Global ETD Search

11	Improving Analytical Travel Time Estimation for Transportation Planning Models Lu, Chenxi 19 May 2010 (has links) This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results. Traffic Demand Estimation Traffic Assignment Planning Modeling Travel Time Intersection Delay Travel Demand Forecasting Simulation Optimization Signal Timing Civil and Environmental Engineering
12	Economic Viability Of International Airline Operations From India Srinidhi, S 05 1900 (has links) (PDF) Route planning forms an important aspect of airline operations for them to sustain the effects of deregulation and fierce competition. The Indian economic liberalization in 1991 has seen diminishing monopoly of Air India and dynamic demand splits amongst the service providers. Our research focuses on developing an aggregate route traffic demand forecasting (RTDF) model specifically for international carriers operating from India. The model is an econometric model that combines concepts of the traditional Gravity model of Physics and the Micro-economic theoretic model that links demand to price. In other words, the RTDF model is a fusion of the behavioral and gravity models. While developing the model, Becker’s approach of utility maximization has been made use of, thereby combining time and other inputs required to produce travel. The model is developed for the existing international routes from India with 2005 aggregative data provided by International Civil Aviation Organization (ICAO), which spanned 15 countries in Europe, Asia, Canada, and North America. The model has been validated and tested for its predictive power on a few intentionally left out routes from the original sample. The model explains about 70% of the variance, which is well above the acceptable zone for cross-sectional data. The model is then estimated for 2007 data on a few randomly selected high demand routes; the prediction error ranging from a minimum of 3.5% to a maximum of 13%, a range well within the acceptable error limits. We derive a sector-cost-model (SCM) by applying the concept of break-even analysis on the RTDF model. The SCM provides cost estimates on a particular route at various levels of airfare. The SCM helps us gain further insights into the business nature prevailing in the airline sector. On the viability of operations, we propose the sector-operation-fare (SOF) to be charged on a respective route, given the load factor, if the airline wishes to continue operations. For arriving at the SOF, we follow a demand oriented framework that comprises of two demand curves: the airline curve and the traffic curve. The numerical analyses provide room for policy formulations that help airlines in refining, redefining, and revitalizing the decision-making process in their operations. Airlines can use this model to forecast demand for a newly contemplated route and obtain a fair idea of the price they can charge the customer. In other words, airlines can estimate the economic viability of operations on a respective route. Air Transportation - India Airline Traffic Model Airline Operations Air Transport Dynamics Route Traffic Demand Forecasting (RTDF) Sector-operation-fare (SOF) Transportation Enginering
13	Erweiterung der Verkehrsnachfragemodellierung um Aspekte der Raum- und Infrastrukturplanung / Extension of traffic demand modeling by considerations of land use and infrastructure planning Schiller, Christian 09 August 2007 (has links) (PDF) Diese Arbeit stellt grundlegend zwei Modellentwicklungen der Verkehrsangebots- und Verkehrsnachfragemodellierung vor. Die erste Entwicklung bezieht sich auf die simultane Ziel- und Verkehrsmittelwahl in Abhängigkeit von Strukturgrößen und/oder Lagegunst. Es werden neue Randsummenbedingungen beschrieben und vorhandene neu definiert. Der neue Modellansatz erlaubt eine Bestimmung minimaler und maximaler Verkehrsaufkommen und stellt eine Erweiterung der theoretischen Grundlagen als auch der praktischen Anwendbarkeit dar. So können alle derzeit bekannten Randsummenbedingungen durch einen Algorithmus (auch innerhalb einer Quelle-Ziel-Gruppe) berechnet werden. Der zweite Ansatz ist ein Werkzeug, welches in Abhängigkeit des vorhandenen Verkehrsangebotes verkehrsplanerisch wünschenswerte quantitative Flächen- bzw. Gebietsnutzungen abschätzt. Aufbauend auf der Verkehrsangebots- und Verkehrsnachfragemodellierung werden Infrastrukturgrößen durch eine aufzustellende Zielfunktion (z. B. minimale Verkehrsarbeit), unter Beachtung vorhandener Freiheitsgrade der Flächennutzung je Verkehrsbezirk, optimiert. Diese Freiheitsgrade werden als minimale und maximale Strukturgrößengrenzen durch die Raum- und Stadtplanung definiert, womit sie den vielfältigen Einflussgrößen dieser Planungen unterliegen und dadurch städtebaulich verträglich sind. Der Modellansatz bildet die für die Infrastrukturplanung wichtigen Wechselwirkungen des durch den Stadt- und Verkehrsplaner angestrebten Systemoptimums (Infrastrukturgrößenverteilung eines Gebietes) mit dem durch den einzelnen Verkehrsteilnehmer angestrebten Nutzenoptimum (Verkehrsnachfrage) ab. / This work basically introduces two model developments of traffic supply and traffic demand modeling. The first development refers to the simultaneous destination and mode choice into dependence of structure sizes and/or accessibility. New constraints are described and available constraints were defined newly. The new model enables the determination of minimal and maximum volumes of traffic (constraints). The new explanatory model is an expansion of the theoretical bases and the practical applicability. So all currently known constraints can be calculated by one algorithm (also within an origin destination group). The second approach is a tool which describes desirable quantitative traffic planningly land uses against the available traffic supply. It uses an algorithm that keeps minimal and maximum structure size limits while it determining e.g. minimal traffic work. Within the algorithm the complete traffic demand will be calculated. The complete model shows the important interactions of the infrastructure planning by the town and transport planer (a striven system optimum) with the traffic demand by the single road user (a striven user equilibrium). Verkehrsnachfrage Verkehrsplanung Stadtplanung Raumplanung Modell simultane Ziel- und Verkehrsmittelwahl Zielwahlmodell Randsummenbedingungen EVA Strukturgrößenoptimierung Flächennutzung traffic demand traffic supply transportation planning constrained model EVA land use planning land use transportation model transportation interaction ddc:620 rvk:ZO 3100
14	Erweiterung der Verkehrsnachfragemodellierung um Aspekte der Raum- und Infrastrukturplanung Schiller, Christian 11 July 2007 (has links) Diese Arbeit stellt grundlegend zwei Modellentwicklungen der Verkehrsangebots- und Verkehrsnachfragemodellierung vor. Die erste Entwicklung bezieht sich auf die simultane Ziel- und Verkehrsmittelwahl in Abhängigkeit von Strukturgrößen und/oder Lagegunst. Es werden neue Randsummenbedingungen beschrieben und vorhandene neu definiert. Der neue Modellansatz erlaubt eine Bestimmung minimaler und maximaler Verkehrsaufkommen und stellt eine Erweiterung der theoretischen Grundlagen als auch der praktischen Anwendbarkeit dar. So können alle derzeit bekannten Randsummenbedingungen durch einen Algorithmus (auch innerhalb einer Quelle-Ziel-Gruppe) berechnet werden. Der zweite Ansatz ist ein Werkzeug, welches in Abhängigkeit des vorhandenen Verkehrsangebotes verkehrsplanerisch wünschenswerte quantitative Flächen- bzw. Gebietsnutzungen abschätzt. Aufbauend auf der Verkehrsangebots- und Verkehrsnachfragemodellierung werden Infrastrukturgrößen durch eine aufzustellende Zielfunktion (z. B. minimale Verkehrsarbeit), unter Beachtung vorhandener Freiheitsgrade der Flächennutzung je Verkehrsbezirk, optimiert. Diese Freiheitsgrade werden als minimale und maximale Strukturgrößengrenzen durch die Raum- und Stadtplanung definiert, womit sie den vielfältigen Einflussgrößen dieser Planungen unterliegen und dadurch städtebaulich verträglich sind. Der Modellansatz bildet die für die Infrastrukturplanung wichtigen Wechselwirkungen des durch den Stadt- und Verkehrsplaner angestrebten Systemoptimums (Infrastrukturgrößenverteilung eines Gebietes) mit dem durch den einzelnen Verkehrsteilnehmer angestrebten Nutzenoptimum (Verkehrsnachfrage) ab. / This work basically introduces two model developments of traffic supply and traffic demand modeling. The first development refers to the simultaneous destination and mode choice into dependence of structure sizes and/or accessibility. New constraints are described and available constraints were defined newly. The new model enables the determination of minimal and maximum volumes of traffic (constraints). The new explanatory model is an expansion of the theoretical bases and the practical applicability. So all currently known constraints can be calculated by one algorithm (also within an origin destination group). The second approach is a tool which describes desirable quantitative traffic planningly land uses against the available traffic supply. It uses an algorithm that keeps minimal and maximum structure size limits while it determining e.g. minimal traffic work. Within the algorithm the complete traffic demand will be calculated. The complete model shows the important interactions of the infrastructure planning by the town and transport planer (a striven system optimum) with the traffic demand by the single road user (a striven user equilibrium). info:eu-repo/classification/ddc/620 ddc:620
15	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics
16	Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement El-Khatib, Mayar January 2010 (has links) While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond. highway development decision making under uncertainty real options jump processes infinitely divisible distributions Lévy processes measure theory characteristic function characteristic exponent Lévy jump measure probability measure cádlág stochastic process Wiener process Poisson process compound Poisson process finite activity models jump diffusion models Merton model Gaussian jump process Kou model double exponential jump process leptokurtic volatility smile infinite activity models pure jumps process generalized hyperbolic model modified Bessel function negative inverse Gaussian model geometric Brownian motion model log-normal distribution model normality assumption heavy-tailed distribution asymmetric distribution quantile-quantile plot Rydberg algorithm parameter calibration moments cummulants sum of squares Monte Carlo simulation least-squares regression backward dynamic programming discrete-time Markov chain land price traffic demand highway service quality index data collection traffic volume Annual Average Daily Traffic Ontario Ministry of Transportation Land Registry Office Freedom of Information Act seasonality value of transportation types of transportation systems importance of highway systems cost of wrong decisions monetary cost private sector cost human cost land expropriation environmental cost irreversibility cost factor time cost factor political cost factor opportunity cost opportunity cost of wrong decisions economic cost of wrong decisions economic cost of mis-estimation economic profit of wrong decisions cost of inaction price of making right decisions scope of decisions rehabilitation decision land acquisition decision expansion decision uncertainty modeling land acquisition cost expropriation cost construction cost material cost Montréal-Mirabel International Airport Pickering Airport 407 Express Toll Route Highway 407 Statistics

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