Effectiveness of roadside crash countermeasures

In this article, an "intelligent" airline seat inventory control system is developed. Applications of the system are considered for both nonstop flights and flights with stopovers. The system developed is able to recognize a situation characterized by the number of reservations made by individual passenger classes and the number of canceled reservations at a certain moment in time before departure. The system can also make the appropriate decision without knowing the functional relationships in effect between individual variables. As in other intelligent systems, the "intelligent" airline seat inventory control system proposed here is able to generalize, adapt and learn based on new knowledge and new information. The "intelligent" airline seat inventory control system is based on fuzzy logic. The system makes on-line decisions as to whether to accept or reject any passenger request using established fuzzy rules. The "intelligent" system's results are compared with those of the EMSR model for nonstop flights. The results for flights with stopovers are compared with those obtained using integer programming. The final conclusions are very promising.     

The planning of aircraft routes and flight frequencies in an airline network operations

This research is aimed at developing a model that maximizes system profit when determining the aircraft routes and flight frequencies in a network. The model employs network flow techniques to effectively collect or deliver passenger flows from all origins to all destinations using non‐stop and multi‐stop flights in multi‐fleet operations. The model was formulated as a multi‐commodity network flow problem. A Lagrangian‐based algorithm was developed to solve the problem. To test the model in practice, a case study is presented.     

Analysis of performance and equity in ground delay programs

The discrepancy between the projected demand for arrival slots at an airport and the projected available arrival slots on a given day is resolved by the Ground Delay Program (GDP). The current GDP rationing rule, Ration-by-Schedule, allocates the available arrival slots at the affected airport by scheduled arrival time of the flights with some adjustments to balance the equity between airlines. This rule does not take into account passenger flow and fuel flow performance in the rationing assignment tradeoff.This paper examines the trade-off between passenger delays and excess surface fuel burn as well as airline equity and passenger equity in GDP slot allocation using different rationing rules. A GDP Rationing Rule Simulator (GDP-RRS) is developed to calculate performance and equity metrics for all stakeholders using six alternate rules. The results show that there is a trade-off between GDP performance and GDP equity. Ration-by-Passengers (a rule which maximizes the passenger throughput) decreased total passenger delay by 22% and decreased total excess fuel burn by 57% with no change in total flight delay compared to the traditional Ration-by-Schedule. However, when the airline and passenger equity are primary concerns, the Ration-by-Schedule is preferred.     

Multi‐objective airport gate assignment problem in planning and operations

We consider the assignment of gates to arriving and departing flights at a large hub airport. This problem is highly complex even in planning stage when all flight arrivals and departures are assumed to be known precisely in advance. There are various considerations that are involved while assigning gates to incoming and outgoing flights (such a flight pair for the same aircraft is called a turn) at an airport. Different gates have restrictions, such as adjacency, last‐in first‐out gates and towing requirements, which are known from the structure and layout of the airport. Some of the cost components in the objective function of the basic assignment model include notional penalty for not being able to assign a gate to an aircraft, penalty for the cost of towing an aircraft with a long layover, and penalty for not assigning preferred gates to certain turns. One of the major contributions of this paper is to provide mathematical model for all these complex constraints that are observed at a real airport. Further, we study the problem in both planning and operations modes simultaneously, and such an attempt is, perhaps, unique and unprecedented. For planning mode, we sequentially introduce new additional objectives to our gate assignment problem that have not been studied in the literature so far—(i) maximization of passenger connection revenues, (ii) minimization of zone usage costs, and (iii) maximization of gate plan robustness—and include them to the model along with the relevant constraints. For operations mode, the main objectives studied in this paper are recovery of schedule by minimizing schedule variations and maintaining feasibility by minimal retiming in the event of major disruptions. Additionally, the operations mode models must have very, very short run times of the order of a few seconds. These models are then applied to a functional airline at one of its most congested hubs. Implementation is carried out using Optimization Programming Language, and computational results for actual data sets are reported. For the planning mode, analyst perception of weights for the different objectives in the multi‐objective model is used wherever actual dollar value of the objective coefficient is not available. The results are also reported for large, reasonable changes in objective function coefficients. For the operations mode, flight delays are simulated, and the performance of the model is studied. The final results indicate that it is possible to apply this model to even large real‐life problems instances to optimality within short run times with clever formulation of conventional continuous time assignment model. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic stochastic transit assignment with explicit seat allocation model

This paper proposes a stochastic dynamic transit assignment model with an explicit seat allocation process. The model is applicable to a general transit network. A seat allocation model is proposed to estimate the probability of a passenger waiting at a station or on-board to get a seat. The explicit seating model allows a better differentiation of in-vehicle discomfort experienced by sitting and standing passengers. The paper proposes simulation procedures for calculating the sitting probability of each type of passengers. A heuristic solution algorithm for finding an equilibrium solution of the proposed model is developed and tested. The numerical tests show significant influences of the seat allocation model on equilibrium departure time and route choices of passengers. The proposed model is also applied to evaluate the effects of an advanced public transport information system (APTIS) on travellers’ decision-making.     

Fuel burn and environmental implications of airline hub networks

Hubs act as switching points for interactions and so are places through which flows are concentrated. This research uses the interactions between a system of cities as an experimental context for understanding selected environmental costs and benefits of concentrated flow. Whether hub based networks create additional environmental costs has been debated in the literature. In this paper, fuel burn is used as an indicator of environmental cost. The essential ideas are: (1) to examine fuel costs associated with larger aircraft; (2) to determine implications of higher loads on dense routes; and (3) to model the resulting implications for hub and gateway location. Variants of these questions apply to passenger and freight flows, and the paper will initially concentrate on passenger models.The paper shows that by modeling fuel burn and introducing a fixed charge (like a set up cost), a multiple allocation hub and spoke model can be adjusted to direct more or less flow onto the inter-facility connector. In other words, usage of multiple connections and direct links can be controlled and modeled as a function of the fixed charge. The resulting networks are characterized by quite different levels of passenger miles, aggregate fuel burn and fixed charges. The preferred network in terms of minimal fuel burn is found by subtracting the fixed set up charge, thereby focusing attention on the modeled fuel burn. The lowest cost set up is a network with a high degree of connectivity, and a pure single assignment hub network has the highest fuel cost (as a result of larger passenger miles needed by connecting paths). The data also allow a tabulation of total passenger miles, which, not surprisingly, track very closely with the fuel burn. In an interesting application of the ideas, it is shown that a fuel efficient network may require a large number of smaller regional jets, and in the interests of avoiding noise and congestion from so many extra airport operations, the carriers may choose to substitute a smaller number of larger planes, thereby slightly increasing fuel needs. This paper also provides a key ingredient for models of an international network where it is impossible to serve many long distance market pairs without consolidation.     

A framework for the assessment of collaborative en route resource allocation strategies

Airspace Flow Programs (AFPs) assign ground delays to flights in order to limit flow through capacity constrained airspace regions. AFPs have been successful in controlling traffic with reasonable delays, but a new program called the Combined Trajectory Options Program, or CTOP, is being explored to further accommodate projected increases in traffic demand. In CTOP, centrally managed rerouting and user preference inputs are also incorporated into initial en route resource allocations. We investigate four alternative versions of resource allocation within CTOP in this research, under differing assumptions about the degree of random variability in airline flight assignment costs when measured against a simple model based upon the flight specific, but otherwise fixed, ratio of airborne flight time and ground delay unit cost. Two en route resource allocation schemes are based on ordered assignments that are similar to those used currently, and the other two are system-optimal assignment schemes. One of these system-optimal schemes is based on complete preference information, which is ideal but not realistic, and the other is based on partial information that may be feasible to implement but yields less efficient assignments. The main contribution of this research is a methodological framework to evaluate and compare these alternative en route resource allocation schemes, under varying assumptions about the information traffic managers have been provided about the flight operators’ route preferences. The framework allows us to evaluate these various schemes under differing assumptions about how well the traffic managers’ flight cost model captures flight costs. A numerical example demonstrates that a sequential resource allocation scheme – where flights are assigned resources in the order in which preference information is submitted – can be more efficient than a scheme that offers a cost minimizing allocation based on less complete preference information, and may at the same time be perceived as equitable. We also find that assigning resources in the order flights are scheduled results in less efficient allocations, but more equitable ones.     

A multiobjective planning model for intercity train seat allocation

This paper presents a multiobjective planning model for generating optimal train seat allocation plans on an intercity rail line serving passengers with many‐to‐many origin‐destination pairs. Two planning objectives of the model are to maximise the operator's total passenger revenue and to minimise the passenger's total discomfort level. For a given set of travel demand, train capacity, and train stop‐schedules, the model is solved by fuzzy mathematical programming to generate a best‐compromise train seat allocation plan. The plan determines how many reserved and non‐reserved seats are to be allocated at each origin station for all subsequent destination stations on each train run operated within a specified operating period. An empirical study on the to‐be‐built Taiwan's high‐speed rail system is conducted to demonstrate the effectiveness of the model. The model can be used for any setting of travel demand and stop‐schedules with various train seating capacities.     

A math-heuristic algorithm for the integrated air service recovery

A sophisticated flight schedule might be easily disrupted due to adverse weather, aircraft mechanical failures, crew absences, etc. Airlines incur huge costs stemming from such flight schedule disruptions in addition to the serious inconveniences experienced by passengers. Therefore, an efficient recovery solution that simultaneously decreases an airline's recovery cost while simultaneously mitigating passenger dissatisfaction is of great importance to the airline industry. In this paper, we study the integrated airline service recovery problem in which the aircraft and passenger schedule recovery problems are simultaneously addressed, with the objective of minimizing aircraft recovery and operating costs, passenger itinerary delay cost, and passenger itinerary cancellation cost.Recognizing the inherent difficulty in modeling the integrated airline service recovery problem within a single formulation (due to its huge solution space and quick response requirement), we propose a three-stage sequential math-heuristic framework to efficiently solve this problem, wherein the flight schedules and aircraft rotations are recovered in the first stage, Then, a flight rescheduling problem and passenger schedule recovery problems are iteratively solved in the next two stages. Time-space network flow representations, along with mixed-integer programming formulations, and algorithms that take advantages of the underlying problem structures, are proposed for each of three stages. This algorithm was tested on realistic data provided by the ROADEF 2009 challenge and the computational results reveal that our algorithm generated the best solution in nearly 72% of the test instances, and a near-optimal solution was achieved in the remaining instances within an acceptable timeframe. Furthermore, we also ran additional computational runs to explore the underlying characteristics of the proposed algorithm, and the recorded insights can serve as a useful guide during practical implementations of this algorithm.     

A decision support framework for handling schedule perturbation

Perturbations of flight schedules may occur everyday. Poor scheduling of flights may result in a substantial loss of profit and decreased levels of service for air carriers. This research aims at developing a framework to help carriers in handling schedule perturbations caused by the breakdown of aircraft. The framework is based on a basic schedule perturbation model constructed as a dynamic network from which several perturbed network models are developed for scheduling following incidents. These network models are formulated as pure network flow problems or network flow problems with side constraints. The former are solved using the network simplex method while the latter are solved using Lagrangian relaxation with subgradient methods. To show how to apply the framework in the real world, a case study focusing on the operations of a major Taiwan air carrier in East Asia is presented.     

On seat capacity in traffic assignment to a transit network

Seating or standing make distinct on‐board states to a transit rider, yielding distinct discomfort costs, with potential influence on the passenger route choice onto the transit network. The paper provides a transit assignment model that captures the seating capacity and its occupancy along any transit route. The main assumptions pertain to: the seat capacity by service route, selfish user behaviour, a seat allocation process with priority rules among the riders, according to their prior state either on‐board or at boarding. To each transit leg from access to egress station is associated a set of ‘service modes’, among which the riders are assigned in a probabilistic way, conditionally on their priority status and the ratio between the available capacity and the flow of them. Thus the leg cost is a random variable, with mean value to be included in the trip disutility. Computationally efficient algorithms are provided for, respectively, loading the leg flows and evaluating the leg costs along a transit line. At the network level, a hyperpath formulation is provided for supply‐demand equilibrium, together with a property of existence and an method of successive averages equilibration algorithm. It is shown that multiple equilibria may arise. Copyright © 2010 John Wiley & Sons, Ltd.     

航班快速恢复建模与仿真研究

随着民用航空的发展与竞争,航班延误不仅影响航空飞行的安全与正常,更与航空公司的运营效率、运营成本及乘客利益息息相关。针对某一恶劣天气影响,对某公司受影响航班进行重新调配,考虑到航班的备降、盘旋等待、延误、取消等多种状态,以总成本最小为目标函数,建立航班快速恢复模型,通过MATLAB运用遗传算法设计航班恢复算法进行求解,得出最经济的航班恢复方案。     

Evaluation and implications of environmental charges on commercial flights

Environmental charges are one of the economic instruments for controlling externalities. Their application to commercial flights has become a preferred method of encouraging the sustainable development of the air transport industry. Two kinds of externalities, aircraft noise and engine emissions, both generating profound impacts on human beings and on the environment, are considered here. The hedonic price method is applied to calculate the social cost of aircraft noise during the landing and take-off stages of the flight. The marginal impact of each flight with specific aircraft/engine combinations is derived for the allocation of aggregate noise social costs. In contrast, the dose - response method is applied to estimate the social cost of each engine exhaust pollutant during different flight modes. The combination of aircraft noise and engine emissions social costs is then evaluated on the basis of several environmental charge mechanism scenarios, using Amsterdam Airport Schiphol as a case study. It is shown that the current noise or engine emissions related charges at airports are lower than the actual social costs of their respective externalities. The implications of charge mechanism scenarios are subsequently discussed and evaluated in terms of their impacts on airline costs, airfares and passenger demand.     

A heuristic model for frequency planning and aircraft routing in small size airlines

The flight schedule of an airline is the primary factor in finding the most effective and efficient deployment of the airline's resources. The flight schedule process aims at finding a set of routes with associated aircraft type, frequency of service and times of departures and arrivals in order to satisfy a specific objective such as profit maximization. In this paper, we develop a two‐phase heuristic model for airline frequency planning and aircraft routing for small size airlines. The first phase develops a frequency plan using an economic equilibrium model between passenger demand for flying a particular route and aircraft operating characteristics. The second phase uses a time‐of‐day model to develop an assignment algorithm for aircraft routing.     

The multi-objective railway timetable rescheduling problem

Unexpected disruptions occur for many reasons in railway networks and cause delays, cancelations, and, eventually, passenger inconvenience. This research focuses on the railway timetable rescheduling problem from a macroscopic point of view in case of large disruptions. The originality of our approach is to integrate three objectives to generate a disposition timetable: the passenger satisfaction, the operational costs and the deviation from the undisrupted timetable. We formulate the problem as an Integer Linear Program that optimizes the first objective and includes $\epsilon$-constraints for the two other ones. By solving the problem for different values of $\epsilon$, the three-dimensional Pareto frontier can be explored to understand the trade-offs among the three objectives. The model includes measures such as canceling, delaying or rerouting the trains of the undisrupted timetable, as well as scheduling emergency trains. Furthermore, passenger flows are adapted dynamically to the new timetable. Computational experiments are performed on a realistic case study based on a heavily used part of the Dutch railway network. The model is able to find optimal solutions in reasonable computational times. The results provide evidence that adopting a demand-oriented approach for the management of disruptions not only is possible, but may lead to significant improvement in passenger satisfaction, associated with a low operational cost of the disposition timetable.     

Comparing the impact of future airline network change on emissions in India and the United States

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.     

Strategic de-confliction in the presence of a large number of 4D trajectories using a causal modeling approach

This paper presents a strategic de-confliction algorithm based on causal modeling developed under the STREAM project and launched under the umbrella of the Single European Sky ATM Research (SESAR) Program. The basic underlying concept makes use of the enriched information included in the Shared Business Trajectories (SBTs) of the flights prior to takeoff (or in the Reference Business Trajectories (RBTs) if the flight is airborne) to allocate conflict-free trajectories in a traffic planning phase that should lead to an actual conflict-free scenario in the flight execution phase in the absence of flight and/or network uncertainties. The proposed approach could decrease the workload of the air traffic controllers, thus improving the Air Traffic Management (ATM) capacity while meeting the maximum possible expectations of the Airspace Users’ requirements in terms of horizontal flight efficiency. The main modules of the implemented system are also presented in this paper; these modules are designed to enable the processing of thousands of trajectories within a few seconds or minutes and encompass a global network scope with a planning horizon of approximately 2–3 h. The causal model applied for network conflict resolution and flight routing allocation is analyzed to demonstrate how the emergent dynamics (i.e., domino effects) of local trajectory amendments can be efficiently explored to identify conflict-free Pareto-efficient network scenarios. Various performance indicators can be taken into account in the multi-criteria optimization process, thus offering to the network manager a flexible tool for fostering a collaborative planning process.     

Assessment of stratospheric fuel burn by civil commercial aviation

When jetliners fly in the stratosphere, their emissions tend to be longer-lived and therefore have greater environmental impact. Since the altitude of the tropopause is not consistent and can be as low as 23,000 ft., cruising flights may have a great chance to fly into the stratosphere. In this paper, we present a simple and rapid method to estimate the extent of US commercial passenger and cargo flight that currently occurs in the stratosphere, based on publicly available historical data from 2008 to 2012. We model the vertical profile of a flight and compare it with the height of the tropopause along its route. Our analysis covers 78% of the total travelled distance reported by the United States Bureau of Transportation Statistics, and shows that these flights burnt ∼11 million tons of fuel annually, or ∼31% of cruise fuel, in the stratosphere between 2008 and 2012. Our results also show that the chance of flying into stratosphere varies by area, but flights within the contiguous United States tend to stay below the stratosphere. Moreover, the stratosphere fuel burn of Asia-US flights may be significantly reduced by taking jet stream routes.     

Heuristic approach to the airline schedule disturbances problem

Abstract

When disturbances make it impossible to realise the planned flight schedule, the dispatcher at the airline operational centre defines a new flight schedule based on airline policy, in order to reduce the negative effects of these perturbations. Depending on airline policy, when designing the new flight schedule, the dispatcher delays or cancels some flights and reassigns some flights to available aircraft. In this paper, a decision support system (DSS) for solving the airline schedule disturbances problem is developed aiming to assist decision makers in handling disturbances in real-time. The system is based on a heuristic algorithm, which generates a list of different feasible schedules ordered according to the value of an objective function. The dispatcher can thus select and implement one of them. In this paper, the possibilities of DSS are illustrated by real numerical examples that concern JAT Airways' flight schedule disturbances.     

Simulation-based assessment methodology to improve ground service operations at a hub airport

ABSTRACT

Airport terminals are dynamic environments and security/passport services generally constitute costly bottlenecks in terminals. Increases in the number of airline passengers compels airport terminals to provide more efficient services to its customers under space and resource limitations. This study examines the level of service of passenger processes at Istanbul Atatürk Airport by constructing a comprehensive simulation model. It focuses mainly on passport control services and passenger transfer security services because of the airport's hub status and the strategy of Turkish Airlines. The increasing number of transfer passengers may cause disruptions in departure flight schedules due to slow passenger processes. After validating the model, we investigate the consequences of three main alternative solutions, including 17 sub-scenarios, to capture target quality levels. Finally, we provide the results for each scenario to investigate the optimum allocation of resources to terminal operations.