Knowledge based decision support in airport terminal design

The state of the art in airport terminal design has essentially remained unchanged since the 1970s, relying on the use of detailed simulation together with empirical and statistical formulae for sizing the terminal. Air transport has altered considerably since then, with increased use of air travel for both business and leisure, together with the increased use of ‘hub’ terminals in which the terminal acts as an interchange stop on a journey involving several flights. The use of simulation involves a detailed analysis of the terminal design under one set of conditions. To change the design or operating conditions involves a complete resimulation using the new design parameters which is time consuming and computationally expensive.

By using a knowledge based approach, a system can be provided which has the flexibility and speed required to explore the consequences of implementing design decisions in a variety of conditions, together with the ability to use and alter facility sizing methodologies to reflect current and future design guidelines.     

Development and demonstration of an integrated decision support system for airport performance analysis

Airport decision makers are frequently facing complex decision-making problems related to airport planning, design, and operations. The airport decision-making process is further perplexed by the large number of stakeholders having different, and sometimes conflicting, objectives regarding the assessment of the airport performance. Despite the rich experience in both models and tools for airport performance analysis, existing models and tools address only fragmented parts of the airport decision-making process. At present, airport stakeholders lack models and tools able to provide an integrated view of the total airport processes and analyze the tradeoffs between the various measures of airport effectiveness. The objective of this paper is threefold: (i) to introduce the concept of total airport performance analysis, (ii) to describe the development of a Decision Support System capable of performing integrated airport analysis, and (iii) to demonstrate the capabilities of this Decision Support System by analyzing a real-world airport planning case of the Athens International Airport.     

A queueing system for airport buses

The use of remote terminals to relieve airport congestion leads rather naturally to queueing systems with batch arrivals occuring at fixed time intervals to a multiple server service facility. In this paper arrival point steady-state solutions to the D^[X]/M/c queueing system are presented. Solution of the steady-state equation WP = W and Neuts' method of solving the GI^[X]/M/c system are used to obtain steady-state system size densities. Results obtained using the two methods are compared with each other as well as with simulation results.     

Parameters of moving sidewalks for airport terminal pier fingers

A moving sidewalk system installed at an airport pier finger is analyzed. The optimal length of the moving sidewalk and the optimal spacing between the access points which minimize the total cost of the system are obtained using methods of calculus, for a number of cases based on the different proportions of arriving, departing and transferring passengers and for two different types of moving sidewalks: elevated, at‐grade.

The optimal length of the moving sidewalk is shown to be linearly related to the length of the concourse, and to the total passenger demand. The effect due to preticketed transferees is insignificant.

The optimal spacing between access points is shown to be proportional to the square‐root of either the cost of an access escalator or the cost of inconvenience to a passenger due to an intermediate gap, depending on the moving sidewalk system under consideration. It also changes with the percentage of preticketed transferees.     

A decision support system for airport strategic planning

This paper describes an integrated set of models for the estimation of the capacity of an airfield and the associated delays. The aim is to develop a decision support tool suitable for airport planning at the strategic level. Thus, the emphasis is on obtaining reliable approximations to the quantities of interest quickly and with a limited set of inputs. The models account for the dynamic characteristics of airfield capacity and demand, as well as for some stochastic aspects of airfield operations. They are sensitive to airfield geometry, the operational characteristics of the airfield and of the local air traffic control system, and the characteristics of the local air traffic demand for airport access and services. Through its integrated structure, the decision support tool can account for interactions among operations at different parts of the airfield.     

A decision support system for total airport operations management and planning

The airport planning and decision making process exhibits various trade‐offs and complications due to the large number of stakeholders having different, and sometimes conflicting, objectives regarding the assessment of airport performance. As a result, the airport performance assessment necessitates the use of advanced modelling capabilities and decision support systems or tools in order to capture the multifaceted aspects, interests and measures of airport performance like capacity, delays, safety, security, noise and cost‐effectiveness. Presently, airport decision makers lack decision support tools able to provide an integrated view of total airport (both airside and landside) operations and analyse at a reasonable effort and decision‐oriented manner the various trade‐offs involved among different airport performance measures. The objective of this paper is twofold: (i) to describe the decision‐oriented modelling framework and development process of a decision support system for total airport operations management and planning, and (ii) to demonstrate the decision support capabilities and basic modelling functionalities of the proposed system. Copyright © 2010 John Wiley & Sons, Ltd.     

A system dynamics approach to land use / transportation system performance modeling Part II: Application

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model system consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is also examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited to some extent due to data availability, the results clearly indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling     

A system dynamics approach to land use/transportation system performance modeling Part I: Methodology

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited due to data availability, the results indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling.     

A simulation framework for evaluating airport gate assignments

There are many factors that affect gate assignments in an airport's operations. These factors include static gate assignments, stochastic flight delays and real-time gate assignments. Most research on gate assignments in the past has laid stress on improving the performance of static gate assignments. None has analyzed the interrelationship between static gate assignments and real-time gate assignments as affected by the stochastic flight delays that occur in real operations. In addition, none has designed flexible buffer times for static gate assignments to effectively absorb stochastic delays in real-time gate assignments. This research proposes a simulation framework, that is not only able to analyze the effects of stochastic flight delays on static gate assignments, but can also evaluate flexible buffer times and real-time gate assignment rules. Finally, a simulation based on Chiang Kai-Shek airport operations is performed to evaluate the simulation framework.     

A new era for airport regulators through capacity investments

Private and public airports’ optimal actions may not coincide. While private airports usually pursue profit maximization, publicly owned airports look for maximum social welfare. Thus, the prices charged by private airports may differ from the socially optimal charges and public intervention may be needed. In this paper, we analyze airport charges when an increase in frequency produces positive or negative externalities and carriers have market power. We use the methodology of game theory to show that there may exist a level of capacity for which private and social objectives coincide, so no price regulation is needed. Thus, the usual role of regulators and planners could be modified in order to decide the appropriate capacity investments for which airport regulation is no longer necessary.     

A flexible terminal/mobile lounge system for expanding the capacity of existing airports

One of the great dilemmas facing major airports is the problem of capacity and seasonal surges of activity. This paper suggests a system of small, inexpensive Airport Terminal Modules, which together with a new type of Mobile Lounge, could make available a considerable degree of flexibility. The ATM's are designed to allow maximum variations of aircraft type and passenger load as well as high ground utilization. This concept would allow major airports to be extended with a minimum of inconvenience as demand becomes apparent, thereby allowing financial expenditure to be carefully controlled and more evenly spread.     

A multicriteria decision support methodology for evaluating airport expansion plans

Rational decision-making requires an assessment of advantages and disadvantages of choice possibilities, including non-market effects (such as externalities). This also applies to strategic decision-making in the transport sector (including aviation). In the past decades various decision support and evaluation methods have been developed in which a market evaluation played a prominent role. The intrinsic limitations of these approaches were also increasingly recognised. Gradually, a variety of adjusted multidimensional methods has been developed over the past years to complement conventional cost–benefit analysis (CBA). These methods aim to investigate and evaluate all relevant impacts of a choice possibility (e.g., project, plan, or programme) on the basis of a multitude of important policy criteria (so-called multicriteria methods). They have a particular relevance in case of non-priced or qualitative effects. There is a clear need for a systematic and polyvalent multicriteria approach to many actual planning issues, such as land use or transportation. This paper offers a new evaluation framework based on a blend of three types of approaches, viz. Regime Analysis, the Saaty method and the Flag Model. All these methods have been developed separately in the past; the paper makes an effort to offer a cohesive framework, which can be used for the e valuation of spatial-economic and environmental-economic policy issues. This new tool is tested by means of a case study on conflicting plans (and policy views) for airport expansion options in the Maastricht area in the southern part of The Netherlands.     

Optimal assignment for check-in counters based on passenger arrival behaviour at an airport

Establishing how to utilize check-in counters at airport passenger terminals efficiently is a major concern facing airport operators and airlines. Inadequate terminal capacity and the inefficient utilization of facilities such as check-in counters are major factors causing congestion and delays at airport passenger terminals. However, such delays and congestion can be reduced by increasing the efficiency of check-in counter operations, based on an understanding of passengers' airport access behaviour. This paper presents an assignment model for check-in counter operations, based on passengers' airport arrival patterns. In setting up the model, passenger surveys are used to determine when passengers arrive at the airport terminals relative to their flight departure times. The model then uses passenger arrival distribution patterns to calculate the most appropriate number of check-in counters and the duration of time that each counter should be operated. This assignment model has been applied at the Seoul Gimpo International Airport in Korea. The model provides not only a practical system for the efficient operations of time-to-time check-in counter assignments, but also a valuable means of developing effective longer-term solutions to the problem of passenger terminal congestion and delays. It also offers airlines a means of operating check-in counters with greater cost effectiveness, thus leading to enhanced customer service.     

A multi-criteria evaluation of solutions and alternatives for matching capacity to demand in an airport system: the case of London

This paper applies multi-criteria decision-making (MCDM) methods to the evaluation of solutions and alternatives for matching airport system airside (runway) capacity to demand. For such a purpose, ‘building a new runway’ is considered as the solution and candidate airports of the system as alternatives for implementing the solution. The alternative airports are characterized by their physical/spatial, operational, economic, environmental, and social performance represented by corresponding indicator systems which, after being defined and estimated under given operating scenarios, are used as evaluation attributes/criteria by the selected MCDM methods. Two MCDM methods – Simple Additive Weighting and Technique for Order of Preference by Similarity to Ideal Solution – are applied to the case of the London airport system to rank and select the preferred alternative from three candidate airports – Heathrow, Gatwick, and Stansted – for where a new runway could be built.     

Application of path analysis methodology to transit system maintenance performance

This paper develops a conceptual framework for bus maintenance based on path analysis and applies it to forty-eight bus transit systems. The application determines the total, direct, and indirect effects of the variables identified as having significant causal links with maintenance cost per mile. These variables are identified using the stepwise regression method. The findings are that the wage rate and fleet size increase maintenance cost directly and indirectly. In terms of the standardized regression coefficients, fleet size has been found to be the most important factor affecting maintenance cost per mile, followed by the proportion of articulated buses, the wage rate and local subsidy in that order. The proportion of articulated buses has been found to reduce maintenance cost per mile directly and to increase it indirectly. The indirect path coefficient of the proportion of articulated buses is 0.1794 whereas the direct path coefficient is –0.351. Similarly local subsidy as a proportion of revenue increases maintenance cost per mile directly and reduces it indirectly. The corresponding path coefficients for the direct and indirect effects of local subsidy are 0.2553 and –0.1073. In addition population density and the peak-base ratio are positively and significantly associated with miles between roadcalls. The implications of these findings are briefly examined in this paper. Because the path analysis methodology allows the direct and indirect effects of a causal variable to be determined, it is recommended for policy analysis.     

A system dynamics modeling for urban air pollution: A case study of Tehran,Iran

Development of strategies to control urban air pollution is a complex process involving a wide range of sciences. In this study a system dynamics model is proposed in order to estimate the behavior of parameters affecting air pollution in Tehran. The proposed model includes two subsystems: (1) urban transportation, (2) air polluting industries. In this paper, several policies are proposed to mitigate air pollution. The proposed model is simulated under several scenarios using historical data of transportation and industrial sectors in Tehran. Policies are categorized as: (1) road construction, (2) technology improvement in fuel and automotive industries, (3) traffic control plans, (4) development of public transportation infrastructures. The results show effectiveness of the proposed policies. In this case, technology improvement in fuel and automotive industries and development of public transportation infrastructures are more effective policies in order to reduce air pollution.     

The vehicle emissions and performance monitoring system: analysis of tailpipe emissions and vehicle performance

This paper describes tailpipe emission results generated by the Vehicle Performance and Emissions Monitoring system (VPEMS). VPEMS integrates on‐board emissions and vehicle/driver performance measurements with positioning and communications technologies, to transmit a coherent spatio‐temporally referenced dataset to a central base station in near real time. These results focus on relationships between tailpipe emissions of CO, CO₂, NO_x and speed and acceleration. Emissions produced by different driving modes are also presented. Results are generally as one would expect, showing variation between vehicle speed, vehicle acceleration and emissions. Data is based upon a test run in central London on urban streets with speeds not exceeding about 65 km/h. The results presented demonstrate the capabilities of the system. Various issues remain with regard to validation of the data and expansion of the system capability to obtain additional vehicle performance data.     

A model and a solution algorithm for airport common use check-in counter assignments

In this research we develop an integer programming model to assist airport authorities to assign common use check-in counters. Due to the many complicated factors that have to be considered in such a model, the problem size is expected to be huge, making its solution difficult and therefore not applicable to the real world. Therefore, we develop a heuristic method, containing three heuristic models, to solve the model. These heuristic models are formulated as zero–one integer programs that can be solved using the simplex method and the branch-and-bound technique. To test how well the proposed models and the solution method may be applied in the real world, we perform a case study concerning the operations of a major airport in Taiwan.     

Simulation model performance analysis of a multiple station shared vehicle system

As an alternative transportation paradigm, shared vehicle systems have become increasingly popular in recent years. Shared vehicle systems typically consist of a fleet of vehicles that are used several times each day by different users. One of the main advantages of shared vehicle systems is that they reduce the number of vehicles required to meet total travel demand. An added energy/emissions benefit comes when low-polluting (e.g., electric) vehicles are used in the system. In order to evaluate operational issues such as vehicle availability, vehicle distribution, and energy management, a unique shared vehicle system computer simulation model has been developed. As an initial case study, the model was applied to a resort community in Southern California. The simulation model has a number of input parameters that allow for the evaluation of numerous scenarios. Several measures of effectiveness have been determined and are calculated to characterize the overall system performance. For the case study, it was found that the most effective number of vehicles (in terms of satisfying customer wait time) is in the range of 3–6 vehicles per 100 trips in a 24 h day. On the other hand, if the number of relocations also is to be minimized, there should be approximately 18–24 vehicles per 100 trips. Various inputs to the model were varied to see the overall system response. The model shows that the shared vehicle system is most sensitive to the vehicle-to-trip ratio, the relocation algorithm used, and the charging scheme employed when electric vehicles are used. A preliminary cost analysis was also performed, showing that such a system can be very competitive with present transportation systems (e.g., rental cars, taxies, etc.).     

Performance indicator analysis: A management tool for the improvement of bus transit operation in Bangkok

This paper intends to demonstrate that the performance indicator analysis technique can be successfully used as a diagnostic tool to identify operational inefficiency and ineffectiveness at the route level of transit operation. The technique has been applied on 14 bus routes of Bangkok Mass Transit Authority to reveal the inter-route differences in operational efficiency and effectiveness. Twenty performance indicators relating to costs of services, fuel consumption, staff ratio, crew productivity, fleet utilization, service output per bus, daily revenues, etc., were selected to represent the resource efficiency, resource effectiveness and service effectiveness of the bus system. Results of the analyses revealed that considerable variations existed across the routes against many of these 20 selected indicators. These included variations in terms of labor and capacity utilization, maintenance expenditure, etc., many of which can be improved through suitable managerial measures. Based on these findings, specific recommendations have been made for improvement in the deficient areas that are considered to be within the operator domain. These indicators also provide a basis for comparison over time, with other operators and standards. A ranking scale was also developed to determine the over all attractiveness of the routes.