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- Title
- Exploring the Innovation Environment within the Systems Engineering Context of a Defense Organization: A Preliminary Framework.
- Creator
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Odeh, Khaled, Rabelo, Luis, Elshennawy, Ahmad, Lee, Gene, Karwowski, Waldemar, Uddin, Nizam, University of Central Florida
- Abstract / Description
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Innovation may involve the introduction of ideas for designing or producing new products, or introducing improvements to products, processes, services or any other aspect of an organization to the market place. A major element for measuring organizational strength is its perception of innovation and the ability of the organization to build on and sustain such strength. While there is no shortage of research and study materials on innovation, there is, however, a shortage of thorough and...
Show moreInnovation may involve the introduction of ideas for designing or producing new products, or introducing improvements to products, processes, services or any other aspect of an organization to the market place. A major element for measuring organizational strength is its perception of innovation and the ability of the organization to build on and sustain such strength. While there is no shortage of research and study materials on innovation, there is, however, a shortage of thorough and realistic analysis of the intersection of innovation management, and measurement of innovation within the systems engineering context of defense organizations. In addition, while most research studies seem to adopt strictly quantitative innovation factors in determining innovation success and performance, they seem to have overlooked the qualitative side of it. An objective of this research study is to address the need for exploring the innovation environment within the systems engineering context of a defense organization. In addition, the research presents a new model for exploring innovation factors within the examined environment, using both quantitative and qualitative factors. The research uses a number of data collection instruments that include a survey construct to gather quantitative and qualitative data. The study identified significant factors that could be used to properly determine innovation within the systems engineering context of defense organizations using traditional statistics and data mining modeling. New indicators such as security and organizational leadership are discovered as important to define, monitor, and assess the innovation of the defense industry within the context of systems engineering.
Show less - Date Issued
- 2013
- Identifier
- CFE0004903, ucf:49643
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004903
- 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
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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.
Show less - Date Issued
- 2013
- Identifier
- CFE0005000, ucf:50019
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005000
- Title
- A New Multidimensional Psycho-Physical Framework for Modeling Car-Following in a Freeway Work Zone.
- Creator
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Lochrane, Taylor, Al-Deek, Haitham, Radwan, Essam, Oloufa, Amr, Harb, Rami, Uddin, Nizam, University of Central Florida
- Abstract / Description
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As the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation...
Show moreAs the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation hypothesizes that drivers change their driving behavior as they drive through a freeway work zone compared to normal freeway conditions which has the potential to impact traffic operations and capacity of work zones. Psycho-physical car-following models are widely used in practice for simulating car-following. However, current simulation models may not fully capture car-following driver behavior specific to freeway work zones. This dissertation presents a new multidimensional psycho-physical framework for modeling car-following based on statistical evaluation of work zone and non-work zone driver behavior. This new framework is close in character to the Wiedemann model used in popular traffic simulation software such as VISSIM. This dissertation used two methodologies for collecting data: (1) a questionnaire to collect demographics and work zone behavior data and (2) a real-time vehicle data from a field experiment involving human participants. It is hypothesized that the parameters needed to calibrate the multidimensional framework for work zone driver behavior can be derived statistically by using data collected from runs of an Instrumented Research Vehicle (IRV) in a Living Laboratory (LL) along a roadway. The design of this LL included the development of an Instrumented Research Vehicle (IRV) to capture the natural car-following response of a driver when entering and passing through a freeway work zone. The development of a Connected Mobile Traffic Sensing (CMTS) system, which included state-of-the-art ITS technologies, supports the LL environment by providing the connectivity, interoperability and data processing of the natural, real-life setting. The IRV and CMTS system are tools designed to support the concept of a LL which facilitates the experimental environment to capture and calibrate natural driver behavior. The objective is to have these participants drive the instrumented vehicle and collect the relative distance and the relative velocity between the instrumented vehicle and the vehicle in the front of the instrumented vehicle. A Phase I pilot test was conducted with 10 participants to evaluate the experiment and make any adjustments prior to the full Phase II driver test. The Phase II driver test recruited a group of 64 participants to drive the IRV through an LL set up along a work zone on I-95 near Washington D.C. in order to validate this hypothesis In this dissertation, a new framework was applied and it demonstrated that there are four different categories of car-following behavior models each with different parameter distributions. The four categories are divided by traffic condition (congested vs. uncongested) and by roadway condition (work zone vs. non-work zone). The calibrated threshold values are presented for each of these four categories. By applying this new multidimensional framework, modeling of car-following behavior can enhance vehicle behavior in microsimulation modeling.This dissertation also explored driver behavior through combining vehicle data and survey techniques to augment the model calibrations to improve the understanding of car-following behavior in freeway work zones. The results identify a set of survey questions that can potentially guide the selection of parameters for car-fallowing models. The findings presented in this dissertation can be used to improve the performance of driver behavior models specific to work zones. This in return will more acutely forecast the impact a work zone design has on capacity during congestion.
Show less - Date Issued
- 2014
- Identifier
- CFE0005521, ucf:50326
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005521
- Title
- Applications of Transit Signal Priority Technology for Transit Service.
- Creator
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Consoli, Frank, Al-Deek, Haitham, Oloufa, Amr, Tatari, Omer, Uddin, Nizam, University of Central Florida
- Abstract / Description
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This research demonstrated the effectiveness of Transit Signal Priority (TSP) in improving bus corridor travel time in a simulated environment using real world data. TSP is a technology that provides preferential treatment to buses at signalized intersections. By considering different scenarios of activating bus signal priority when a bus is 3 or 5 minutes behind schedule, it was demonstrated that bus travel times improved significantly while there is little effect on delays for crossing...
Show moreThis research demonstrated the effectiveness of Transit Signal Priority (TSP) in improving bus corridor travel time in a simulated environment using real world data. TSP is a technology that provides preferential treatment to buses at signalized intersections. By considering different scenarios of activating bus signal priority when a bus is 3 or 5 minutes behind schedule, it was demonstrated that bus travel times improved significantly while there is little effect on delays for crossing street traffic. The case of providing signal priority for buses unconditionally resulted in significant crossing street delays for some signalized intersections with only minor improvement to bus travel time over both scenarios of Conditional priority.Evaluation was conducted by using micro-simulation and statistical analysis to compare Unconditional and Conditional TSP with the No TSP scenario. This evaluation looked at performance metrics (for buses and all vehicles) including average speed profiles, average travel times, average number of stops, and crossing street delay. Different Conditional TSP scenarios of activating TSP when a bus is 3 or 5 minutes behind schedule were considered. The simulation demonstrated that Conditional TSP significantly improved bus travel times with little effect on crossing street delays. The results also showed that utilizing TSP technology reduced the environmental emissions in the I-Drive corridor. Furthermore, field data was used to calculate actual passenger travel time savings and benefit cost ratio (7.92) that resulted from implementing conditional TSP. Conditional TSP 3 minutes behind schedule was determined to be the most beneficial and practical TSP scenario for real world implementation at both the corridor and regional levels.
Show less - Date Issued
- 2014
- Identifier
- CFE0005474, ucf:50343
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005474
- Title
- Multi-Level Safety Performance Functions for High Speed Facilities.
- Creator
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Ahmed, Mohamed, Abdel-Aty, Mohamed, Radwan, Ahmed, Al-Deek, Haitham, Mackie, Kevin, Pande, Anurag, Uddin, Nizam, University of Central Florida
- Abstract / Description
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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.
Show less - Date Issued
- 2012
- Identifier
- CFE0004508, ucf:49274
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004508
- Title
- Livelihoods support programs, conservation attitudes, and tropical biodiversity: an evaluation of biocomplexity in southeastern Ghana.
- Creator
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Ekpe, Edem, Hinkle, Charles, Quigley, Martin, VonHolle, Mary, Weishampel, John, Uddin, Nizam, Owusu, Erasmus, Milon, Joseph, University of Central Florida
- Abstract / Description
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Human activities are a major driver of biodiversity degradation and loss, especially in tropical forest areas, where forest-fringe towns and villages depend on the forests for their livelihoods. In order to reduce threats that human activities pose to biodiversity, livelihoods support programs are employed as economic incentives for biodiversity conservation. These programs support the livelihoods activities of local communities, with the aim of triggering favorable attitudes and behaviors...
Show moreHuman activities are a major driver of biodiversity degradation and loss, especially in tropical forest areas, where forest-fringe towns and villages depend on the forests for their livelihoods. In order to reduce threats that human activities pose to biodiversity, livelihoods support programs are employed as economic incentives for biodiversity conservation. These programs support the livelihoods activities of local communities, with the aim of triggering favorable attitudes and behaviors towards conservation, and ultimately reduce biodiversity degradation. Their effectiveness as conservation tools has not been evaluated. I investigated the effects of livelihoods programs on conservation attitudes and the consequent effects on biodiversity in the Afadjato-Agumatsa and Atewa forest areas in southeastern Ghana.The study areas are coupled human and natural systems, which are excellent for research in the theoretical framework of biocomplexity in the environment. Using literature reviews and field visits, I documented the specific livelihoods support activities (LSAs) used for biodiversity conservation, their historical trend and geographical distribution in Ghana. I used ex-post cost-benefit analysis to determine socio-economic estimates of the LSAs in the two forest areas. Since communities were not randomly assigned to the interventions, I employed quasi-experimental design to evaluate the effects of LSAs on environmental attitudes. I evaluated the effect of conservation attitudes on biodiversity at two levels. These levels included 1) functional biodiversity at the landscape level represented by mean Normalized Difference Vegetation Index (NDVI) of forest; and 2) compositional biodiversity at the species level represented by species diversity of fruit bats. The earliest record of LSAs used for biodiversity conservation in Ghana was in 1993. I identified 71 different activities belonging to eight categories. Some of these activities are beekeeping, animal husbandry, crop farming, and snail rearing. Most LSA programs have been in northern Ghana. There was an increasing tendency to make LSAs part of every conservation program in Ghana and this satisfies the current policy of collaborative conservation.The socio-economic estimates of LSAs included: 1) capital investment; 2) net socio-economic benefits; and 3) the benefit-cost ratio. The per-community values of the three estimates were not different between the two study areas. The per capita values of capital investment and net economic benefit were not significantly different between the two study areas. However, benefit-cost ratio per capita was higher in Afadjato-Agumatsa than in Atewa. Estimates of economic returns from LSAs were marginal but the perceptions of success were relatively high.Environmental attitudes in LSA communities and non-LSA communities were not significantly different, and this was confirmed by an estimate of infinitesimal effects of LSAs on forest conservation attitudes. Among LSA communities, benefit-cost ratio of LSAs predicted favorable forest conservation attitudes; and change in pro-conservation attitudes were significantly higher in communities that had active LSAs than in communities which had no active LSA.Mean NDVI of the forests decreased from 1991 to 2000 and decreased further but at a slower rate to 2010. Higher forest conservation attitudes predicted higher mean NDVI in 2010. Higher change in mean NDVI from 1991 to 2000 predicted higher change in mean NDVI from 2000 to 2010. Eleven of the 13 fruit bat species in Ghana were recorded in the study areas. Longer distances between a local community and its forest predicted higher species diversity of forest-specialist fruit bats.The results indicate that LSAs have become a major contribution to Ghana's current collaborative forest policy. The fact that perceptions of LSA success were moderate even though the economic returns from them were marginal suggest that other factors such as provision of employment, training in new skills and community cohesion played a part in how communities viewed the success as LSAs. Evaluations of conservation attitudes suggest that just participating in LSAs did not improve attitudes; but higher benefit-cost ratio predicted favorable conservation attitudes, and conservation attitudes were higher in communities that sustained their LSAs. Therefore, it may serve biodiversity conservation to invest in LSAs that can be sustained and involve the least costs to local communities. Primary production of the forests, a proxy for a functional habitat, continued to decrease. Preventing communities from locating closer to forests could improve fruit bat diversity, which contributes to natural forest regeneration. Improving conservation attitudes should be an objective of conservation at the landscape scale.On the basis of the results, I developed a conceptual model for forest biodiversity conservation in a biocomplexity framework. This model could be useful for evaluating conservation in tropical forest areas. Lessons from this study can be applied in other incentive-based conservation programs such as payments for ecosystem services systems and carbon market schemes. I suggest that this study be repeated after a decade and that other socio-political and biogeochemical variables be integrated into future studies.
Show less - Date Issued
- 2012
- Identifier
- CFE0004246, ucf:49511
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004246
- Title
- Microscopic Safety Evaluation and Prediction for Special Expressway Facilities.
- Creator
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Wang, Ling, Abdel-Aty, Mohamed, Radwan, Essam, Eluru, Naveen, Lee, JaeYoung, Uddin, Nizam, University of Central Florida
- Abstract / Description
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Expressways are of great importance and serve as the backbone of a roadway system. One of the reasons why expressways increase travel speeds and provide high level of services is that limited access is provided to permit vehicles to enter or exit expressways. Entering and exiting of vehicles are accomplished through interchanges, which consist of several ramps, thus the spacing between ramps is important. A weaving segment might form when an on-ramp is closely followed by an off-ramp. The...
Show moreExpressways are of great importance and serve as the backbone of a roadway system. One of the reasons why expressways increase travel speeds and provide high level of services is that limited access is provided to permit vehicles to enter or exit expressways. Entering and exiting of vehicles are accomplished through interchanges, which consist of several ramps, thus the spacing between ramps is important. A weaving segment might form when an on-ramp is closely followed by an off-ramp. The geometric design of ramps and the traffic behavior of weaving segments are different from other expressway segments. These differences result in distinct safety mechanisms of these two expressway special facilities. Hence, the safety of these two facilities needs to be addressed.The majority of previous traffic safety studies on expressway special facilities are based on highly aggregated traffic data, e.g., Annual Average Daily Traffic (AADT). This highly aggregated traffic data cannot represent traffic conditions at the time of crashes and also cannot be used in the study of weather and temporal impact on crash occurrence. One way to solve this problem is microscopic safety evaluation and prediction through hourly crash prediction and real-time safety analysis. An hourly crash study averages one or several hours' traffic data in a year and also aggregates crash frequencies in the corresponding hour(s). Then it applies predictive models to determine the statistical relationship between crashes and hourly traffic flow characteristics, such as traffic volume. Real-time safety analysis enables us to predict crash risk and distinguish crashes from non-crashes in the next few minutes using the current traffic, weather, and other conditions.There are four types of crash contributing factors: traffic, geometry, weather, and driver. Among these, traffic parameters have been utilized in all previous microscopic safety studies. On the other hand, the other three factors' impact on microscopic safety has not been widely analyzed. The geometric factors' influence on safety are generally excluded by previous researchers using the matched-case-control method, because the majority of previous microscopic safety studies are on mainlines, where the geometric design of a segment does not change much and geometry does not have a significant effect on safety. Not enough studies have adopted weather factors in microscopic safety analysis because of the limited availability of weather data. The impact of drivers on safety has also not been widely considered since driver information is hard to be obtained. This study explores the relationship between crashes and the four contributing factors. Weather data are obtained from airport weather stations and crash reports which record weather and roadway surface conditions for crashes. Meanwhile, land-use and trip generation parameters serve as surrogates for drivers' behavior.Several methods are used to explore and quantify the impact of these factors. Random forests are used in discovering important and significant explanatory variables, which play significant roles in determining traffic safety, by ranking their importance. Meanwhile, in order to prevent high correlation between independent variables, Pearson correlation tests are carried out before model estimations. Only the variables which are not highly correlated are selected. Then, the selected variables are put in logistic regression models and Poisson-lognormal models to respectively estimate crash risk and crash frequency for special expressway facilities. Meanwhile, in case of correlation among observations in the same segment, a multilevel modeling structure has been implemented. Furthermore, a data mining technique(-)Support Vector Machine (SVM)(-)is used to distinguish crash from non-crash observations. Once the crash mechanisms for special expressway facilities are found, we are able to provide valuable information on how to manage roadway facilities to improve the traffic safety of special facilities. This study adopts Active Traffic Management (ATM) strategies, including Ramp Metering (RM) and Variable Speed Limit (VSL), in order to enhance the safety of a congested weaving segment. RM regulates the entering vehicle volume by adjusts metering rate, and VSL is able to provide smoother mainline traffic by changing the mainline speed limits. The ATM strategies are carried out in microscopic simulation VISSIM through the Component Object Model (COM) interface. The results shows that the crash risk and conflict count of the studies weaving segment have been significantly reduced because of ATM.Furthermore, the mechanisms of traffic conflicts, a surrogate safety measurement, are explored for weaving segments using microscopic simulation. The weaving segment conflict prediction model is compared with its crash prediction model. The results show that there are similarity and differences between conflict and crash mechanisms. Finally, potential relevant applications beyond the scope of this research but worth investigation in the future are also discussed in this dissertation.
Show less - Date Issued
- 2016
- Identifier
- CFE0006414, ucf:51480
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006414
