optimization mechanisms that would enable the algorithm to extensively search the solution space and avoid its convergence toward local optima; and 3) provide the construction industry with a reliable optimization tool that is capable of solving different classes of NP-hard optimization problems. First, internal processes are designed, modeled, and tested to enable the individual assessment of the quality of each decision variable value available in the solution space. The main principle in assessing the quality of each decision variable value individually is to use the segment resistance (local resistance) as an indicator of the quality. This is accomplished by conducting a sensitivity analysis to record the change in the resistance of a control wire, when a certain decision variable value is substituted into the corresponding segment of the control wire. The calculated local resistances of all segments of a wire are then normalized to ensure that their summation is equal to the global wire resistance and no violation is made of Kirchhoff's rule. A benchmark NP-hard cash flow management problem from the literature is attempted to test and validate the performance of the developed approach. Not only was Electimize able to identify the optimal solution for the problem, but also it identified ten alternative optimal solutions, outperforming the existing algorithms. Second, the internal processes for the sensitivity analysis are designed to allow for extensive search of the solution space through the generation of new wires. Every time a decision variable value is substituted in the control wire to assess its quality, a new wire that might have a better quality is generated. To further test the capabilities of Electimize in searching the solution space, Electimize was applied to a multimodal 9-city travelling salesman problem (TSP) that had been previously designed and solved mathematically. The problem has 27 alternative optimal solutions. Electimize succeeded to identify 21 of the 27 alternative optimal solutions in a limited time period. Moreover, Electimize was applied to a 16-city benchmark TSP (Ulysses16) and was able to identify the optimal tour and its alternative. Further, additional parameters are incorporated to 1) allow for the extensive search of the solution space, 2) prevent the convergence towards local optima, and 3) increase the rate of convergence towards the global optima. These parameters are classified into two categories: 1) resistance related parameters, and 2) solution exploration parameters. The resistance related parameters are: a) the conductor resistivity, b) its cross-sectional area, and c) the length of each segment. The main role of this set of parameters is to provide the algorithm with additional gauging parameters to help guide it towards the global optima. The solution exploration parameters included a) the heat factor, and b) the criterion of selecting the control wire. The main role of this set of parameters is to allow for an extensive search of the solution space in order to facilitate the identification all the available alternative optimal solutions; prevent the premature convergence towards local optima; and increase the rate of convergence towards the global optima. Two TSP instances (Bayg29 and ATT48) are attempted and the results obtained illustrate that Electimize outperforms other EAs with respect to the quality of solutions obtained. Third, to test the capabilities of Electimize as a reliable optimization tool in construction optimization problems, three benchmark NP-hard construction optimization problems are attempted. The first problem is the cash flow management problem, as mentioned earlier. The second problem is the time cost tradeoff problem (TCTP) and is used as an example of static optimization. The third problem is a site layout planning problem (SLPP), and represents dynamic optimization. When Electimize was applied to the TCTP, it succeeded to identify the optimal solution of the problem in a single iteration using thirty solution strings, compared to hundreds of iterations and solution strings that were used by EAs to solve the same problem. Electimize was also successful in solving the SLPP and outperformed the existing algorithm used to solve the problem by identifying a better optimal solution. The main contributions of this research are 1) developing a new approach and algorithm for optimization based on the simulation of the phenomenon of electrical conduction, 2) devising processes that enable assessing the quality of decision variable values independently, 3) formulating methodologies that allow for the extensive search of the solution space and identification of alternative optimal solutions, and 4) providing a robust optimization tool for decision makers and construction planners.
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Date Issued: 2011
Identifier: CFE0003954, ucf:48698
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003954

Title: Sustainable Transportation at the University of Central Florida: Evaluation of UCF Rideshare Program, Zimride.
Creator: Defrancisco, Joseph, Radwan, Ahmed, Abdel-Aty, Mohamed, Harb, Rami, University of Central Florida
Abstract / Description: As the second-largest university in the United States, UCF has experienced the largest enrollment in its history. A more densely populated campus has in turn caused increased traffic congestion. Despite increased parking permit fees and newly constructed parking garages, traveling and parking on campus is unpredictable. In effort to reduce congestion on campus, a rideshare program was implemented in Summer 2010. Several universities across the nation have successfully used carpooling as a...
Show moreAs the second-largest university in the United States, UCF has experienced the largest enrollment in its history. A more densely populated campus has in turn caused increased traffic congestion. Despite increased parking permit fees and newly constructed parking garages, traveling and parking on campus is unpredictable. In effort to reduce congestion on campus, a rideshare program was implemented in Summer 2010. Several universities across the nation have successfully used carpooling as a viable alternative mode to manage traffic and parking demand. This thesis evaluates the UCF rideshare program, Zimride, using stated- and revealed-preference surveys. Preliminary results indicate most students prefer to commute to campus using their own car and without incentives there is no reason to change mode choice, regardless of associated costs(-)e.g. decal cost, parking time and frustration. Despite 70% of respondents considering themselves environmentally friendly and over 80% are aware of savings in money and productive by using alternative modes, 70% still use their car to commute to campus. Using Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM), the observed variables were organized into three (3) latent variables based on the correlation among them. The SEM results of the revealed-preference survey indicate current travel behavior significantly influences attitudes towards carpooling and demographics have a significant effect on current travel behavior. It was also found that demographics influences attitudes towards carpooling at a non statistically significant level.
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Date Issued: 2012
Identifier: CFE0004226, ucf:48996
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004226

Title: Evaluation and Modeling of the Safety of Open Road Tolling System.
Creator: Abuzwidah, Muamer, Abdel-Aty, Mohamed, Radwan, Ahmed, Uddin, Nizam, University of Central Florida
Abstract / Description: The goal of this thesis is to examine the traffic safety impact of upgrading Toll Plazas (TP) to Open Road Tolling (ORT). The ORT could enhance safety but could also pose some traffic safety concerns at Toll plazas. Crashes from eight years were investigated by evaluating the crash data before and after the implementation of the ORT.The study was conducted by using two approaches: 1) a simple before and after study and with a comparison group; 2) a modeling effort to help understand the...
Show moreThe goal of this thesis is to examine the traffic safety impact of upgrading Toll Plazas (TP) to Open Road Tolling (ORT). The ORT could enhance safety but could also pose some traffic safety concerns at Toll plazas. Crashes from eight years were investigated by evaluating the crash data before and after the implementation of the ORT.The study was conducted by using two approaches: 1) a simple before and after study and with a comparison group; 2) a modeling effort to help understand the relationship between the crash frequency and several important factors and circumstances such as injury severity, collision types, average daily traffic (ADT) and Toll plaza characteristics. The study investigated 11 Toll plazas on State Roads 408, 417, 528 and 429 that have been changed to the ORT design. Several maps showing the Toll plazas and identifying the relevant crash locations were generated. Negative Binomial (NB), Log Linear model and two-way contingency table were examined. Two log-linear models with three variables in each model with all possible two-way interactions were developed. Categorical data analysis of the 2009 and 2010 crash dataset was performed. In order to compare the differences in response between the crash frequency and a particular crash-related variable, odds ratios were computed. The effects of crash frequency and crash-related factors were examined, and interactions among them were considered. The results indicated significant relationships between the crash frequency and ADT, crash type and driver age.It is worth mentioning that the expressway network understudy was continuously experiencing constructions throughout the study period. There is indication that ORT reduced the total crash number; also there is indication of changing the crash types and locations; and the majority of crashes occurred at the diverging and merging areas and resulted in more severe crashes. More data may be needed to confirm these results especially after all constructions and upgrades are made.The Implementation of open road tolling, the locations of Toll plazas, Automatic Vehicle Identification (AVI) subscription rate, traffic demand, and plaza geometry all may have a high influence on traffic safety concerns at Toll plazas, as concluded from the negative Binomial Model's results. The changing of sign locations, reducing the speed limit, installing variable message signs, configuring plazas properly, and other considerations may be the solution to overcome the potential safety problems in the vicinity of Toll plazas.The change of design to ORT was proven to be an excellent solution to several traffic operation problems, including reducing congestion and improving traffic flow and capacity at Toll plazas. However, addressing safety concerns at Toll plazas should take priority.
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Date Issued: 2011
Identifier: CFE0004466, ucf:49330
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004466

Title: Multi-Level Safety Performance Functions for High Speed Facilities.
Creator: Ahmed, Mohamed, Abdel-Aty, Mohamed, Radwan, Ahmed, Al-Deek, Haitham, Mackie, Kevin, Pande, Anurag, Uddin, Nizam, University of Central Florida
Abstract / Description: High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the...
Show moreHigh speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the crash risk on long and short term basis. Therefore, the main focus of the research in this dissertation is to provide a framework of risk assessment to promote safety and enhance mobility on freeways and expressways. Multi-level Safety Performance Functions (SPFs) were developed at the aggregate level using historical crash data and the corresponding exposure and risk factors to identify and rank sites with promise (hot-spots). Additionally, SPFs were developed at the disaggregate level utilizing real-time weather data collected from meteorological stations located at the freeway section as well as traffic flow parameters collected from different detection systems such as Automatic Vehicle Identification (AVI) and Remote Traffic Microwave Sensors (RTMS). These disaggregate SPFs can identify real-time risks due to turbulent traffic conditions and their interactions with other risk factors.In this study, two main datasets were obtained from two different regions. Those datasets comprise historical crash data, roadway geometrical characteristics, aggregate weather and traffic parameters as well as real-time weather and traffic data.At the aggregate level, Bayesian hierarchical models with spatial and random effects were compared to Poisson models to examine the safety effects of roadway geometrics on crash occurrence along freeway sections that feature mountainous terrain and adverse weather. At the disaggregate level; a main framework of a proactive safety management system using traffic data collected from AVI and RTMS, real-time weather and geometrical characteristics was provided. Different statistical techniques were implemented. These techniques ranged from classical frequentist classification approaches to explain the relationship between an event (crash) occurring at a given time and a set of risk factors in real time to other more advanced models. Bayesian statistics with updating approach to update beliefs about the behavior of the parameter with prior knowledge in order to achieve more reliable estimation was implemented. Also a relatively recent and promising Machine Learning technique (Stochastic Gradient Boosting) was utilized to calibrate several models utilizing different datasets collected from mixed detection systems as well as real-time meteorological stations. The results from this study suggest that both levels of analyses are important, the aggregate level helps in providing good understanding of different safety problems, and developing policies and countermeasures to reduce the number of crashes in total. At the disaggregate level, real-time safety functions help toward more proactive traffic management system that will not only enhance the performance of the high speed facilities and the whole traffic network but also provide safer mobility for people and goods. In general, the proposed multi-level analyses are useful in providing roadway authorities with detailed information on where countermeasures must be implemented and when resources should be devoted. The study also proves that traffic data collected from different detection systems could be a useful asset that should be utilized appropriately not only to alleviate traffic congestion but also to mitigate increased safety risks. The overall proposed framework can maximize the benefit of the existing archived data for freeway authorities as well as for road users.
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Date Issued: 2012
Identifier: CFE0004508, ucf:49274
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004508

Title: Investigating and Facilitating the Transferability of Safety Performance Functions.
Creator: Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
Abstract / Description: Safety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public...
Show moreSafety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public or private, may opt to not invest their resources in data collection and processing to develop own localized SPFs. Instead, the agencies may adopt the HSM's. However, the HSM's SPFs may not necessarily be applicable to any conditions. Hence, this research is focused on SPF transferability, specifically for rural divided multilane highway segments. Use of Bayesian informative priors to aid in the transferability of NB SPFs, developed for Florida, to California's conditions and vice versa is investigated. It is demonstrated that informative priors facilitate SPF transferability. Furthermore, NB SPFs are developed for Florida, Ohio, Illinois, Minnesota, California, Washington and North Carolina. That is to evaluate the transferability of each state's SPFs to the other states' conditions. The results indicate that Ohio, Illinois, Minnesota and California have SPFs that are transferable to conditions of each of the four states. Also, two methods are proposed for calibrating transferred SPFs to the destinations' conditions and are shown to outperform the SPF calibration methods in the road safety literature. Finally, a variety of modeling frameworks are proposed for developing and transferring SPFs of the seven aforementioned states to each state's data. Not a single model exhibits the best fit when transferred in all cases. However, the Tobit model, NB model and a hybrid model that coalesces the results of both perform the best in a substantial number of the transferred SPFs.
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Date Issued: 2018
Identifier: CFE0007000, ucf:52054
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007000

Title: Examining Multiple Approaches for the Transferability of Safety Performance Functions.
Creator: Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
Abstract / Description: Safety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are...
Show moreSafety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are not available, it is custom to adopt nationwide SPFs for crash predictions then apply a calibration factor. Yet, the research is limited regarding the application of national SPFs for local jurisdictions. In this study, the topic of transferability is explored by examining rural multilane highway SPFs from Florida, Ohio, and California. That is for both divided segments and intersections. Traffic, road geometrics and crash data from the three states are collected to develop one-state, two-state and three-state SPFs. The SPFs are negative binomial models taking the form of those of the HSM. Evaluation of the transferability of models is undertaken by calculating a measure known as the transfer index. It is used to explain which SPFs may be transferred tolerably to other jurisdictions. According to the results, the transferability of rural divided segments' SPFs of Florida to California and vice versa is superior to that of Ohio's SPFs. For four-leg signalized intersections, neither state's models are transferable to any state. Also, the transfer index indicates improved transferability when using pooled data from multiple states. Furthermore, a modified version of the Empirical Bayes method that is responsible for segment specific adjustment factors is proposed as an alternative to the HSM calibration method. It is used to adjust crash frequencies predicted by the SPFs being transferred to the jurisdiction of interest. The modified method, proposed, outperforms the HSM calibration method as per the analysis results.
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Date Issued: 2015
Identifier: CFE0006298, ucf:51604
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006298

Title: Financial evaluation of milege based user fees for Florida's transportation funding.
Creator: Moradi, Massoud, Al-Deek, Haitham, Radwan, Ahmed, Abdel-Aty, Mohamed, Uddin, Nizam, University of Central Florida
Abstract / Description: ABSTRACTMotor fuel taxes have been collected as a principal source of highway funding for close to a century. They account for approximately two thirds of all the highway user fees and about half of all highway expenditures. Federal fuel taxes have not kept pace with the inflation in general and increasing traffic demand and resulting construction, maintenance and operation costs of the transportation assets in particular.Lack of political will, combined with rising anti-tax sentiment among...
Show moreABSTRACTMotor fuel taxes have been collected as a principal source of highway funding for close to a century. They account for approximately two thirds of all the highway user fees and about half of all highway expenditures. Federal fuel taxes have not kept pace with the inflation in general and increasing traffic demand and resulting construction, maintenance and operation costs of the transportation assets in particular.Lack of political will, combined with rising anti-tax sentiment among the populace, has kept the federal tax level not only well below its initial intents, but also at a unsustainable level in future.Mileage based user fees are possibly an alternative to the fuel taxes, which have been the main mechanism for funding the transportation system.Mileage based user fees have been successfully utilized in many parts of the world with glowing results. Germany's (")TollCollect("), a quasi government enterprise has utilized GPS technology in collecting the users' fee from the truck operators. The system has been a financial engine providing much needed funding for many major transportation projects. Oregon Department of Transportation, in a federally co-funded pilot project, examined the practicality of the mileage based user fee collection at the fuel pumps. According to the Oregon study, there are not any major technical difficulties in mileage based user fee collection at the pump. Study participants (general motorist) did not express any objection to the mileage based user fee collection.This dissertation evaluates revenue impacts of several pricing policies including: Current per gallon fuel taxes, conversion to a mileage based user fee, time of day user fee application, area type user fee and congestion priced user fees. State of Florida's years 2015-2035 fuel revenue forecast is used as a case study. A model is constructed to estimate annual vehicle miles travelled for the analyses period. Fuel efficiencies, current per gallon fuel taxes and their corresponding mileage-based user fee equivalents are the input to a financial model developed for comparisons. Results demonstrate that decrease in fuel revenues due to vehicles fuel efficiency improvements can be offset by replacing current per gallon fuel taxes with a mileage-based user fee. Pricing the user fee according to area type, roadway classification, time of day and congestion level can not only generate more revenues but also assist in demand management.
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Date Issued: 2012
Identifier: CFE0004416, ucf:49378
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004416

Title: A Comparative Evaluation of FDSA,GA, and SA Non-Linear Programming Algorithms and Development of System-Optimal Dynamic Congestion Pricing Methodology on I-95 Express.
Creator: Graham, Don, Radwan, Ahmed, Abdel-Aty, Mohamed, Al-Deek, Haitham, Uddin, Nizam, University of Central Florida
Abstract / Description: As urban population across the globe increases, the demand for adequatetransportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities.High (-)Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today's highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases,...
Show moreAs urban population across the globe increases, the demand for adequatetransportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities.High (-)Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today's highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases, is one such HOT facility. With the growing abundance of such facilities comes the need for in- depth study of demand patterns and development of an appropriate pricing scheme which reduces congestion.This research develops a method for dynamic pricing on the I-95 HOT facility such as to minimize total travel time and reduce congestion. We apply non-linear programming (NLP) techniques and the finite difference stochastic approximation (FDSA), genetic algorithm (GA) and simulated annealing (SA) stochastic algorithms to formulate and solve the problem within a cell transmission framework. The solution produced is the optimal flow and optimal toll required to minimize total travel time and thus is the system-optimal solution.We perform a comparative evaluation of FDSA, GA and SA non-linear programmingalgorithms used to solve the NLP and the ANOVA results show that there are differences in the performance of the NLP algorithms in solving this problem and reducing travel time. We then conclude by demonstrating that econometric forecasting methods utilizing vector autoregressive (VAR) techniques can be applied to successfully forecast demand for Phase 2 of the 95 Express which is planned for 2014.
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Date Issued: 2013
Identifier: CFE0005000, ucf:50019
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005000

Title: Warrants for Right-Turn Flashing Yellow Arrow Signal Phases.
Creator: Alfawzan, Mohammed, Radwan, Ahmed, Eluru, Naveen, Abou-Senna, Hatem, Zheng, Qipeng, University of Central Florida
Abstract / Description: The right-turn flashing yellow arrow (FYA) signal phasing is a new signal practice in the United States. The Manual on Uniform Traffic Control Devices MUTCD (2009) allocates a signal phasing section for the right-turn FYA, which requires a four-section head FYA signal. It supports multiple phases' indications that guide the motorist through permissive, protected, and/or permissive/protected phases. For this dissertation, I investigated three permissive right-turn FYA signal phases in various...
Show moreThe right-turn flashing yellow arrow (FYA) signal phasing is a new signal practice in the United States. The Manual on Uniform Traffic Control Devices MUTCD (2009) allocates a signal phasing section for the right-turn FYA, which requires a four-section head FYA signal. It supports multiple phases' indications that guide the motorist through permissive, protected, and/or permissive/protected phases. For this dissertation, I investigated three permissive right-turn FYA signal phases in various traffic conditions and signal timing circumstances. The first permissive right-turn FYA signal phase is the tight-turn on impeding through (RTOIT) taking place during the cross-street through traffic movement. The second permissive right-turn FYA signal phase occurs during the opposing left-turn approach movement and so is called the right-turn on impeding left (RTOIL). The third permissive right-turn phase is a right-turn on through green impeded only by the side street pedestrians called the right-turn on adjacent through (RTOAT). I aimed to develop warrants leading to efficient implementation of permissive right-turn FYA signal phases based on microsimulation analysis. I developed multinomial logit models to establish a decision support system that predicts the efficiency attributes of the permissive right-turn FYA signal phases.
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Date Issued: 2019
Identifier: CFE0007883, ucf:52801
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007883

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

Title: Microscopic Assessment of Transportation Emissions on Limited Access Highways.
Creator: Abou-Senna, Hatem, Radwan, Ahmed, Abdel-Aty, Mohamed, Al-Deek, Haitham, Cooper, Charles, Johnson, Mark, University of Central Florida
Abstract / Description: On-road vehicles are a major source of transportation carbon dioxide (CO2) greenhouse gas emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, e.g., carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). The need to accurately quantify transportation-related emissions from vehicles is essential. Transportation agencies and researchers in the past have...
Show moreOn-road vehicles are a major source of transportation carbon dioxide (CO2) greenhouse gas emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, e.g., carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). The need to accurately quantify transportation-related emissions from vehicles is essential. Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The new United States Environmental Protection Agency (USEPA) mobile source emissions model, MOVES2010a (MOVES) can estimate vehicle emissions on a second-by-second basis creating the opportunity to develop new software (")VIMIS 1.0(") (VISSIM/MOVES Integration Software) to facilitate the integration process. This research presents a microscopic examination of five key transportation parameters (traffic volume, speed, truck percentage, road grade and temperature) on a 10-mile stretch of Interstate 4 (I-4) test bed prototype; an urban limited access highway corridor in Orlando, Florida. The analysis was conducted utilizing VIMIS 1.0 and using an advanced custom design technique; D-Optimality and I-Optimality criteria, to identify active factors and to ensure precision in estimating the regression coefficients as well as the response variable.The analysis of the experiment identified the optimal settings of the key factors and resulted in the development of Micro-TEM (Microscopic Transportation Emissions Meta-Model). The main purpose of Micro-TEM is to serve as a substitute model for predicting transportation emissions on limited access highways to an acceptable degree of accuracy in lieu of running simulations using a traffic model and integrating the results in an emissions model. Furthermore, significant emission rate reductions were observed from the experiment on the modeled corridor especially for speeds between 55 and 60 mph while maintaining up to 80% and 90% of the freeway's capacity. However, vehicle activity characterization in terms of speed was shown to have a significant impact on the emission estimation approach.Four different approaches were further examined to capture the environmental impacts of vehicular operations on the modeled test bed prototype. First, (at the most basic level), emissions were estimated for the entire 10-mile section (")by hand(") using one average traffic volume and average speed. Then, three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-by-second link driving schedules (LDS), and second-by-second operating mode distributions (OPMODE). This research analyzed how the various approaches affect predicted emissions of CO, NOx, PM and CO2. The results demonstrated that obtaining accurate and comprehensive operating mode distributions on a second-by-second basis improves emission estimates. Specifically, emission rates were found to be highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, frequent braking/coasting and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach.Additionally, model applications and mitigation scenarios were examined on the modeled corridor to evaluate the environmental impacts in terms of vehicular emissions and at the same time validate the developed model (")Micro-TEM("). Mitigation scenarios included the future implementation of managed lanes (ML) along with the general use lanes (GUL) on the I-4 corridor, the currently implemented variable speed limits (VSL) scenario as well as a hypothetical restricted truck lane (RTL) scenario. Results of the mitigation scenarios showed an overall speed improvement on the corridor which resulted in overall reduction in emissions and emission rates when compared to the existing condition (EX) scenario and specifically on link by link basis for the RTL scenario.The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways.
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Date Issued: 2012
Identifier: CFE0004777, ucf:49788
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004777

Highway Safety Manual (2)	+ -
ANOVA (1)	+ -
Active Traffic Management (1)	+ -
Advanced Traveler Information Systems (1)	+ -
Air Quality Impacts (1)	+ -

Bayesian Inference (1)	+ -
Bayesian inference (1)	+ -
Before and After Study with a Comparison group (1)	+ -
Blank out Signs (1)	+ -
CO2 (1)	+ -
Calibration (1)	+ -
Calibration Factor (1)	+ -
Carbon Dioxide (1)	+ -
Construction (1)	+ -
Custom Design (1)	+ -
D-Optimal (1)	+ -
Data Mining (1)	+ -
Data Mining Methods (1)	+ -
Demand forecast (1)	+ -
Electimize (1)	+ -
Empirical Bayes Method (1)	+ -
Environmental Impacts (1)	+ -
Evolutionary Algorithms (1)	+ -
Expressway (1)	+ -
Expressway Safety (1)	+ -
FDSA (1)	+ -
Freeway (1)	+ -
Fuel Taxes (1)	+ -
Full Bayesian Hierarchical (1)	+ -
GA (1)	+ -

University of Central Florida (14)	+ -
Abdel-Aty, Mohamed (12)	+ -
Radwan, Ahmed (9)	+ -
Ahmed, Mohamed (4)	+ -
Al-Deek, Haitham (4)	+ -

Uddin, Nizam (4)	+ -
Eluru, Naveen (3)	+ -
Lee, JaeYoung (3)	+ -
Abou-Senna, Hatem (2)	+ -
Farid, Ahmed Tarek Ahmed (2)	+ -
Laman, Haluk (2)	+ -
Abdel-Raheem, Mohamed (1)	+ -
Abuzwidah, Muamer (1)	+ -
Alfawzan, Mohammed (1)	+ -
Choi, Keechoo (1)	+ -
Cooper, Charles (1)	+ -
Defrancisco, Joseph (1)	+ -
Graham, Don (1)	+ -
Harb, Rami (1)	+ -
Johnson, Mark (1)	+ -
Khalafallah, Ahmed (1)	+ -
Kuo, Pei-Fen (1)	+ -
Mackie, Kevin (1)	+ -
Madani Larijani, Kaveh (1)	+ -
Moradi, Massoud (1)	+ -
Nam, Boo Hyun (1)	+ -
Pande, Anurag (1)	+ -
Tatari, Mehmet (1)	+ -
Tatari, Omer (1)	+ -
Wang, Xuesong (1)	+ -

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