VTechWorks Repository :: Browsing by Author "Baik, Hojong"

Browsing by Author "Baik, Hojong"

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Accounting for Risk and Level of Service in the Design of Passing Sight Distances
El Khoury, John (Virginia Tech, 2005-11-28)
Current design methods in transportation engineering do not simultaneously address the levels of risk and service associated with the design and use of various highway geometric elements. Passing sight distance (PSD) is an example of a geometric element designed with no risk measures. PSD is provided to ensure the safety of passing maneuvers on two-lane roads. Many variables decide the minimum length required for a safe passing maneuver. These are random variables and represent a wide range of human and vehicle characteristics. Also, current PSD design practices replace these random variables by single-value means in the calculation process, disregarding their inherent variations. The research focuses on three main objectives. The first goal is to derive a PSD distribution that accounts for the variations in the contributing parameters. Two models are devised for this purpose, a Monte-Carlo simulation model and a closed form analytical estimation model. The results of both models verify each other and differ by less than 5 percent. Using the PSD distribution, the reliability index of the current PSD criteria are assessed. The second goal is to attach risk indices to the various PSD lengths of the obtained distribution. A unique microscopic simulation is devised to replicate passing maneuvers on two-lane roads. Using the simulation results, the author is able to assess the risk of various PSD lengths for a specific design speed. The risk index of the AASHTO Green Book and the MUTCD PSD standards are also obtained using simulation. With risk measures attached to the PSD lengths, a trade-off analysis between the level of service and risk is feasible to accomplish. The last task is concerned with applying the Highway Capacity Manual concepts to assessing the service measures of the different PSD lengths. The results of the final trade-off analysis show that for a design speed of 50 mph, the AASHTO Green Book and the MUTCD standards overestimate the PSD requirements. The criteria can be reduced to 725 ft and still be within an acceptable risk level.
Alternative Methodology To Household Activity Matching In TRANSIMS
Paradkar, Rajan (Virginia Tech, 2001-06-15)
TRANSIMS (Transportation Analysis and Simulation System) developed at the Los Alamos National Laboratory, is an integrated system of travel forecasting models designed to give transportation planners accurate and complete information on traffic impacts, congestion, and pollution. TRANSIMS is a micro-simulation model which uses census data to generate a synthetic population and assigns activities using activity survey data to each person of every household of the synthetic population. The synthetic households generated from the census data are matched with the survey households based on their demographic characteristics. The activities of the survey household individuals are then assigned to the individuals of the matched synthetic households. The CART algorithm is used to match the households. With the use of CART algorithm a classification tree is built for the activity survey households based on some dependent and independent variables from the demographic data. The TRANSIMS model assumes activity times as dependent variables for building the classification tree. The topic of this research is to compare the TRANSIMS approach of using times spent in executing the activities as dependent variables, compared to match the alternative of using travel times for trips between activities as dependent variables i.e. to use the travel time pattern instead of activity time pattern to match the persons in the survey households with the synthetic households. Thus assuming that if the travel time patterns are the same then we can match the survey households to the synthetic population i.e. people with similar demographic characteristics tend to have similar travel time patterns. The algorithm of the Activity Generator module along with the original set of dependent variables, were first used to generate a base case scenario. Further tests were carried out using an alternative set of dependent variables in the algorithm. A sensitivity analysis was also carried out to test the affect of different sets of dependent variables in generating activities using the algorithm of the Activity Generator. The thesis also includes a detailed documentation of the results from all the tests.
A bi-level system dynamics modeling framework to evaluate costs and benefits of implementing Controller Pilot Data Link Communications and Decision Support Tools in a non-integrated and integrated scenario
Sen, Debayan (Virginia Tech, 2003-12-23)
A modeling framework to evaluate the costs and benefits of implementation of Controller Pilot Data Link Communication (CPDLC), and Air Traffic Management (ATM) decision support tools is proposed in this paper. The benefit/cost evaluation is carried out for four key alternatives namely alternative A: Do nothing scenario (only voice channel), alternative B: Voice channel supplemented with CPDLC, alternative C: Alternative B with ATM tools in a non-integrated scenario and finally alternative D: Alternative B with ATM tools in an integrated scenario. It is a bi-level model that captures the linkages between various technologies at a lower microscopic level using a daily microscopic model (DATSIM) and transfers the measures of effectives to a higher macroscopic level. DATSIM stands for Data Link and Air Traffic Technologies SIMulation and it simulates air traffic in the enroute sector and terminal airspace for a single day and captures the measures of effectiveness at a microscopic level and feeds its output to the macroscopic annual model which then runs over the entire life cycle of the system. Airspace dwell time benefit data from the microscopic model is regressed into three dimensional benefit surfaces as a function of the equipage level of aircraft and aircraft density and embedded into the macroscopic model. The main function of the annual model is to ascertain economic viability of any deployment schedule or alternative over the entire life cycle of the system. The life cycle cost model is composed of four modules namely: Operational benefits module, Safety benefit module,Technology cost module and Training cost module. Analysis using the model showed that an enroute sector gets congested at aircraft densities greater 630 per day. This is mainly because the controller workload gets saturated at that traffic volume per day. Benefits realized in alternatives B, C and D as compared to alternative A increased exponentially at traffic densities greater than 630 i.e. when controller workload for alternative A becomes saturated.
Collaborative En Route Airspace Management Considering Stochastic Demand, Capacity, and Weather Conditions
Henderson, Jeffrey Michael (Virginia Tech, 2008-03-26)
The busiest regions of airspace in the U.S. are congested during much of the day from traffic volume, weather, and other airspace restrictions. The projected growth in demand for airspace is expected to worsen this congestion while reducing system efficiency and safety. This dissertation focuses on providing methods to analyze en route airspace congestion during severe convective weather (i.e. thunderstorms) in an effort to provide more efficient aircraft routes in terms of: en route travel time, air traffic controller workload, aircraft collision potential, and equity between airlines and other airspace users. The en route airspace is generally that airspace that aircraft use between the top of climb and top of descent. Existing en route airspace flight planning models have several important limitations. These models do not appropriately consider the uncertainty in airspace demand associated with departure time prediction and en route travel time. Also, airspace capacity is typically assumed to be a static value with no adjustments for weather or other dynamic conditions that impact the air traffic controller. To overcome these limitations a stochastic demand, stochastic capacity, and an incremental assignment method are developed. The stochastic demand model combines the flight departure uncertainty and the en route travel time uncertainty to achieve better estimates for sector demand. This model is shown to reduce the predictive error for en route sector demand by 20\% at a 30 minute look-ahead time period. The stochastic capacity model analyzes airspace congestion at a more macroscopic level than available in existing models. This higher level of analysis has the potential to reduce computational time and increase the number of alternative routing schemes considered. The capacity model uses stochastic geometry techniques to develop predictions of the distribution of flight separation and conflict potential. A prediction of dynamic airspace capacity is calculated based on separation and conflict potential. The stochastic demand and capacity models are integrated into a graph theoretic framework to generate alternative routing schemes. Validation of the overall integrated model is performed using the fast time airspace simulator RAMS. The original flight plans, the routing obtained from an integer programming method, and the routing obtained from the incremental method developed in this dissertation are compared. Results of this validation simulation indicate that integer programming and incremental routing methods are both able to reduce the average en route travel time per flight by 6 minutes. Other benefits include a reduction in the number of conflict resolutions and weather avoidance maneuvers issued by en route air traffic controllers. The simulation results do not indicate a significant difference in quality between the incremental and integer programming methods of routing flights around severe weather.
Cost-Benefit Analysis Model for Advanced Weather Forecasting Installations in Airport Terminal Areas
Kane, Aniruddha V. (Virginia Tech, 2005-06-17)
Better utilization of the airport system capacities can significantly decrease delays, as well as number of cancelled flights. An efficient Air Traffic Control system equipped with advanced technology installations in the terminal area can help reduce flight delays and cancellations. The same technology could also help reduce accidents in the terminal area, thereby increasing the safety of the system. Due to the expense of fielding advanced technology in the terminal area, it is important to conduct realistic cost-benefit analysis to predict the life-cycle cost of the system. A computer simulation and optimization model to estimate the costs and benefits of fielding advanced technologies at airport terminal areas is introduced in this paper. The model developed is called the Cost-Benefit Analysis Terminal Investment Model (COTIM). This model considers costs and benefits to both service providers (Federal Aviation Administration and airport authorities) and users (Airlines). The model combines a simulation-optimization based approach to predict benefits and costs accrued in one day or throughout the life-cycle of the facility. We present an example to demonstrate the functionality of the model using Chicago O'Hare International Airport (ORD) equipped with the Integrated Terminal Weather System (ITWS). The Integrated Terminal Weather System (ITWS) is a relatively new technology that forecasts convective weather movements thus allowing Air Traffic Control (ATC) personnel to re-direct flights inside the terminal area efficiently. COTIM estimates flight delays and cancellations at an airport, when the airport is equipped with advanced technologies such as ITWS. The model performs cost-benefit analysis by comparing a baseline scenario without terminal area technologies against a scenario with technology. The difference between the two scenarios help decision makers justify whether technology investments are warranted of not.
A Demand Driven Airline and Airport Evolution Study
Seshadri, Anand (Virginia Tech, 2009-05-11)
The events of September 11,2001 followed by the oil price hike and the economic crisis of 2008, have lead to a drop in the demand for air travel. Airlines have attempted to return to profitability by cutting service in certain unattractive routes and airports. Simultaneously, delays and excess demand at a few major hubs have lead to airline introducing service at reliever airports. This dissertation attempts to capture the changes in the airline network by utilizing a supply-demand framework.
Demand Management in Evacuation: Models, Algorithms, and Applications
Bish, Douglas R. (Virginia Tech, 2006-07-31)
Evacuation planning is an important disaster management tool. A large-scale evacuation of a region by automobile is a difficult task, especially as demand is often greater than supply. This is made more difficult as the imbalance of supply and demand actually reduces supply due to congestion. Currently, most of the emphasis in evacuation planning is on supply management. The purpose of this dissertation is to introduce and study sophisticated demand management tools, specifically, staging and routing of evacuees. These tools can be used to produce evacuation strategies that reduce or eliminate congestion. A strategic planning model is introduced that accounts for evacuation dynamics and the non-linearities in travel times associated with congestion, yet is tractable and can be applied to large-scale networks. Objective functions of potential interest in evacuation planning are introduced and studied in the context of this model. Insights into the use of staging and routing in evacuation management are delineated and solution techniques are developed. Two different strategic approaches are studied in the context of this model. The first strategic approach is to control the evacuation at a disaggregate level, where customized staging and routing plans are produced for each individual or family unit. The second strategic approach is to control the evacuation at a more aggregate level, where evacuation plans are developed for a larger group of evacuees, based on pre-defined geographic areas. In both approaches, shelter requirements and preferences can also be considered. Computational experience using these two strategic approaches, and their respective solution techniques, is provided using a real network pertaining to Virginia Beach, Virginia, in order to demonstrate the efficacy of the proposed methodologies.
Development of a Decision Support Tool for Planning Rail Systems: An Implementation in TSAM
Joshi, Chetan (Virginia Tech, 2005-12-15)
A Decision Support model for planning Intercity Railways is presented in this research. The main aim of the model is to generate inputs for the logit model existing in the Virginia Tech Transportation Systems Analysis Model (TSAM). The inputs required by the TSAM logit model are travel time, travel cost and schedule delay. Travel times and travel costs for different rail technologies are calculated using a rail network and actual or proposed rail schedules. The concept of relational databases is used in the development of the network topology. Further, an event graph approach is used for analysis of the generated network. Shortest travel times and their corresponding travel costs between origin-destination pairs are found using Floyd's algorithm. Complete itineraries including transfers (if involved) are intrinsically held in the precedence matrix generated after running the algorithm. A standard mapping technique is used to obtain the actual routes. The algorithms developed, have been implemented in MATLAB. Schedules from the North American Passenger rail system AMTRAK are used to generate the sample network for this study. The model developed allows the user to evaluate what-if scenarios for various route frequencies and rail technologies such as Accelerail, High Speed Rail and Maglev. The user also has the option of modifying route information. Comparison of travel time values for the mentioned technology types in different corridors revealed that frequency of service has a greater impact on the total travel time in shorter distance corridors, whereas technology/line-haul speed has a greater influence on the total travel time in the longer distance corridors. This tool could be useful to make preliminary assessments of future rail systems. The network topology generated by the algorithm can further be used for network flow assignment, especially time-dependent assignment if used with dynamic graph algorithms.
Development of an Airport Choice Model for General Aviation Operations
Ashiabor, Senanu Y. (Virginia Tech, 2002-07-17)
The General Aviation Airport Choice model is an attempt to model General Aviation (GA) travel patterns in the US in order to provide a means of assessing the impact of General Aviation activities on the National Air Space system. The model will also serve as part of transportation planning tool to help assess the viability of deploying NASA's Small Aircraft Transportation Systems (SATS) aircraft as a competitive mode of transportation for intercity travel. The General Aviation Airport Choice model developed estimates General Aviation (GA) person-trips and number of aircraft operations given trip demand in the form of GA person trips from counties. A pseudo-gravity model is embedded in the model to distribute the inter-county person-trips to a prescribed set of airports in the US. The airport-to-airport person-trips are split into person-trips by three aircraft modes (single, multi and jet engine) using an attractiveness factor based on average occupancy, utilization and a distance distribution factor for each aircraft type and the number of aircraft based at each airport. The person-trips by aircraft type are then converted to aircraft operations using occupancy factors for each aircraft type. The final output from the model are aircraft operations trip-tables by aircraft type between the airports in the model. The GA trips are estimated in order to provide a means of assessing the impact of GA activities on the National Airspace System. The model output may be used to assess the viability of GA aircraft serving as a competitive mode of transportation for intercity travel.
Development of Nation Wide Cost-Benefit Analysis Framework for Aviation Decision Making Using Transportation Systems Analysis Model
Xu, Yue (Virginia Tech, 2008-03-28)
The aim of this study is to establish a nation-wide cost-benefit framework for aviation projection appraisal. This framework is built upon Transportation System Analysis Model developed at Virginia Tech Air Transportation System Model (TSAM). Both supply and demand characteristics and their inter-dependence are investigated. It attempts to solve the absence of supply constraints in aviation demand forecast in the literature. In addition, external costs in term of noise and emission are also considered. A national environmental impact analysis introduced by new generation small aircraft system is conducted. Two case studies are discussed to illustrate the framework. The first one is based on the GPS Wide Area Augmentation System (WAAS) Lower Landing Minima capability. It represents a nation-wide cost-benefit analysis with examination of both supply and demand. System-wide benefit of accessibility improvement and infrastructure cost are scrutinized at the same time. A prioritized set of candidate airports for this technology is provided as a result. The second study focuses on New York area. Benefits brought by DataComm technology are evaluated by multi-iteration simulations. DataComm is projected to reduce entry point intrail and final approach separation. The improvements are modeled at individual airport and New York airspace. Consumer surplus is estimated based on demand and delay relationship using TSAM.
Development of Optimization and Simulation Models for the Analysis of Airfield Operations
Baik, Hojong (Virginia Tech, 2000-05-22)
This research is concerned with the modeling and development of algorithmic approaches for solving airport operational problems that arise in Air Traffic Control (ATC) systems within the terminal area at hub airports. Specifically, the problems addressed include the Aircraft Sequencing Problem (ASP) for runway operations, the Network Assignment Problem (NAP) for taxiway operations, and a simulation model for the evaluation of current or proposed ATC system in detail. For the ASP, we develop a mathematical model and apply the Reformulation-Linearization-Technique (RLT) of Sherali and Adams to construct an enhanced tightened version of the proposed model. Since ASP is NP-Hard and in fact, it is a variation of the well-known Traveling Salesman Problem with time-windows, sub-optimal solutions are usually derived to accommodate the real-time constraints of ATC systems. Nevertheless, we exhibit a significant advancement in this challenging class of problem. Also for the purpose of solving relatively large sized problems in practice, we develop and test suitable heuristic procedures. For the NAP, we propose a quasi-dynamic assignment scheme which is based on the incremental assignment technique. This quasi-dynamic assignment method assumes that the current aircraft route is influenced only by the previous aircraft assigned to the network. This simplified assumption obviates the need for iterative rerouting procedures to reach a pure equilibrium state which might not be achievable in practical taxiway operations. To evaluate the overall system, we develop a microscopic simulation model. The simulation model is designed to have the capability for reproducing not only the dynamic behavior of aircraft, but also incorporates communication activities between controllers and pilots. These activities are critical in ATC operations, and in some instances, might limit the capacity of the facility. Finally, using the developed simulation model named Virginia Tech Airport Simulation Model (VTASM) in concert with ASP and NAP, we compare the overall efficiencies of several control strategies, including that of the existing control system as well as of the proposed advanced control system.
Enhancements to Transportation Analysis and Simulation Systems
Jeihani Koohbanani, Mansoureh (Virginia Tech, 2004-11-30)
Urban travel demand forecasting and traffic assignment models are important tools in developing transportation plans for a metropolitan area. These tools provide forecasts of urban travel patterns under various transportation supply conditions. The predicted travel patterns then provide useful information in planning the transportation system. Traffic assignment is the assignment of origin-destination flows to transportation routes, based on factors that affect route choice. The urban travel demand models, developed in the mid 1950s, provided accurate and precise answers to the planning and policy issues being addressed at that time, which mainly revolved around expansion of the highway system to meet the rapidly growing travel demand. However, the urban transportation planning and analysis have undergone changes over the years, while the structure of the travel demand models has remained largely unchanged except for the introduction of disaggregate choice models beginning in the mid-1970s. Legislative and analytical requirements that exceed the capabilities of these models and methodologies have driven new technical approaches such as TRANSIMS. The Transportation Analysis and Simulation System, or TRANSIMS, is an integrated system of travel forecasting models designed to give transportation planners accurate, and complete information on traffic impacts, congestion, and pollution. It was developed by the Los Alamos National Laboratory to address new transportation and air quality forecasting procedures required by the Clean Air Act, the Intermodal Surface Transportation Efficiency Act, and other regulations. TRANSIMS includes six different modules: Population Synthesizer, Activity Generator, Route Planner, Microsimulator, Emissions Estimator, and Feedback. This package has been under development since 1994 and needs significant improvements within some of its modules. This dissertation enhances the interaction between the Route Planner and the Microsimulator modules to improve the dynamic traffic assignment process in TRANSIMS, and the Emissions Estimator module. The traditional trip assignment is static in nature. Static assignment models assume that traffic is in a steady-state, link volumes are time invariant, the time to traverse a link depends only on the number of vehicles on that link, and that the vehicle queues are stacked vertically and do not traverse to the upstream links in the network. Thus, a matrix of steady-state origin-destination (O-D) trip rates is assigned simultaneously to shortest paths from each origin to a destination. To address the static traffic assignment problems, dynamic traffic assignment models are proposed. In dynamic traffic assignment models, the demand is allowed to be time varying so that the number of vehicles passing through a link and the corresponding link travel times become time-dependent. In contrast with the static case, the dynamic traffic assignment problem is still relatively unexplored and a precise formulation is not clearly established. Most models in the literature do not present a solution algorithm and among the presented methods, most of them are not suitable for large-scale networks. Among the suggested solution methodologies that claim to be applicable to large-scale networks, very few methods have been actually tested on such large-scale networks. Furthermore, most of these models have stability and convergence problem. A solution methodology for computing dynamic user equilibria in large-scale transportation networks is presented in this dissertation. This method, which stems from the convex simplex method, routes one traveler at a time on the network and updates the link volumes and link travel times after each routing. Therefore, this method is dynamic in two aspects: it is time-dependent, and it routes travelers based on the most updated link travel times. To guarantee finite termination, an additional stopping criterion is adopted. The proposed model is implemented within TRANSIMS, the Transportation Analysis and Simulation System, and is applied to a large-scale network. The current user equilibrium computation in TRANSIMS involves simply an iterative process between the Route Planner and the MicroSimulator modules. In the first run, the Route Planner uses free-flow speeds on each link to estimate the travel time to find the shortest paths, which is not accurate because there exist other vehicles on the link and so, the speed is not simply equal to the free-flow speed. Therefore, some paths might not be the shortest paths due to congestion. The Microsimulator produces the new travel times based on accurate vehicle speeds. These travel times are fed back to the Route Planner, and the new routes are determined as the shortest paths for selected travelers. This procedure does not necessarily lead to a user equilibrium solution. The existing problems in this procedure are addressed in our proposed algorithm as follows. TRANSIMS routes one person at a time but does not update link travel times. Therefore, each traveler is routed regardless of other travelers on the network. The current stopping criterion is based only on visualization and the procedure might oscillate. Also, the current traffic assignment spends a huge amount of time by iterating frequently between the Route Planner and the Microsimulator. For example in the Portland study, 21 iterations between the Route Planner and the Microsimulator were performed that took 33:29 hours using three 500-MHZ CPUs (parallel processing). These difficulties are addressed by distributing travelers on the network in a better manner from the beginning in the Route Planner to avoid the frequent iterations between the Route Planner and the Microsimulator that are required to redistribute them. By updating the link travel times using a link performance function, a near-equilibrium is obtained only in one iteration. Travelers are distributed in the network with regard to other travelers in the first iteration; therefore, there is no need to redistribute them using the time-consuming iterative process. To avoid problems caused by link performance function usage, an iterative procedure between the current Route Planner and the Microsimulator is performed and a user equilibrium is found after a few iterations. Using an appropriate descent-based stopping criterion, the finite termination of the procedure is guaranteed. An illustration using real-data pertaining to the transportation network of Portland, Oregon, is presented along with comparative analyses. TRANSIMS framework contains a vehicle emissions module that estimates tailpipe emissions for light and heavy duty vehicles and evaporative emissions for light duty vehicles. It uses as inputs the emissions arrays obtained the Comprehensive Modal Emissions Model (CMEM). This dissertation describes and validates the framework of TRANSIMS for modeling vehicle emissions. Specifically, it identifies an error in the model calculations and enhances the emission modeling formulation. Furthermore, the dissertation compares the TRANSIMS emission estimates to on-road emission-measurements and other state-of-the-art emission models including the VT-Micro and CMEM models.
Forecasting Model for Air Taxi, Commercial Airline, and Automobile Demand in the United States
Baik, Hojong; Trani, Antonio A.; Hinze, Nicolas; Swingle, Howard; Ashiabor, Senanu; Seshadri, Anand (Transportation Research Board of the National Academies, 2008)
A nationwide model predicts the annual county-to-county person roundtrips for air taxi, commercial airline, and automobile at 1-year intervals through 2030. The transportation systems analysis model (TSAM) uses the four-step transportation systems modeling process to calculate trip generation, trip distribution, and mode choice for each county origin–destination pair. Network assignment is formulated for commercial airline and air taxi demand. TSAM classifies trip rates by trip purpose, household income group, and type of metropolitan statistical area from which the round-trip started. A graphical user interface with geographic information systems capability is included in the model. Potential applications of the model are nationwide impact studies of transportation policies and technologies, such as those envisioned with the introduction of extensive air taxi service using very light jets, the next-generation air transportation system, and the introduction of new aerospace technologies.
Hybrid Multi-Objective Optimization Models for Managing Pavement Assets
Wu, Zheng (Virginia Tech, 2008-01-25)
Increasingly tighter budgets, changes in government role/function, declines in staff resources, and demands for increased accountability in the transportation field have brought unprecedented challenges for state transportation officials at all management levels. Systematic methodologies for effective management of a specific type of infrastructure (e.g., pavement and bridges) as well as for holistically managing all types of infrastructure assets are being developed to approach these challenges. In particular, the intrinsic characteristics of highway system make the use of multi-objective optimization techniques particularly attractive for managing highway assets. Recognizing the need for effective tradeoff tools and the limitations of state-of-practice analytical models and tools in highway asset management, the main objective of this dissertation was to develop a performance-based asset management framework that uses multi-objective optimization techniques and consists of stand-alone but logically interconnected optimization models for different management levels. Based on a critical review of popular multi-objective optimization techniques and their applications in highway asset management, a synergistic integration of complementary multi-criteria optimization techniques is recommended for the development of practical and efficient decision-supporting tools. Accordingly, the dissertation first proposes and implements a probabilistic multi-objective model for performance-based pavement preservation programming that uses the weighting sum method and chance constraints. This model can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon, but is found more suitable to problems with small number of objective functions due to its computational intensity. To enhance the above model, a hybrid model that requires less computing time and systematically captures the decision maker's preferences on multiple objectives is developed by combining the analytic hierarchy process and goal programming. This model is further extended to also capture the relative importance existent within optimization constraints to be suitable for allocations of funding across multiple districts for a decentralized state department of transportation. Finally, as a continuation of the above proposed models for the succeeding management level, a project selection model capable of incorporating qualitative factors (e.g. equity, user satisfaction) into the decision making is developed. This model combines k-means clustering, analytic hierarchy process and integer linear programming. All the models are logically interconnected in a comprehensive resource allocation framework. Their feasibility, practicality and potential benefits are illustrated through various case studies and recommendations for further developments are provided.
Integrated Modeling of Air Traffic, Aviation Weather, and Communication Systems
Quan, Chuanwen (Virginia Tech, 2007-04-20)
Aviation suffers many delays due to the lack of timely air traffic flow management. These delays are also caused by the uncertainty weather information; and the lack of efficient dissemination of weather products to pilots. It is clear that better models are needed to quantify air traffic flow in three flight regions - en-route, in the terminal, and on the ground, to determine aviation weather information requirements at each region, and to quantify their bandwidth requirements. Furthermore, the results from those models can be used to select alternative future aviation communication systems. In this research, the 'ITHINK' and 'MATLAB' software packages have been used to develop a lumped Air Traffic Flow Model (ATFM) and an Aviation Weather Information and Bandwidth Requirements Model (AWINBRM). The ATFM model is used to quantify the volume of air traffic in each phase of flight in three flight regions. This model can be used to study navigation, surveillance, and communication requirements. The AWINBRM model is used to study aviation weather information requirements in different flight phases of flight. Existing and potential communication systems used for transmitting aviation weather information are explored in this research. Finally, a usable and practical computer model - Aircraft Impacted and Detour Model (AIDM) around an aviation weather system is developed. This model is used to compare the costs between detoured flights around a weather system and delayed flights at the airports. The purpose of this research is to study air traffic flow and aviation weather information and bandwidth requirements through modeling. The ultimate goal of the models described here is to serve as a living laboratory where policies can be tried before implementing them into the real system. Moreover, these computer models can evolve dynamically through time allowing decision makers to exercise policies at various points in time to quantify results with ease. This research would be a first integrated model for combing air traffic flow and aviation weather requirements and determining the quantity of aviation weather information between pilot and ground service centers. This research would be a guideline for aviation industry to build an efficient and timely aviation weather information transmission system with minimum budget. Consequently, this research will reduce aviation delays and improve aviation safety.
Integration of the Transportation Systems Analysis Model for the Small Aircraft Transportation System
Hinze, Nicolas Karlsson (Virginia Tech, 2005-06-20)
Standalone computer modules for county to county travel demand forecasting have been integrated. The Trip Generation, Trip Distribution and Mode Choice modules have been unified under one Graphical User Interface (GUI). The outputs are automatically mapped using Geographic Information Systems (GIS) technology to allow immediate and spatial analysis. The integrated model allows for faster running times and quicker analysis of the results. The ability to calculate travel time savings for travelers was also included to the final model. The modeling framework developed is known as the Transportation Systems Analysis Model (TSAM).
Measuring and Ranking Efficiency of Major Airports in the United States Using Data Envelopment Analysis
Lee, Myunghyun (Virginia Tech, 2004-07-08)
An airport is an important piece of infrastructure in air transportation system. This project focuses on measuring and ranking the efficiency of airports in the United States using the basic DEA, Ranking DEA, Goal programming and DEA and TOPSIS. In general, airport authorities of relatively inefficient airports are trying to benchmark the operational strategies of efficient airports. This project focuses on evaluating hub airports in the United States. ATL, LAX, and MEM airports are relatively efficient among forty four hub airports in the United States based on the performances and airport facilities of the 2000 year when the results of all applied methods in this project, the basic DEA ranking, the Cross Efficiency ranking, the Andersen-Petersen ranking and TOPSIS ranking method, are compared. The implication of this project is that airport authorities in the United States would benchmark these three airports to maximize operation and management efficiency for their airports. In general, most of the airports are handling passengers and freight. Therefore, ATL and LAX would be the most efficient hub airports in the United States. The capacities of airport facilities and more appropriate input data like financial data should be considered in the follow up research.
Mesoscopic Fuel Consumption and Emission Modeling
Yue, Huanyu (Virginia Tech, 2008-03-25)
The transportation sector is a major contributor to U.S. fuel consumption and emissions. Consequently, assessing the environmental impacts of transportation activities is essential for air-quality improvement programs. Current state-of-the-art models estimate vehicle emissions based on typical urban driving cycles. Most of these models offer simplified mathematical expressions to compute fuel consumption and emission rates based on average link speeds while ignoring transient changes in a vehicle's speed and acceleration level as it travels on a highway network. Alternatively, microscopic models capture these transient effects; however, the application of microscopic models may be costly and time consuming. Also, these tools may require a level of input data resolution that is not available. Consequently, this dissertation attempts to fill the void in energy and emission modeling by a framework for modeling vehicle fuel consumption and emissions mesoscopically. This framework is utilized to develop the VT-Meso model using a number of data sources. The model estimates average light-duty vehicle fuel consumption and emission rates on a link-by-link basis using up to three independent variables, namely: average travel speed, average number of stops per unit distance, and average stop duration. The mesoscopic model utilizes a microscopic vehicle fuel consumption and emission model that was developed at Virginia Tech to compute mode-specific fuel consumption and emission rates. This model, known as VT-Micro, predicts the instantaneous fuel consumption and emission rates of HC, CO and NOx of individual vehicles based on their instantaneous speed and acceleration levels. The mesoscopic model utilizes these link-by-link input parameters to construct a synthetic drive cycle and compute average link fuel consumption and emission rates. After constructing the drive cycle, the model estimates the proportion of time that a vehicle typically spends cruising, decelerating, idling and accelerating while traveling on a link. A series of fuel consumption and emission models are then used to estimate the amount of fuel consumed and emissions of HC, CO, CO2, and NOX emissions for each mode of operation. Subsequently, the total fuel consumed and pollutants emitted by a vehicle while traveling along a segment are estimated by summing across the different modes of operation and dividing by the distance traveled to obtain distance-based average vehicle fuel consumption and emission rates. The models are developed for normal and high emitting vehicles. The study quantifies the typical driver deceleration behavior for incorporation within the model. Since this model constructs a drive cycle which includes a deceleration mode, an accurate characterization of typical vehicle deceleration behavior is critical to the accurate modeling of vehicle emissions. The study demonstrates that while the deceleration rate typically increases as the vehicle approaches its desired final speed, the use of a constant deceleration rate over the entire deceleration maneuver is adequate for environmental modeling purposes. Finally, the study validates the model on a freeway and urban arterial network. The results demonstrate that the model provides accurate estimates of vehicle fuel consumption and emission rates and is adequate for the evaluation of transportation operational projects.
Mode Choice Methodology in TRANSIMS
Lu, Qingying (Virginia Tech, 2002-09-20)
TRANSIMS is a disaggregate, behavioral transportation planning package developed under US DOT's and EPA funding at the Los Alamos National Laboratory (LANL). It is an integrated system of travel forecasting models designed to give transportation planners accurate, complete information on traffic impacts, congestion, and pollution by simulating second-by-second movements of every person and every vehicle through the transportation network of a large metropolitan area. There is no built-in module for travellers' mode choices In TRANSIMS. The modes going with the shortest path are always taken. In Portland Study, a mode choice methodology implemented by a series of feedback processes is proposed. However, it uses aggregate, deterministic mode choice model. There is little solid theoretic ground for the format and coefficients of the generalized costs used in the calibration process. The accessibility to a mode, especially to Transit, was also not included in the model. In the thesis, a disaggregate and deterministic mode choice methodology in TRANSIMS is developed. The accessibility to each mode is analyzed and included in the model. The methodology is then implemented on the Blacksburg transportation planning study, namely Blacksburg_Lite. The analysis of the result is based on the indicator of mode choice, mode split between Transit and Auto. The indicator is close to that in survey data and converged fast. Therefore, this mode choice methodology could be used within TRANSIMS framework.
A Model to Assess the Mobility of the National Airpspace System (NAS)
Seshadri, Anand (Virginia Tech, 2003-12-17)
One of the ways to define mobility in a transportation system is total travel time for all travelers using the transportation network. A good assessment of the mobility is essential for knowing the points of congestion in the network and the factors responsible for the congestion. Also the change in mobility from the baseline to the horizon year would give the modeler an idea of the effectiveness of the various transportation systems. One of the applications of the mobility measurement is the evaluation of aviation technologies proposed by FAA to ease the congestion. This paper addresses a method to estimate the mobility of the air transportation network in the baseline year (2000). Also presented is a method to estimate the mobility to the horizon year by considering congestion on the roadway.

Browsing by Author "Baik, Hojong"

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