Path Of Taxes Research Articles

Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model

Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this paper, a bilevel spatial and temporal optimization model of aircraft taxiing is constructed. The upper-level model optimizes the aircraft taxiing path, and the lower-level model optimizes the taxiing start time of the aircraft. By the iterative optimization of the upper- and lower-level interactions, the aviation fuel consumption, flight waiting time, and number of taxiing conflicts are reduced. To improve the calculation accuracy, the depth-first search algorithm is utilized to generate the set of available paths for aircraft during the model solution process, and a model solution method based on the genetic algorithm is constructed. Simulation experiments using Tianjin Binhai International Airport as the research object show that adopting the waiting taxiing strategy can effectively avoid taxiing conflicts and reduce aviation fuel consumption by 753.18 kg and 188.84 kg compared to the available path sets generated using Dijkstra’s algorithm and those created manually based on experience, respectively. Conversely, adopting an immediate taxi-out strategy caused 54 taxiing conflicts and increased aviation fuel consumption by 49.44 kg. These results can provide safe and environmentally friendly taxiing strategies for the sustainable development of the air transportation industry.

Energy Efficiency and Directed Technical Change: Implications for Climate Change Mitigation

Abstract I develop a directed technical change model of economic growth and energy efficiency in order to study the impact of climate change mitigation policies on energy use. I show that the standard Cobb–Douglas production function used in the environmental macroeconomics literature overstates the reduction in cumulative energy use that can be achieved with a given path of energy taxes. I also show that, in the model, the government combines energy taxes with research and development (R&D) policy that favors output-increasing technology—rather than energy efficiency technology—to maximize welfare subject to a constraint on cumulative energy use. In addition, I study energy use dynamics following sudden improvements in energy efficiency. Exogenous shocks that increase energy efficiency also decrease the incentive for subsequent energy efficiency R&D and increase long-run energy use relative to a world without the original shock. Subsidies for energy efficiency R&D, however, permanently alter R&D incentives and decrease long-run energy use.

Methodology for database collection of Taxi drivers' behavior in real time

In any city of the world, the taxi paths provide a big reasonable data source for urban studies given their ability to capture a large proportion of trips between different origins and destinations. In order to collect data in real time in situ from public service drivers (Taxis), a questionnaire which had two components was designed: i) Survey of revealed preferences and personality aspects through direct observation of drivers and ii) route information through GPS devices that measure distance and time during the journey.Data collection focused on the reaction to information about and during a trip, drivers’ willingness to receive information about the network, their personality profile, their behavior when driving and their influence on the choice of a route.Taxi Data collection, Driver Behavior, Human factors, Route choice.

Research on Joint Ground Movement Optimization Based on Bilevel Programming

Requirements of digitization, intellectualization, and integration for the programming and management of air transportation have been recommended as information technology booms. A variety of single ground movement optimization problems have been discussed with few taking the impact of other segments into account. In this research, bilevel programming is applied to simultaneously consider three problems including the gate assignment, taxi path scheduling, and pushback time delay. For evaluating the strategy of gate assignment and measuring its connection with taxiing comprehensively, an auxiliary variable and the matching degree of gate and aircraft are introduced. In addition, an algorithm incorporating the genetic algorithm and routing algorithm is designed to obtain a solution with satisfactory performance in both taxi time and conflict risk. The scheme obtained also assigns aircraft to gates more appropriately and maintains the characteristics of environmental protection as well as high efficiency, showing considerable reliability in practice.

Vehicle Path Recognition Approach Based on Incomplete Automatic Vehicle Identification

Vehicle path recognition is one of the key methods used in urban traffic research, such as traffic flow characteristics analysis. Automatic vehicle identification (AVI) is often used for vehicle path recognition and is suitable for mixed traffic flow with connected automated vehicles (CAVs). However, there still remain issues in overcoming the difficulty of vehicle path identification caused by the discontinuity of AVI data and solving the problem of low precision of AVI application. To model the vehicle path, this paper selects the AVI system of Yicheng Town, Linfen City, Shanxi Province, as a test bed. The travel modes of private cars and taxis are discussed, and the quantified indicators of the model are determined. By combining the analytic hierarchy process (AHP) with the entropy weight method (EWM) to get the weights of the indicators, the path recognition model under incomplete AVI data is proposed. Finally, based on the path recognition model proposed in this paper, case studies are carried out for the private car and taxi path recognition, respectively. The validity of the path identification through practical studies and the effect of the number of missing nodes of AVI equipment on the accuracy of the model are discussed. The results show that the recognition of the travel path using the proposed model is consistent with the actual travel path. The accuracy of the proposed model is more than 60% when the number of missing nodes is less than 7 in total 31 nodes. Considering the decision models for private cars and taxis, respectively, the proposed model provides a method for vehicle path recognition based on incomplete AVI data.

Optimization and evaluation for autonomous taxi ride-sharing schedule and depot location from the perspective of energy consumption

Taxi ride-sharing based on autonomous vehicles (AVs) is seen as a new and promising mode of urban mobility to promise a huge social and environmental benefits, such as conserving fuel, mitigating traffic congestions, reducing air pollution. Although a number of studies have focused on taxipooling or taxi ride-sharing, majority of these studies just concerned about the vehicle routing problem. Limited studies were conducted to excavate and understand the potential benefits of this new mobility mode through a comprehensively designed taxi ride-sharing system. To fill this gap, this study tries to design an autonomous taxi ride-sharing system for commuting trips from the perspective of energy consumption, in which schedule (i.e., taxi type, taxi path, feet size) and depot location are optimized within a unified model. Based on this, we further evaluate its effectiveness in reductions of energy consumption and vehicle usage, and analyze the influences of several key factors on the system efficiency. Case studies show that the taxi ride-sharing service mode needs fewer vehicles than the private car travel mode, and outperforms the traditional taxi service mode in terms of fuel consumption. Moreover, it is found that trip density is an important influence factor on the benefits of taxi ride-sharing system. This study aims to provide transportation managers a good understanding of the energy benefits of well-designed autonomous taxi ride-sharing system.

Research on Aircraft Surface Taxi Path Planning and Conflict Detection and Resolution

Aircraft surface taxiing conflict avoidance is mostly adopted by waiting and rerouting methods, but this method does not consider the difference in total taxiing time that may be caused by different strategies. In this study, the airport taxiing path optimization model and taxiing area division model are constructed first. Then, the taxiway use is controlled by subregion based on the analysis of the surface activity area connection relationship. Based on the results of aircraft surface taxiway preselection, the time window of the taxiing area is solved and conflict detection is performed. For aircraft with taxiing conflicts, waiting or changing paths is selected to deconflict taxiing by comparing priorities. An improved A∗ algorithm solution is applied to generate conflict-free glide paths and new glide trajectory occupancy time windows, while the glide paths of aircraft without glide conflicts are not affected. The results of the study show that the use of time windows for conflict detection and deconfliction can further reduce the total taxiing time of aircraft operating on the surface, resulting in a significant reduction in the number of aircraft conflicts, and thus, airport operational safety is ensured. This study has a high practical value and is expected to be applied in the real-time control decision of aircraft taxiing in the future.

4D Trajectory Planning of Aircraft Taxiing considering Time and Fuel

Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed, and the model is optimized based on the shortest taxi time. Although it is easy to solve, it does not consider the change of the speed profile when the aircraft turns, and the optimal taxiing time of the aircraft does not necessarily bring the optimal taxiing fuel consumption. In this paper, the aircraft’s taxi distance and the number of turns in the taxi are considered. The aircraft path planning model with the shortest total distance of the airport surface is established. The improved A ∗ algorithm is used to obtain the shortest path P. Based on this, the shortest path P is established. Considering the multitarget velocity profile model of time and fuel consumption, a heuristic search is used to generate an accurate velocity profile for each path to obtain a 4D trajectory of the aircraft and then quantitative analysis of the impact of aircraft pollutant emissions on the airport environment based on 4D trajectory taxi time. The experimental results show that, compared with the traditional optimization method without considering the turning times, the total taxiing distance and turning times of the aircraft are greatly reduced. By balancing the taxiing time and fuel consumption, a set of Pareto-optimal velocity profiles is generated for the aircraft taxiing path; at the same time, it will help the airport save energy and reduce emissions and improve the quality of the airport environment. It has a high practical application value and is expected to be applied in the real-time air traffic control decision of aircraft surface in the future.

Carbon Footprint and Total Fuel Consumption Benefit Evaluation of a Proposed Decision Support System Algorithm for Istanbul Ataturk Airport Surface Movement Area

The continuous growth in air traffic volume causes extra operational fuel consumption due to serious ground delays at major airports. Effective ground movement management of aircraft plays an essential role in reducing or even eliminating these ground holds and congestions. Ground movement of aircraft is conventionally done by ground controllers using conventional techniques, which rely on static and short-term (dynamic) planning. Such planning usually overlooks possible in-flight delays, which lead to gate assignment problems (GAP) at destination airports. Ground movement decision support system is proposed as an alternative method to mitigate these problems. This system allocates available taxi paths to arriving and departing aircraft. Such a dynamic planning provides more robust taxi path assignment and delay management at the airports movement area especially in the peak hours. This study analyzes time benefits and time cost effects of this system using SIMMOD, which is a fast time simulation tool. In order to demonstrate the fuel consumption benefits of tactical taxi path allocation, two scenarios (baseline and alternative), have been generated and tested for Istanbul Ataturk Airport. Keywords: Airport Modeling, Carbon Footprint, Heuristic Algorithm, Airport Ground Delays, Air Traffic Management DOI: 10.7176/JSTR/6-04-06

ASSESSING EFFECTS OF BUS SERVICE QUALITY ON PASSENGERS’ TAXI-HIRING BEHAVIOR

Due to low quality of bus service in a congested road network, some bus-waiting travelers would take taxis instead in order to save time or get to their destinations on time. However, the correlation between bus service quality and passengers’ taxi-hiring behavior is essentially unknown. This paper aims to assess the effects of bus service quality on taxi-hiring behavior based on historical data from the Global Position Systems (GPS) equipped buses and taxis in the city of Shenzhen, China. The taxi-hiring behavior is captured by analyzing the taxi-data, such as the origins of passenger pick-up, destinations of passengers drop-off, and taxi paths from the taxi movement data. The quality of bus service is assessed based on the bus location information. Parametric, semiparametric and nonparametric models are developed to explore the effects of bus service quality on taxi-hiring behavior. The results indicate that bus speed, headway and stoppage time are the core factors affecting passengers’ taxi-hiring behavior. Availability of metro, time of the day and bus route directions are the secondary important factors. This study shows that when buses run with relatively low and stable speed, taxi-hiring behavior is sensitive to the slight change of bus speed. More passengers would like to take taxis when bus speed starts to decline, or speed or stoppage time of buses tends to be irregular. However, the effects of bus headway on taxi-hiring behavior are more complicated. A specific turning point (coefficient of variability of mean headway ≈ 0.7) in the relationship between taxi-hiring behavior and bus headway is shown in this paper. Based on data mining and model development, this research presents details on attributes of bus service that drive passengers to switch to taxis and how changes in those attributes encourage modal shift from buses to taxis.

Path Planning for Aircraft Fleet Launching on the Flight Deck of Carriers

This paper studies the path planning problem for aircraft fleet taxiing on the flight deck of carriers, which is of great significance for improving the safety and efficiency level of launching. As there are various defects of manual command in the flight deck operation of carriers, the establishment of an automatic path planner for aircraft fleets is imperative. The requirements of launching, the particularities of the flight deck environment, the way of launch, and the work mode of catapult were analyzed. On this basis, a mathematical model was established which contains the constraints of maneuverability and the work mode of catapults; the ground motion and collision detection of aircraft are also taken into account. In the design of path planning algorithm, path tracking was combined with path planning, and the strategy of rolling optimization was applied to get the actual taxi path of each aircraft. Taking the Nimitz-class aircraft carrier as an example, the taxi paths of aircraft fleet launching was planned with the proposed method. This research can guarantee that the aircraft fleet complete launching missions safely with reasonable taxi paths.

Evaluating the role of capital controls and monetary policy in emerging market crises

This paper explores the interactive role of optimal monetary policy and capital controls in dealing with ‘sudden-stop’ financial crises in emerging market economies. The model features collateral constraints embedding pecuniary externalities, as well as nominal rigidities in prices and wages. We explore the role of policy commitment and macro-prudential motives in the design of optimal monetary and capital market responses to crises, under alternative exchange rate regimes. We find that policy commitment is very important under flexible exchange rates, but commitment (to the path of capital taxes) is only of minor benefit under an exchange rate peg. As regards macro-prudential policy, we find the exact opposite. Under floating exchange rates, the optimal policy has almost no macro-prudential elements. On the other hand, when authorities are constrained by an exchange rate peg, macro-prudential policy is used aggressively as part of an optimal policy framework. An important additional finding is that the direction of capital controls is different under a fixed relative to a flexible exchange rate. With flexible exchange rates, policy makers impose inflow taxes immediately at the onset of a crisis. Under pegged exchange rates, they will impose capital inflow subsidies.

Analysis of spatiotemporal trajectories for stops along taxi paths

ABSTRACTStops along taxi trajectories, such as picking up and dropping off passengers, are spatially clustered and related to certain attributes of places where stops are made. To detect the hidden knowledge regarding these places, this article examines the semantics of massive taxi stops in a large city. Each taxi trajectory is modeled as a series of sequential semantic stops labeled by street names. All the trajectories can be examined as a document corpus, from which the hidden themes of the stops are identified through Latent Dirichlet Allocation model. Conventional GIS tools are coupled with topic modeling toolkit to visualize and analyze potential information of stop topics for understanding intra-city dynamics. The effectiveness of this approach is illustrated by a case study using a large dataset of taxi trajectories including approximately 4,000 taxis in Wuhan, China.

The Optimum Quantity of Capital and Debt

In this paper we solve the dynamic optimal Ramsey taxation problem in a model with incomplete markets, where the government commits itself ex-ante to a time path of labor taxes, capital taxes and debt to maximize the discounted sum of agents’ utility starting from today. Whereas the literature has bee limited mainly to studying policies that maximize steady-state welfare only, we instead characterize the optimal policy along the full transition path. We show theoretically that in the long run the capital stock satisfies the modified golden rule. More importantly, we prove that in contrast to complete markets economies, in incomplete markets economies the long run steady-state resulting from an infinite sequence of optimal policy choices is independent of initial conditions. This result is not only of theoretical interest but moreover, enables us to compute the long-run optimum independently from the transition path such that a quantitative analysis becomes tractable. Quantitatively we find, robustly across various calibrations, that in the long run the government debt-to-GDP ratio is high, capital is taxed at a low rate and labor income at a high rate when compared to current U.S. values. Along the optimal transition to the steady state, labor taxes initially are lowered, financed through issuing more debt and taxing capital income heavily, before they are eventually increased to their steady-state level.

Analysis of aircraft ground traffic flow and gate utilisation using a hybrid dynamic gate and taxiway assignment algorithm

ABSTRACTThe rapid increase in the demand for air transportation over the last four decades has led to serious capacity problems for both the airside and landside components of major airports. The efficient management of existing airside resources seems to be the most effective and practical approach to overcome these capacity and traffic flow problems. Although integrated management of aircraft parking position assignments and ground movement planning processes are vital for the effective use of resources and for efficient operations, the current practice is that these processes are handled separately by different agents. This study proposes a hybrid dynamic system, an integrated methodology of taxi path and gate assignment using a knowledge-based decision-making approach to model effectively time-variant and realistic operational features of aircraft gate management and route planning. The model assigns the most suitable parking positions with minimum taxi time and taxi delay among a reduced solution set, satisfying pre-defined decision criteria as well as monitoring ground movements and, if necessary, reassigning new taxi paths and parking positions in real time. Both the proposed integrated methodology and the separate gate assignment and ground management operations currently in use were implemented, analysed and compared in a fast-time simulation model of Istanbul Ataturk Airport (LTBA). The hybrid dynamic assignment model provided significant improvements in taxi times, ground delays and gate utilisation.

Too Slow a Change? Deep Habits, Consumption Shifts and Transitory Tax Policy

Habits are an important cause of sluggish consumption adjustment in response to price shocks. This paper studies shifts within the consumption bundle under endogenous habit formation. I put forward a model with good-specific, or ’deep’, habits that cause persistence in good-specific consumption. In addition, at the aggregate level, habits act as a benchmark against which consumption is evaluated. I evaluate dynamic consumption choices under the realistic assumption that the consumer imperfectly internalizes the habit formation process. I compare consumption choices to the welfare-maximizing choices, and determine the path of taxes or subsidies that implements first-best consumption, both when goods are produced competitively and when they are produced by monopolists. I establish that a transition to a new consumption bundle is more likely inefficiently sluggish if the persistence effect is relatively strong. Strategic pricing behavior by monopolists leads to inefficiently rapid transitions. To explore the quantitative implications of the model I consider the introduction of a 10 percent charge on a subset of goods. I find that consumption adjusts inefficiently fast; implementing first-best adjustment requires a transitory discount of up to 60 percent of the cost increase.

AN EVALUATION OF CONSTITUTIONAL CONSTRAINTS ON CAPITAL TAXATION

This paper investigates the desirability of constitutional constraints on capital taxation in an environment without government debt and where benevolent governments have limited commitment. In our setup, governments can choose proportional capital and labor income taxes subject to the constitutional constraint but cannot commit to an actual path of taxes. First, we explore a form of constitutional constraint: a constant cap on capital tax rates. In our quantitative exercise, we show that a three percent cap on capital taxes provides the highest welfare at the worst sustainable equilibrium. However, such a cap decreases welfare at the best sustainable equilibrium (both because it constrains feasibility and because it tightens the incentive compatibility constraint). Second, we identify a form of constitutional constraint that can improve all sustainable equilibria. That constraint features a cap on capital taxes that increases with the level of capital.

Government Deficits in Large Open Economies: The Problem of Too Little Public Debt

Abstract Large and growing levels of public debt in the United States, United Kingdom, Japan and the Euro Area raise new interest in the cross-country effects of a large open economy’s deficits. The authors consider a dynamic optimising model with costly tax collection and exogenously given public spending and initial debt. They ask whether the externalities associated with an individual country’s deficits are positive or negative. They characterise the path of taxes in the Nash equilibrium where policy makers act nationalistically and compare this outcome to the global optimal outcome.

A Methodology and Modelling Technique for Taxi Path Optimization

Vehicle Routing Problem (VRP) is a typical combinatorial optimization problem. A new type of bionic algorithm-ant colony algorithm is very appropriate to solve Vehicle Routing Problem because of its positive feedback, robustness, parallel computing and collaboration features. In view of the taxi route optimization problem, this article raised the issue of the control of the taxi, by using the Geographic Information System (GIS), through the establishment of the SMS platform and reasonable taxi dispatch control center, combining ant colony algorithm to find the most nearest no-load taxi from the passenger, and giving the no-load taxi the best path to the passenger. Finally this paper use Ant Colony laboratory to give the simulation. By using this way of control, taxis can avoid the no-load problem effectively, so that the human and material resources can also achieve savings.

The Optimal Distribution of the Tax Burden over the Business Cycle

This paper analyses optimal income taxes over the business cycle under a balanced-budget restriction, for low, middle and high income households. A model incorporating capital-skill complementarity in production and differential access to capital and labour markets is developed to capture the cyclical characteristics of the US economy, as well as the empirical observations on wage (skill premium) and wealth inequality. We find that the tax rate for high income agents is optimally the least volatile and the tax rate for low income agents the least counter-cyclical. In contrast, the path of optimal taxes for the middle income group is found to be very volatile and counter-cyclical. We further find that the optimal response to output-enhancing capital equipment technology and spending cuts is to increase the progressivity of income taxes. Finally, in response to positive TFP shocks, taxation becomes more progressive after about two years.