Masters Theses
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Browsing Masters Theses by Author "Abbas, Montasir M."
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- Analysis of Potential Wake Turbulence Encounters in Current and NextGen Flight OperationsSchroeder, Nataliya (Virginia Tech, 2011-01-31)Wake vortices pose a threat to a following aircraft, because they can induce a roll and compromise the safety of everyone on board. Caused by a difference in pressure between the upper and the lower part of the wings, these invisible flows of air are a major hazard and have to be avoided by separating the aircraft at considerable distances. One of the known constraints in airport capacity for both departure and arrival operations is the large headway resulting from the wake spacing separation criteria. Reducing wake vortex separations to a safe level between successive aircraft can increase capacity in the National Airspace System (NAS) with corresponding savings in delay times. One of the main goals of the Wake Encounter Model (WEM) described in this thesis is to assess the outcome from future reduced separation criteria in the NAS. The model has been used to test probable encounters in today's operations, and can also be used to test NextGen scenarios, such as Close Parallel Approaches and reduced in-trail separation flights. This thesis presents model enhancements to account for aircraft turning maneuvers, giving the wake a more realistic shape. Three major airspaces, New York, Southern California and Atlanta, were analyzed using the original and the enhanced WEM to determine if the enhanced model better represents the conditions in today's operations. Additionally, some analysis on the wake lateral travel for closely spaced runways is presented in this thesis. Finally, some extension tools for post -analysis, such as animation tool and various graphs depicting the interactions between wake pairs were developed.
- Application of Naturalistic Truck Driving Data to Analyze and Improve Car Following ModelsHiggs, Bryan James (Virginia Tech, 2011-12-02)This research effort aims to compare car-following models when the models are calibrated to individual drivers with the naturalistic data. The models used are the GHR, Gipps, Intelligent Driver, Velocity Difference, Wiedemann, and the Fritzsche model. This research effort also analyzes the Wiedemann car-following model using car-following periods that occur at different speeds. The Wiedemann car-following model uses thresholds to define the different regimes in car following. Some of these thresholds use a speed parameter, but others rely solely upon the difference in speed between the subject vehicle and the lead vehicle. This research effort also reconstructs the Wiedemann car-following model for truck driver behavior using the Naturalistic Truck Driving Study's (NTDS) conducted by Virginia Tech Transportation Institute. This Naturalistic data was collected by equipping 9 trucks with various sensors and a data acquisition system. This research effort also combines the Wiedemann car-following model with the GHR car-following model for trucks using The Naturalistic Truck Driving Study's (NTDS) data.
- Aviation Global Demand Forecast Model Development: Air Transportation Demand Distribution and Aircraft Fleet EvolutionFreire Burgos, Edwin R. (Virginia Tech, 2017-09-08)The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. This research project intends to enhance the GDM capabilities. A Fratar model is implemented for the distribution of the forecast demand during each year. The Fratar model uses a 3,974 by 3,974 origin-destination matrix to distribute the demand among 55,612 unique routes in the network. Moreover, the GDM is capable to estimate the aircraft fleet mix per route and the number of flights per aircraft that are needed to satisfy the forecast demand. The model adopts the aircraft fleet mix from the Official Airline Guide data for the year 2015. Once the aircraft types are distributed and flights are assigned, the GDM runs an aircraft retirement and replacement analysis to remove older generation aircraft from the network and replace them with existing or newer aircraft. The GDM continues to evolve worldwide aircraft fleet by introducing 14 new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA.
- Bluetooth based dynamic critical route volume estimation on signalized arterialsGharat, Asmita (Virginia Tech, 2011-09-09)Bluetooth Data collection technique is recently proven as a reliable data collection technique that provides the opportunity to modify traditional methodologies to improve system performance. Actual volume in the network is a result of the timing plans which are designed and modified based on the volume which is generated using existing timing plans in the system. This interdependency between timing plan and volume on the network is a dynamic process and should be captured to obtain actual traffic states in the network. The current practice is to calculate synthetic origin destination information based on detector volume that doesn't necessarily represent the volume scenario accurately. The data from Bluetooth technology can be utilized to calculate dynamic volume on the network which can be further used as input for signal timing design. Application of dynamic volume improves the system performance by providing the actual volume in system to design optimal timing plans. This thesis proposes a framework that can be used to integrate data obtained from the Bluetooth technology with the traditional methods to design timing plans. The proposed methodology utilizes the origin destination information obtained from Bluetooth data, detector data, characteristics of intersections such as number of lanes, saturation flow rate and existing timing plans as a basis for the calculation of the dynamic volume for the various movements at each intersection. The study shows that using the Bluetooth based OD matrix to calculate accurate dynamic volumes results in better system performance compared to the traditional way of using the static detector volume alone.
- Calibration and Comparison of the VISSIM and INTEGRATION Microscopic Traffic Simulation ModelsGao, Yu (Virginia Tech, 2008-09-05)Microscopic traffic simulation software have gained significant popularity and are widely used both in industry and research mainly because of the ability of these tools to reflect the dynamic nature of the transportation system in a stochastic fashion. To better utilize these software, it is necessary to understand the underlying logic and differences between them. A Car-following model is the core of every microscopic traffic simulation software. In the context of this research, the thesis develops procedures for calibrating the steady-state car-following models in a number of well known microscopic traffic simulation software including: CORSIM, AIMSUN, VISSIM, PARAMICS and INTEGRATION and then compares the VISSIM and INTEGRATION software for the modeling of traffic signalized approaches. The thesis presents two papers. The first paper develops procedures for calibrating the steady-state component of various car-following models using macroscopic loop detector data. The calibration procedures are developed for a number of commercially available microscopic traffic simulation software, including: CORSIM, AIMSUN2, VISSIM, Paramics, and INTEGRATION. The procedures are then applied to a sample dataset for illustration purposes. The paper then compares the various steady-state car-following formulations and concludes that the Gipps and Van Aerde steady-state car-following models provide the highest level of flexibility in capturing different driver and roadway characteristics. However, the Van Aerde model, unlike the Gipps model, is a single-regime model and thus is easier to calibrate given that it does not require the segmentation of data into two regimes. The paper finally proposes that the car-following parameters within traffic simulation software be link-specific as opposed to the current practice of coding network-wide parameters. The use of link-specific parameters will offer the opportunity to capture unique roadway characteristics and reflect roadway capacity differences across different roadways. Second, the study compares the logic used in both the VISSIM and INTEGRATION software, applies the software to some simple networks to highlight some of the differences/similarities in modeling traffic, and compares the various measures of effectiveness derived from the models. The study demonstrates that both the VISSIM and INTEGRATION software incorporate a psycho-physical car-following model which accounts for vehicle acceleration constraints. The INTEGRATION software, however uses a physical vehicle dynamics model while the VISSIM software requires the user to input a vehicle-specific speed-acceleration kinematics model. The use of a vehicle dynamics model has the advantage of allowing the model to account for the impact of roadway grades, pavement surface type, pavement surface condition, and type of vehicle tires on vehicle acceleration behavior. Both models capture a driver's willingness to run a yellow light if conditions warrant it. The VISSIM software incorporates a statistical stop/go probability model while current development of the INTEGRATION software includes a behavioral model as opposed to a statistical model for modeling driver stop/go decisions. Both software capture the loss in capacity associated with queue discharge using acceleration constraints. The losses produced by the INTEGRATION model are more consistent with field data (7% reduction in capacity). Both software demonstrate that the capacity loss is recovered as vehicles move downstream of the capacity bottleneck. With regards to fuel consumption and emission estimation the INTEGRATION software, unlike the VISSIM software, incorporates a microscopic model that captures transient vehicle effects on fuel consumption and emission rates.
- A Computer Model to Estimate Benefits of Data Link Mandates and Reduced Separations across North Atlantic Organized Track SystemGunnam, Aswin Kumar (Virginia Tech, 2013-01-04)The International Civil Aviation Organization (ICAO) proposed to introduce new operational strategies across the North Atlantic (NAT) airspace. This includes Minimum Navigation Performance Specifications (MNPS) airspace to increase the capacity and efficiency of the North Atlantic Organized Track System (NAT OTS). A numerical integration and simulation model called North Atlantic Simulation and Modeling (NATSAM) is developed to study the effects of these new strategies on NAT system performance. The model is capable of investigating the effects of implementing different operational policies and strategies proposed by ICAO such as Reduced Lateral Separation Minimum (RLatSM), NAT Region Data link mandate (DLM), Reduced Longitudinal Separation Minimum (RLongSM), cruise-climb profiles, variable Mach number profiles, step-climbs and other operational concepts to be studied by the ICAO. NATSAM models the individual flight performance using the Base of Aircraft Data (BADA) 3.9 model to calculate the flight profiles and fuel burn. The model employs simple heuristics to execute flight track assignment in the organized track system for each scenario. Detailed outputs and also aggregated outputs are provided by the model from which various key performance indicators (KPI) can be derived to assess the performance of the system.
- A Computer Model to Estimate Commercial Aviation Fuel Consumption and Emissions in the Continental United StatesZou, Zhihao (Virginia Tech, 2013-01-03)A comprehensive model is developed to estimate and predict the fuel consumption and emissions by domestic commercial aviation in the Continental United States. Most of the existing fuel consumption and emission models are limited in their ability to predict the annual fuel burn for air transportation at the national level. For example, those models either require real track data or are developed only to model single flight scenarios. The model developed in this thesis is part of a software framework called the Transportation Systems Analysis Model (TSAM). The model has the capability to estimate fuel consumption and emissions for millions of domestic flights in a year in the continental U.S. TSAM is a nationwide, long-distance, multimodal travel demand forecast model developed at Virginia Tech. The model enables TSAM to quantify fuel and emission metrics for various modes of transportation. The EUROCONTROL Base of Aircraft Data (BADA) is employed as the Aircraft Performance Model to simulate individual flight profiles and calculate fuel burn rates. Fuel consumption on the ground (taxi mode) is estimated separately. Different operational conditions like wind states, terminal area detour, cruise altitude and airport elevation are considered in the model. Emissions of HC, CO, NOx and SOx are computed inside the Landing/Take-off (LTO) cycle based on the fuel consumption estimate, while greenhouse gas of CO2 is calculated for the complete flight cycle.
- Development of a High-Speed Rail Model to Study Current and Future High-Speed Rail Corridors in the United StatesVandyke, Alex J. (Virginia Tech, 2011-05-31)A model that can be used to analyze both current and future high-speed rail corridors is presented in this work. This model has been integrated into the Transportation Systems Analysis Model (TSAM). The TSAM is a model used to predict travel demand between any two locations in the United States, at the county level. The purpose of this work is to develop tools that will create the necessary input data for TSAM, and to update the model to incorporate passenger rail as a viable mode of transportation. This work develops a train dynamics model that can be used to calculate the travel time and energy consumption of multiple high-speed train types while traveling between stations. The work also explores multiple options to determine the best method of improving the calibration and implementation of the model in TSAM. For the mode choice model, a standard C logit model is used to calibrate the mode choice model. The utility equation for the logit model uses the decision variables of travel time and travel cost for each mode. A modified utility equation is explored; the travel time is broken into an in-vehicle and out-of-vehicle time in an attempt to improve the model, however the test determines that there is no benefit to the modification. In addition to the C-logit model, a Box-Cox transformation is applied to both variables in the utility equation. This transformation removes some of the linear assumptions of the logit model and thus improves the performance of the model. The calibration results are implemented in TSAM, where both existing and projected high-speed train corridors are modeled. The projected corridors use the planned alignment for modeling. The TSAM model is executed for the cases of existing train network and projected corridors. The model results show the sensitivity of travel demand by modeling the future corridors with varying travel speeds and travel costs. The TSAM model shows the mode shift that occurs because of the introduction of high-speed rail.
- Development of Optimal Migration Plan for New Traffic Signal Controllers Using Gis and Multi-Criteria Decision MakingGanta, Surender (Virginia Tech, 2010-07-01)Signal Replacement decisions are often made based on the experience of the Traffic Engineers. These decisions are made while considering the deployment time of the system, the new technology available, and the performance of the system in the given location. However, there is no set of proper guidelines or methods which can quantify the system replacement decision in large scale projects. This thesis presents a methodology that can be applied to determine optimal migration plans for traffic signal controllers. A Multi-Criteria Decision Making technique has been adopted to evaluate various traffic signal controllers. Various controller manuals were studied and information was obtained from the vendors of the controllers. In addition to that, Geographic Information System (GIS) has been used as a tool to evaluate and identify the areas where the traffic signal controllers have to be replaced first. The study considers the budget constraints and the benefits that can be obtained by the replacement of the controllers. This thesis presents the Methodology adopted for the Migration Plan and a case study implementation on the Northern Virginia Region. Finally it presents the conclusions drawn from the research with insights into the scope for further research.
- Discrete Element Method (DEM) Contact Models Applied to Pavement SimulationPeng, Bo (Virginia Tech, 2014-08-20)Pavement is usually composed of aggregate, asphalt binder, and air voids; rigid pavement is built with hydraulic cement concrete; reinforced pavement contains steel. With these wide ranges of materials, different mechanical behaviors need to be defined in the pavement simulation. But so far, there is no research providing a comprehensive introduction and comparison between various contact models. This paper will give a detail exploration on the contact models that can be potentially used in DEM pavement simulation; in the analysis, it includes both a theoretical part, simulation results and computational time cost, which can reveal the fundamental mechanical behaviors for the models, and that can be a reference for researchers to choose a proper contact model. A new contact model—the power law viscoelastic contact model is implemented into software PFC 3D and is numerically verified. Unlike existing linear viscoelastic contact models, the approach presented in this thesis provides a detailed exploration of the contact model for thin film power-law creeping materials based on C.Y Chueng's work. This model is aimed at simulating the thin film asphalt layer between two aggregates, which is a common structure in asphalt mixtures. Experiments with specimens containing a thin film asphalt between two aggregates are employed to validate the new contact model.
- Driver Safety and Emissions at Different PPLT IndicationsDuvvuri, Sri Rama Bhaskara Kumari (Virginia Tech, 2017-03-03)According to NCHRP Report 493, there are five major left turn signal indications for permitted operations in the United States. They are: Circular Green (CG), Flashing Circular Red (FCR), Flashing Red Arrow (FRA), Flashing Circular Yellow (FCY) and Flashing Yellow Arrow (FYA). The main goal of this thesis is to study the driver behavior and analyze safety of drivers for different left turn indications using a real-time driving simulator. Different signal indications alter driver behavior which influences velocity and acceleration profiles. These profiles influence vehicular emissions and hence need to be studied as well. For this purpose, different scenarios are implemented in the driving simulator. Data is analyzed using Microsoft Excel, JMP Statistical tool and MATLAB. Safety of drivers is analyzed with respect to the parameter "Time to Collision (TTC)" which is directly obtained from simulator data. Vehicular emissions and fuel consumption are calculated using VT-Micro microscopic emissions model. Graphs are plotted for TTC and total emissions. Results indicate that for a day-time scenario, FCY and FYA are the most suitable left-turning indications whereas FCR and FRA are most suitable for a night-time scenario.
- Dynamic OD Estimation with Bluetooth Data Using Kalman FilterMurari, Sudeeksha (Virginia Tech, 2012-08-10)Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) utilize real-time information to apply measures improve the transportation system performance. Two key inputs for ATMS and ATIS are dynamic travel times and dynamic OD matrices. Bluetooth devices detection technology has been increasingly used to track vehicle movements on the network. This possibility naturally raises the question of whether this information can be used to improve the dynamic estimation of OD matrices. Previous research efforts rely entirely on the Bluetooth OD counts for estimation, which is why they require high penetration rates. In our study, we use Bluetooth data to supplement loop detector data while estimating dynamic OD matrices using Kalman filter. We use OD proportions as state variables and travel times, link counts, Bluetooth OD matrix and input and exit volumes as measurements. A simulation experiment is conducted in VISSIM and is designed such that the traffic network emulates the observed traffic patterns. Two case studies are performed for comparison. One uses Bluetooth OD matrices as input for estimation while the other does not. The Bluetooth ODs used in the Kalman filter estimation was found to improve the OD flow estimates. The developed methods were compared with synthetic OD estimation software (QueensOD) and were found to be more effective in obtaining dynamic OD flow estimates. A case of study with fewer detectors was also studied. When it was compared with a similar method developed by Gharat(2011), the errors were lower.
- Effect of Pavement Condition on Traffic Crash Frequency and Severity in VirginiaMohagheghi, Ali (Virginia Tech, 2020-09-30)Previous studies show that pavement condition properties are significant factors to enhance road safety and riding experience, and pavements with low quality might have inadequate performance in terms of safety and riding experience. Pavement Management System (PMS) databases include pavement properties for each segment of the road collected by the agencies. Understanding the impact of road characteristics on crash frequency is a key step to prevent crashes. Whereas other studies analyzed the effect of different characteristics such as International Roughness Index (IRI), Rutting Depth (RD), Annual Average Daily Traffic (AADT), this thesis analyzed the effect of Critical Condition Index (CCI) on crash frequency, in addition to the other factors identified in previous studies. Other characteristics such as Percentage of Heavy Vehicles, Road Surface Condition, Road Lighting Condition, and Driver Conditions are taken into the consideration. The scope of the study is the interstate highway system in Fairfax County, Virginia. Negative Binomial, Least Square and Nominal Logistic Models were developed, showing that the CCI value is a significant factor to predict the number of crashes, and that it has different effect for different values of AADT. The result of this study is a substantial step towards developing an integrated transportation control and infrastructure management framework.
- Estimation of Runway Throughput with Reduced Wake Vortex Separation, Technical Buffer and Runway Occupancy Time ConsiderationsHu, Junqi (Virginia Tech, 2018-09-18)This thesis evaluates the potential recovery of the runway throughput under Wake Turbulence Re-categorization (RECAT) Phase II and Time-based Separation (TBS) with a Runway Occupancy Time (ROT) constraint comparing with RECAT Phase I. This research uses aircraft performance parameters (runway occupancy time, approach speed, etc.) from the Airport Surface Detection Equipment, Model X (ASDE-X) data set. The analysis uses a modified version of the Quick Response Runway Capacity Model (RUNSIM). The main contributions of the study are: 1) identifying the technical buffer between in-trail arrivals and regenerate them in RUNSIM; 2) estimate the percentage of the arrival pairs that have wake mitigation separation times in excess of ROT; 3) developed an additional in-trail arrival separation rule based on ROT; 4) measure the risk of potential go-arounds with and without the additional 95 ROT separation rules. 5) generate a sample equivalent time-based RECAT II. The study results show that the distributions of technical buffers have significant differences for different in-trail groups and strong connectivity to airport elevations. This is critical to estimate runway capacities and safety issues especially when advanced wake mitigation separation rules are applied. Also, with decreasing of wake separations, ROT will become a limiting factor in runway throughput in the future. This study shows that by considering a 95 percentile ROT constrain, one single runway can still obtain 4 or 5 more arrivals per hour under RECAT II but keep the same level of potential go-arounds compared with current operation rules (RECAT I). TBS rules seem to benefit more under strong wind conditions compared to RECAT I, and RECAT II. TBS rules need to be tailored to every airport.
- Evaluation and Development of a University Visitor Parking Management FrameworkGurram, Sashikanth (Virginia Tech, 2009-11-16)The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has a current parking inventory of approximately 14,310 parking spaces in 88 surface lots. Of the available parking spaces 92% are designated for the use of Virginia Tech students, faculty and staff members. The share of visitor usage of these parking spaces is approximately 2%. The objective of this thesis is to evaluate the current visitor parking system and develop techniques to enhance the parking facility operations. The current visitor parking demand is determined by conducting a field evaluation of the visitor parking in five parking lots. Personal and follow-up interviews were conducted with university visitors to determine their satisfaction levels with the existing parking facilities. While the survey results demonstrated that 52% of visitors rated the parking services to be good or very good, the study also showed that approximately 28% of the visitors did not know the location of the most convenient parking lot to access their destination and almost 6% were not satisfied with the parking services offered by Virginia Tech. Apart from this, about 32% of the visitors had to visit at least 2 parking lots before finding a parking space. These figures clearly demonstrate a need for a better management of the parking lots to serve the visitors in an efficient way. In an attempt to enhance the visitor parking system a web-based interactive framework is proposed. This framework identifies the best possible parking lot(s) for a selected destination considering various factors like - distance of the parking lot to the destination and typical occupancy of the parking lot at specific times of the day and other relevant factors. The web-based interactive system is designed to provide the visitor with two or more choices for the parking in order to arrive at their desired destination.
- Exploratory Study of Distracted Behaviors of Transit OperatorsArbie, Nurlayla (Virginia Tech, 2014-08-30)Bus transit driving is an occupation that requires high concentration in driving and is demanding due to work overload, time pressure, and responsibility for lives. In 2006, there were 103 fatal crashes involving transit buses. As the number of distraction-related crashes increases, it is important to conduct a transit distraction study to reduce future crashes. This thesis focused on the analysis of the likelihood of the operator distraction behaviors and the analysis to find a predictive model to classify different distraction categories. An ordinal logistic regression was carried out to evaluate how age, gender, driving experience of the operators, and their driving frequencies accounts for the likelihood of 17 potential distracted driving behaviors. The results of this analysis showed that there were only 5 best models (p-value of model fit less than 0.005 and p-value of parallel line test more than 0.005) that could be constructed, including: listening to the radio/ CD/DVD/MP3 player (D1); picking Up and Holding 2-way Radio (D5); listening to the Dispatch Office broadcast (D6); adjusting switches/controls on dashboard (D15); and utilizing mentor ranger (D16). On the other hand, a discriminant analysis was performed to predict how different transit operator driving behaviors when exposed by 10 different distraction activities and 16 predictors were considered in this analysis. The final results showed that there are 4 predictors that seem to be able to classify distraction groups across all 4 models; those include segment length, average duration of idling time/stop delay at speed interval 0—4 km/hr, frequency of speed transitions that deviate by ± 0 to 4 km/hr from its speed, and frequency of speed transitions that deviate by ± 8 to 12 km/hr from its speed.
- Forecasting Model for High-Speed Rail in the United StatesRamesh Chirania, Saloni (Virginia Tech, 2012-10-02)A tool to model both current rail and future high-speed rail (HSR) corridors has been presented in this work. The model is designed as an addition to the existing TSAM (Transportation System Analysis Model) capabilities of modeling commercial airline and automobile demand. TSAM is a nationwide county to county multimodal demand forecasting tool based on the classical four step process. A variation of the Box-Cox logit model is proposed to best capture the characteristic behavior of rail demand in US. The utility equation uses travel time and travel cost as the decision variables for each model. Additionally, a mode specific geographic constant is applied to the rail mode to model the North-East Corridor (NEC). NEC is of peculiar interest in modeling, as it accounts for most of the rail ridership. The coefficients are computed using Genetic Algorithms. A one county to one station assignment is employed for the station choice model. Modifications are made to the station choice model to replicate choices affected by the ease of access via driving and mass transit. The functions for time and cost inputs for the rail system were developed from the AMTRAK website. These changes and calibration coefficients are incorporated in TSAM. The TSAM model is executed for the present and future years and the predictions are discussed. Sensitivity analysis for cost and speed of the predicted HSR is shown. The model shows the market shift for different modes with the introduction of HSR. Limited data presents the most critical hindrance in improving the model further. The current validation process incorporates essential assumptions and approximations for transfer rates, short trip percentages, and access and egress distances. The challenges for the model posed by limited data are discussed in the model.
- Game-Aided Education for Transportation Engineering: Design, Development, and AssessmentWang, Qichao (Virginia Tech, 2017-05-04)Transportation engineering is a wide area that covers different topics including traffic planning, highway design, pavement design, traffic safety, and traffic control. Certain concepts in those topics are challenging and are hard to understand based on textbooks and lectures. In this work, we developed five web games targeting the five topics in transportation engineering education to improve students’ understanding of those hard concepts. The games are hosted in a website server. Students can play these games online after register and login. The server stores the users’ information and their gameplay data. We conducted a Before-and-After study to test the effectiveness of the games in terms of improving the learning outcomes of the students. The results showed that the games could increase the students’ understanding of hard concepts significantly. The developed games can be used in transportation education. This game framework can serve as a reference for other education game developers. We envision that more educational games will be developed by transportation and education communities in the recent future. There will be more than one game for the same topic. We need an approach to select games for different students group. We proposed a gravity model for evaluating the engagement of the students for the educational games. We found that different games have different properties in terms of attracting students’ engagement. The proposed model can be used in the future for selecting educational games for specific students group.
- Global Commercial Aircraft Fuel Burn and Emissions Forecast: 2016 to 2040Padalkar, Rahul Rajaram (Virginia Tech, 2017-10-13)This thesis discusses enhancements to the Global Demand Model (GDM). The model addresses the need to predict: a) number of flights Worldwide by Origin-Destination (OD) airport pair, b) the number of seats (surrogate of demand) by OD airport pair, c) the fleet evolution over time, d) fuel consumption by OD pair and aircraft type, and emissions by OD pair and aircraft type. The model has developed an airline fleet assignment module to predict changes to the airline fleet in the future. Specifically, the model has the capability to examine the fuel and emission benefits of next generation N+1 aircraft and advanced NASA's N+2 aircraft are adopted in the future.
- Global Demand Forecast ModelAlsalous, Osama (Virginia Tech, 2016-01-19)Air transportation demand forecasting is a core element in aviation planning and policy decision making. NASA Langley Research Center addressed the need of a global forecast model to be integrated into the Transportation Systems Analysis Model (TSAM) to fulfil the vision of the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters to develop a picture of future demand worldwide. Future forecasts can be performed using a range of techniques depending on the data available and the scope of the forecast. Causal models are widely used as a forecasting tool by looking for relationships between historical demand and variables such as economic and population growth. The Global Demand Model is an econometric regression model that predicts the number of air passenger seats worldwide using the Gross Domestic Product (GDP), population, and airlines market share as the explanatory variables. GDP and Population are converted to 2.5 arc minute individual cell resolution and calculated at the airport level in the geographic area 60 nautical miles around the airport. The global demand model consists of a family of models, each airport is assigned the model that best fits the historical data. The assignment of the model is conducted through an algorithm that uses the R2 as the measure of Goodness-of-Fit in addition to a sanity check for the generated forecasts. The output of the model is the projection of the number of seats offered at each airport for every year up to the year 2040.
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