长三角民航协同规划的上海实践

推进长三角交通一体化规划落地是实施国家长三角一体化发展战略的重要基础。通过系统梳理上海多年空间规划实践经验,遵循城市群、机场群、近沪地区、全球城市多机场体系的逻辑思路,基于问题导向和目标导向,提出优先实现近沪地区民航紧密联系的规划突破点。临近地区民航协同,需要实现发展目标、通道枢纽、飞行保障、运输服务、货运物流、设施建设、重大项目、进度时序等多方面系统协同,建立契约关系,以市场化方式实践区域民航协同发展。     

Predictability impacts of airport surface automation

Past evaluations of airport surface operations automation technologies have focused on capacity utilization, delay mitigation and fuel efficiency impacts. Predictability, while recognized as an important operational performance goal, has received little attention. One reason could be that applicable predictability metrics have not been developed in the context of airport surface operations management. This research fills the gap by proposing metrics for predictability performance evaluation. Using results from a SARDA human-in-the-loop simulation conducted at NASA Ames’ Future Flight Central, we present a comprehensive assessment of the predictability impacts of airport surface automation. A wide range of the impacts is considered, which includes variability in taxi-out time, predictability of take-off time and take-off sequence, entropy of the airfield state, and perceived predictability from users.     

An analysis of airport–airline vertical relationships with risk sharing contracts under asymmetric information structures

We analyze the double moral hazard problem at the joint venture type airport–airline vertical relationship, where two parties both contribute efforts to the joint venture but neither of them can see the other’s efforts. With the continuous-time stochastic dynamic programming model, we show that by the de-centralized utility maximizations of two parties under very strict conditions, i.e., optimal efforts’ cost being negligible and their risk averse parameters both asymptotically approaching to zero, the vertical contract could be agreed as the optimal sharing rule, which is the linear function of the final state with the slope being the product of their productivity difference and uncertainty (diffusion rate) level index.If both parties’ productivities are same, or the diffusion rate of the underlying process is unity, optimal linear sharing rule do not depend on the final state. If their conditions not dependent on final state are symmetric as well, then risk sharing disappears completely. In numerical examples, we illustrate the complex impact of uncertainty increase and end-of-period load factor improvement on the optimal sharing rule, and the relatively simple impact on total utility levels.     

Airport capacity choice under airport-airline vertical arrangements

This study investigates the effects of airport-airline vertical arrangements on airport capacity choices under demand uncertainty. A multi-stage game is analysed, in which competing airlines contribute to capacity investments and share airport revenues. Our analytical results suggest that for a profit-maximising airport, such a vertical arrangement leads to higher capacity but may not increase its profit, whereas for a welfare-maximising airport, such an arrangement has no effect on capacity or welfare. Capital cost savings brought by airport-airline cooperation, if any, always lead to higher capacity, and to higher profit for a profit-maximising airport and higher welfare for a welfare-maximising airport. Numerical simulations reveal that win-win outcomes may be achieved for an airport and its airlines without government intervention.     

Real-time airport surface movement planning: Minimizing aircraft emissions

This paper presents a study towards the development of a real-time taxi movement planning system that seeks to optimize the timed taxiing routes of all aircraft on an airport surface, by minimizing the emissions that result from taxiing aircraft operations. To resolve this online planning problem, one of the most commonly employed operations research methods for large-scale problems has been successfully used, viz., mixed-integer linear programming (MILP). The MILP formulation implemented herein permits the planning system to update the total taxi planning every 15 s, allowing to respond to unforeseen disturbances in the traffic flow. Extensive numerical experiments involving a realistic (hub) airport environment bear out that an estimated environmental benefit of 1–3 percent per emission product can be obtained. This research effort clearly demonstrates that a surface movement planning system capable of minimizing the emissions in conjunction with the total taxiing time can be beneficial for airports that face dense surface traffic and stringent environmental requirements.     

An online speed profile generation approach for efficient airport ground movement

The precise guidance and control of taxiing aircraft based on four-dimensional trajectories (4DTs) has been recognised as a promising means to ensure safe and efficient airport ground movement in the context of ever growing air traffic demand. In this paper, a systematic approach for online speed profile generation is proposed. The aim is to generate fuel-efficient speed profiles respecting the timing constraints imposed by routing and scheduling, which ensures conflict-free movement of aircraft in the planning stage. The problem is first formulated as a nonlinear optimisation model, which uses a more flexible edge-based speed profile definition. A decomposed solution approach (following the framework of matheuristic) is then proposed to generate feasible speed profiles in real time. The decomposed solution approach reduces the nonlinear optimisation model into three tractable constituent problems. The control point arrival time allocation problem is solved using linear programming. The control point speed allocation problem is solved using particle swarm optimisation. And the complete speed profile between control points is determined using enumeration. Finally, improved speed profiles are generated through further optimisation upon the feasible speed profiles. The effectiveness and advantages of the proposed approach are validated using datasets of real-world airports.     

Experience sampling in and around airports. Momentary subjective wellbeing,airports, and aviation noise in England

We explore the wellbeing of people in and around English airports using real-time data from a large spatial positioning experience sampling dataset (Mappiness). We analyze the association between subjective wellbeing reported in the moment and aviation, in terms of airport location, aircraft noise, and activities within airports. This is the first time that a large Experience Sample Method (ESM) of momentary wellbeing measurements has been used to quantify the associations between aviation and subjective wellbeing. Being within areas of high levels of aircraft noise is associated with lower levels of happiness and relaxation. Those surveyed in proximity to airports report significantly lower levels of relaxation. These findings have important implications to policy. Exploiting the panel nature of the ESM data provides the strongest causal claims to date of the negative association between aviation activities and subjective wellbeing. The Mappiness application also allows us to assess the association between airports and wellbeing on those inside them, and divide activities within airports between those who work there and those who are passing through for travel purposes, as well as the effects of aircraft noise beyond airports. This gives us a broader insight into the range of impacts, both positive and negative, that aviation has on peoples’ momentary wellbeing, which may be used to inform aviation noise mitigation and compensation policies in the future.     

An aggregate demand model for air passenger traffic in the hub-and-spoke network

In this paper, we build an aggregate demand model for air passenger traffic in a hub-and-spoke network. This model considers the roles of airline service variables such as service frequency, aircraft size, ticket price, flight distance, and number of spokes in the network. It also takes into account the influence of local passengers and social-economic and demographic conditions in the spoke and hub metropolitan areas. The hub airport capacity, which has a significant impact on service quality in the hub airport and in the whole hub-and-spoke network, is also taken into consideration.Our demand model reveals that airlines can attract more connecting passengers in a hub-and-spoke network by increasing service frequency than by increasing aircraft size in the same percentage. Our research confirms the importance of local service to connecting passengers, and finds that, interestingly, airlines’ services in the first flight leg are more important to attract passengers than those in the second flight segment. Based on data in this study, we also find that a 1% reduction of ticket price will bring about 0.9% more connecting passengers, and a 1% increase of airport acceptance rate can bring about 0.35% more connecting passengers in the network, with all else equal. These findings are helpful for airlines to understand the effects of changing their services, and also useful for us to quantify the benefits of hub airport expansion projects.At the end of this paper, we give an example as an application to demonstrate how the developed demand model could be used to valuate passengers’ direct benefit from airport capacity expansion.     

On the relationship between airport pricing models

Airport pricing papers can be divided into two approaches. In the traditional approach the demand for airport services depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled. In the vertical-structure approach instead, airports provide an input for an airline oligopoly and it is the equilibrium of this downstream market which determines the airports’ demand. We prove, analytically, that the traditional approach to airport pricing is valid if air carriers have no market power, i.e. airlines are atomistic or they behave as price takers (perfect competition) and have constant marginal operational costs. When carriers have market power, this approach may result in a surplus measure that falls short of giving a true measure of social surplus. Furthermore, its use prescribes a traffic level that is, for given capacity, smaller than the socially optimal level. When carriers have market power and consequently both airports and airlines behave strategically, a vertical-structure approach appears a more reasonable approach to airport pricing issues.     

Deconstructing delay: A non-parametric approach to analyzing delay changes in single server queuing systems

This paper introduces an empirically driven, non-parametric method to isolate and estimate the effects that changes in demand and changes in throughput have on delay – in particular, arrival and departure flight delay at airport runways. Classic queuing concepts were used to develop a method by which an intermediate, or counterfactual, queuing scenario could be constructed, to isolate the delay effects due to shifts in demand and throughput. This method includes the development of a stochastic throughput function that is based entirely on data and has three key features. Firstly, the function relies on non-parametric, empirically-based probability distributions of throughput counts. Secondly, facility capacity needs not be explicitly defined, as it is implicitly included in the probability distributions of throughput. Thirdly, the throughput performance function preserves the effect of factors that cause capacity (and, therefore, throughput) to fluctuate over a given period. Temporal sequences of high, moderate, and low capacity are maintained between the observed and counterfactual scenarios. The method was applied to a case study of the three major New York area airports of LaGuardia (LGA), Newark Liberty (EWR), and John F. Kennedy (JFK), using operational data extracted from the Federal Aviation Administration’s (FAA’s) Aviation System Performance Metrics (ASPM) database. The focus was on the peak summer travel seasons of 2006 and 2007, as these airports experienced record levels of delay in 2007. The results indicate that decreases in both demand and throughput were experienced at LGA and EWR, although the decreases in throughput had more significant effects on operational delays as they increased overall at these airports. At JFK, the increase in departure throughput was not sufficient to offset the increase in departure demands. For arrivals, demand increased and throughput decreased. These trends caused a significant growth in delay at JFK between 2006 and 2007.