Airport Taxi Research Articles

ANALYZING IMPACT FACTORS OF AIRPORT TAXIING DELAY BASED ON ADS-B DATA

Abstract. Identifying the factors that cause taxiing delay on airports is a prerequisite for optimizing aircraft taxiing schemes, and helps improve the efficiency of taxiing system. Few of current studies had quantified the potential influencing factors and further investigated their intrinsic relationship. In view of these problems, this paper uses ADS-B data to calculate taxiing delay time by restoring taxiing route and identifying key status points, and further analyzes the impact factors of airport taxiing delay by investigating the relationship between delay time and environmental data such as weather, wind, visibility etc. The case study in Guangzhou Baiyun Airport validates the effectiveness of the proposed method.

Spatial welfare effects of shared taxi operating policies for first mile airport access

Abstract With increasing availability of alternative mobility options for first/last mile, it is necessary to better understand how shared taxis are impacting airport access demand and consumer surplus. However, no study has been conducted to evaluate the welfare effects of the range of shared taxi matching and fare allocation policies for airport access. Using several data sources primarily from Port Authority of NY and NJ and The Taxi and Limousine Commission, a mode choice model is estimated for access to John F. Kennedy International Airport in New York City. The baseline model and data show that passengers have a value of time of $101 per hour, consistent with Harvey’s study from 1986. Airport taxi travelers are also elastic to cost in a similar manner to public transit. The model is used to evaluate two policies: a first (we call this wait-share policy) where taxis can offer shared rides for two passengers from the same zip code, incorporating an endogenous expected wait time variable; and a second (we call this space-share policy) where taxis match randomly arriving passengers from any zip codes in the city. These two policies reflect extreme ends of a spectrum of policies between waiting and detouring. Findings suggest that having a shared taxi option benefit passengers in NYC going to JFK airport by at least 10% increase in consumer surplus. However, the increase in taxi ridership comes at a cost to transit ridership. Furthermore, the population in NYC that benefits most is highly dependent on the type of shared taxi policy. A wait-share policy benefits passengers from the dense parts of Manhattan most, while a space-share policy distributes the benefits more to other boroughs. These insights can help policymakers set regulations in providing first/last mile ride-sharing taxi options in different cities around the world.

Methods for determining unimpeded aircraft taxiing time and evaluating airport taxiing performance

The objective of this study is to improve the methods of determining unimpeded (nominal) taxiing time, which is the reference time used for estimating taxiing delay, a widely accepted performance indicator of airport surface movement. After reviewing existing methods used widely by different air navigation service providers (ANSP), new methods relying on computer software and statistical tools, and econometrics regression models are proposed. Regression models are highly recommended because they require less detailed data and can serve the needs of general performance analysis of airport surface operations. The proposed econometrics model outperforms existing ones by introducing more explanatory variables, especially taking aircraft passing and over-passing into the considering of queue length calculation and including runway configuration, ground delay program, and weather factors. The length of the aircraft queue in the taxiway system and the interaction between queues are major contributors to long taxi-out times. The proposed method provides a consistent and more accurate method of calculating taxiing delay and it can be used for ATM-related performance analysis and international comparison.

Safety Control Management at Airport Taxiing to Take-Off Procedure

Air traffic control (ATC) system is a safety critical system because its failure may result into loss of life, considerable financial and environmental damages. Modelling safe and efficient ATC system is an open research problem and has become a challenging task due to its complexity and ever increasing traffic at airports. It is reported in the literature that a number of collisions occurred at airports surface are three time larger than the collisions in the airspace. The delays at airport surface require effective safety and guidance protocols to control traffic at the airport. In this paper, formal procedure of managing air traffic from taxiing to take-off is provided using graph theory and Z notation. After definition of airport surface by the graph structure in terms of nodes and edges, formal specification of taxiways, aircrafts and runways is provided in static part of the model. The state space analysis is provided by describing optimal paths in dynamic model expediting the departure procedure. The safety properties are described in terms of invariants over the data types carrying critical information. Further, the safety is insured by defining pre- and post-conditions in description of operations for changing state space of the system. The proposed study is focussed more on the safety component; however, the efficiency of the system is not ignored. For example, the model is based on the next generation ATC systems that use new technologies expediting the procedures. Graph theory is used in our model under the Z specification that is a foundation for automating the procedure in our future work. Formal specification is analysed and validated using Z/Eves tool. It is observed that weaknesses of testing and simulation can be overcome by applications of formal techniques avoiding state space explosions problems in complex systems.

Airport Taxi Scheduling Strategy based on Cooperate Particle Swarm Optimization Algorithm

1, * Qing Liu, 2 Chunling Li, 3 Xianfei Luo *1,First and Corresponding Author Department of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China, E-mail: liuqing@nuaa.edu.cn 2 Department of Economics and Management, Civil Aviation university of China, Tianjin, 300300, China 3 Department of Economics and Management, Civil Aviation university of China, Tianjin, 300300, China

Airport taxi planning: Lagrangian decomposition

SUMMARYThe airport taxi planning (TP) module is a decision tool intended to guide airport surface management operations. TP is defined by a flow network optimization model that represents flight ground movements and improves aircraft taxiing routes and schedules during periods of aircraft congestion. TP is not intended to operate as a stand‐alone tool for airport operations management: on the contrary, it must be used in conjunction with existing departing and arriving traffic tools and overseen by the taxi planner of the airport, also known as the aircraft ground controller. TP must be flexible in order to accommodate changing inputs while maintaining consistent routes and schedules already delivered from past executions. Within this dynamic environment, the execution time of TP may not exceed a few minutes. Classic methods for solving binary multi‐commodity flow networks with side constraints are not efficient enough; therefore, a Lagrangian decomposition methodology has been adapted to solve it. We demonstrate TP Lagrangian decomposition using actual data from the Madrid‐Barajas Airport. Copyright © 2011 John Wiley & Sons, Ltd.

A space-time network model based on improved genetic algorithm for airport taxiing scheduling problems

In order to reduce the flight delays and ease the airport congestion, a space-time network taxi scheduling model integrates the three types of conflicts was used. In the model, the aircraft taxiing schedule problem was transformed to multi-commodity network model, and the Genetic-annealing algorithm was designed to solve the problem. The simulation case showed that optimized schedule results significantly reduced the total taxiing time by 586seconds of 17 flights compared with FCFS strategy and avoided the potential flight conflicts, which greatly improved airport operational efficiency. In addition, genetic-annealing algorithm weight out the standard genetic algorithm in convergence rate and solution efficiency.

Performance evaluation of airport taxi services provision

Airports are important infrastructures of modern life and play a major role in the transportation of passengers for tourism and business. Airport terminal curbsides are the critical interfaces between standing vehicles, moving vehicles and pedestrians, acting as the capacity buffer between the road delivery system and the airport terminal building. A correct design and dimensioning of airport terminal curbsides is a major step for achieving positive passenger experiences, since long pedestrian paths, lack of information or long waiting time for transportation may cause passengers discomfort and bewilderment. In the paper, we analyse the viability of a recent proposal from a consulting company for the taxi service provision on the passenger's arrival curbside at Portela Airport (Lisbon, Portugal). We compare the capacity and performance of the proposed taxi service provision, which is based on a 'spine' parking design for taxis, with those of the solution currently implemented at Portela Airport.

Optimal scheduling model for hub airport taxi based on improved ant colony collaborative algorithm

Taxiway connects parking spot and runway,which takes an important part in airport surface scheduling.According to the constraints of aircraft taxi conflict and dynamic allocation of runway's resources,improved ant colony collaborative algorithm and sliding window control were adopted to optimize taxi scheduling.Ensuring taxi conflict free and taking account of single flight taxi time,total taxi time of inbound and outbound flights was reduced.A domestic hub airport taxi scheduling simulation shows that the proposed method and model have obvious advantages,which can provide decision support for hub airport's taxi scheduling.

Airport taxi scheduling optimization strategy based on genetic algorithm

An airport taxi scheduling optmiization strategy based on genetic algorithm was presented,which firstly determ ined the sequence of all the aircraft at each taxi intersection,and then solved the detailed scheduling.The optmiization was achieved through repeated iterations.This strategy effectively enhances the solving efficiency in comparison with the MILP

Airport taxi service regulation: An analysis of an exclusive contract

Taxi service at a number of major airports is supplied by one taxi company under an exclusive contract with the airport operating authority. Conventional wisdom suggests that airport taxi service produced under exclusive contract is socially inefficient. This was found to be true at the Dallas/Fort Worth Airport. In this paper we analyze the exclusive airport taxi service at Honolulu International Airport as a case study. At Honolulu International Airport, the terms of the exclusive airport taxi service contract are far less restrictive than those at Dallas/Fort Worth. Our analysis indicates that exclusive airport service can provide high quality service, reasonable prices and revenues to finance airport service. We conclude that is not the exclusivity, but rather the terms of the contract and the circumstances specific to each market that determines which system is best for a particular place.

A Theory of Price Control

PRICE or rent control is but one of many forms of legislative action which interfere with private contracting in the market place. To delimit the scope of my analysis, I shall use the term "price control" to refer only to any set of regulations which satisfies the following three conditions. First, the control must fix the price (or income)' terms of private contracts; this categorically excludes any laws which regulate the distribution of income among the contracting parties on a share or percentage basis.2 Second, the control must involve no appropriation of proceeds to or from the government; taxation and subsidization are thus excluded. Finally, the fixing of price must not be associated with direct government sales, purchases, or manipulation of resources so as to maintain the regulated price;3 by this stipulation, price "support" is also excluded. Even on such terms, legal regulations to control price are still many and varied. To evaluate our understanding of the class of phenomena which we seek to explain it is essential that we discover implications refutable by facts. By this criterion the available body of economic theory pertaining to price control is deficient indeed: the massive literature on the subject offers few such implications.4 An alternative approach to analyzing the observable effects of price control is presented here.