Clean Vehicle Policies at Public Use Airports
Alexander Kolpakov, Center for Urban Transportation Research at USFShow Abstract
The implementation of alternative fuel technologies and the use of low-emission vehicles provide opportunities for airports to reduce petroleum use, lower greenhouse gas (GHG) emissions and enhance energy security. In addition to using alternative fuel vehicle (AFV) and emission reduction strategies in their own fleets, airports often encourage private ground transportation providers to employ clean vehicle technologies while operating at the airport by implementing different types of formal and informal policies and programs. The survey of 11 commercial airports and 13 private ground transportation operators identified six common types of formal clean vehicle policies applied to private ground transportation providers by the airports, including the explicit requirement to use AFVs, emission standards, minimum fuel economy requirements, incentives for using AFVs, penalties for not using AFVs, and requirements to reduce “empty rides”. The most popular reasons for clean vehicle policies at the surveyed airports include reducing GHG emissions, achieving “green” image in the community and complying with government regulations or binding legal agreements. Major barriers for implementing clean vehicle programs include lack of financial resources or government grants for converting fleets to AFVs, the state of alternative fuel technologies making AFV less practical compared to conventional vehicles and higher upfront costs of alternative fuel technologies. Surveyed airports and private fleets voiced several concerns related to the operation of transportation network companies (TNC) at the airports, including light state/local regulations of TNCs, challenges with tracking TNC operations and enforcing equitable airport fees.
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David Ballard, GRA, Incorporated
Research on Airport Cluster Passengers’ Joint Travel Choice Behavior Based on Cross-Nested Logit Model
Danwen Bao, Nanjing UniversityShow Abstract
To solve the problem of passengers’ joint choice behavior of airports, airlines, and access modes to airports, this paper establishes a cross-nested logit (CNL) model for passengers’ traveling choices. Additionally, to perform a comparative analysis, the paper establishes four traditional logit models. By using survey data of passengers from the Yangtze River Delta airport cluster, the model parameters are estimated and tested, and forecasting analysis is performed to quantify the substitution possibilities under different alternatives. The calculation results show that compared with the multinomial logit (MNL) and nested logit (NL) models, the CNL model has superior fitness. When the utility value changes, passengers first consider changing the means of transportation, then the airline, and finally consider changing the departure airport; payment willingness shows that the differences in passengers’ choices for different airlines or means of transportation are not significant. When the fluctuation of the payment willingness is between 15% and 20%, the passengers may change their travel plans; the forecasting analysis in the two scenarios indicates that the CNL model has considered the correlation between the three-dimensional variables and obtained diversified forecast results under different alternative schemes. The CNL model is more in line with the patterns of passenger behavioral decision making, and its measurement results are also more reliable. The results of the study will provide data to support airports and airlines formulation of development strategies.
Variations in Airline Passenger Expectation of Service Quality Across the Globe
Aymeric Punel, Northwestern UniversityShow Abstract View Presentation
Lama Al Hajj Hassan, Northwestern University
Alireza Ermagun, Mississippi State University
This study explores the relationship between passenger travel experience and service quality in the airline industry for ten geographical regions across the globe. We extract 40,510 passenger reviews and rating information from Skytrax dataset between October 2011 and January 2018. To understand whether and to what extent passenger travel experience varies across ten regions, we test several analytical techniques including sentiment score analysis of the reviews and path analysis. The results support the hypothesis that the customer origins impact travel experience, perception, and evaluation of airline services. More specifically, North American passengers complain more about their national airline, while Eastern and South Eastern Asian passengers are more satisfied with Asian airlines. North American passengers care essentially about the money they pay for their flight. They give less attention to inflight services, as they view flying more as a basic way of commute rather than a special experience. On the contrary, Eastern Asian passengers care more about inflight services in their overall opinion of their flights. Across all geographical regions, seat comfort is the most important factor to evaluate the value for money of the flight, while cabin staff service is the main feature to rate overall flight experience.
An Exploratory Investigation of Public Perceptions Toward Key Benefits and Concerns from the Future Use of Flying Cars
Ugur Eker, University at Buffalo - The State University of New YorkShow Abstract
Grigorios Fountas, Edinburgh Napier University
Panagiotis Anastasopoulos, University at Buffalo, The State University of New York
Stephen Still, University at Buffalo, The State University of New York
The imminent introduction of flying cars in the traffic fleet is anticipated to modify the mobility patterns of urban commuters. Flying cars’ hybrid operation on the ground and in the air, in conjunction with their (semi-) automated capabilities, may lead to more appealing trip considerations, such as travel time, fuel consumption, or environmental emissions, as well as to the emergence of new sources of concerns for the potential users. In this context, the future adoption of flying cars is directly associated with individuals’ perceptions of the benefits and concerns arising from the use of flying cars. This paper aims to identify the perceptual patterns of individuals towards travel time, cost and environmental benefits, as well as towards challenges arising from key flying cars operational characteristics. To that end, grouped random parameters bivariate probit models of individuals’ perceptions are estimated using data collected from an online survey of 692 individuals. The statistical analysis shows that a number of socio-demographic, behavioral, and attitudinal characteristics affect respondents’ expectations and concerns towards the adoption and implementation of flying cars. Even though individuals’ perceptions are anticipated to undergo substantial changes until the introduction of flying cars in the traffic fleet, the findings of this work may shed more light on perceptual nuances with critical effect on public interest about the adoption of flying cars.
Determination of the Bearing Capacity of Airports Cleared and Graded Areas
Vittorio Ranieri, Polytechnic University of BariShow Abstract View Presentation
Nicola Berloco, Politecnico di Bari
Pasquale Colonna, Politecnico di Bari
Donato D'Auria, Aeroporti di Puglia
Vincenzo Disalvo, Civil Engineer
Veronica Fedele, Politecnico di Bari
Paolo Intini, Politecnico di Bari
The aircraft veer-off accident is a lateral excursion from the runway. The Cleared-and-Graded Area (CGA) outside the runway is a specifically designed area which must be provided with graded bearing capacity, to ease the safe stop of aircraft veered-off. However, no clear standards are currently present for the design of bearing capacity values and their gradation in the CGAs. This study attempts to address these lacks, by proposing the division of CGAs into strips of specified widths and fixed bearing capacities, decreasing towards the outside of the runway. The division of the CGA into strips is based on a risk assessment procedure, in which veer-off accidents (period: 1980-2016) were analysed. Both probabilities and consequences associated to side distances run by aircraft veered-off from the runway center-line (CL) were assessed. Risks associated to different side distances run were then computed by combining probabilities and consequences. Three CGA strips were proposed, having width extending from, namely, 30 to 50 m, 50 to 65 m, 65 to 105 m from the runway CL. Whereas, the bearing capacity values proposed for each CGA strip were based on the simulation of a veer-off accident, carried out through a dedicated model, which takes into account soil properties and other influencing characteristics. Among the different considered combinations of California Bearing Ratio (CBR) values associated to each strip, those deemed to provide the safest aircraft stopping were set, namely, to 17, 16, and 15. The proposed values are coherent with current International and National regulations.
Airline Passenger Load Factor Prediction
Kevser Simsek, Turkish AirlinesShow Abstract
The aviation industry uses forecasting both to enable short term decisions, and to support longer term decisions in respect of future patterns in demand for air travel. The main aim of forecasting is to determine how patterns of demand will change over time, reflecting external factors such as growth in incomes, changes in prices and demographic changes. Forecasting is therefore a key tool for decision making, and is used in both business planning and policy decision making. With this study, it was aimed to forecast the passenger load factor (PLF) by using the information of two years reservation, group sales data, calendar information, weekly dates, trend difference between current year and previous year , past load factor information, load factor information of the same period of the previous year of Turkish Airlines which is a four star airline with a fleet of over 300 aircraft flying to over 290 destinations around the world. When each flight is thought to be its own characteristic, there is a need to find a solution for this work by a method that can reflect both the flight profile and the flight time dimension. Panel data regression method will be used for finding a solution of the problem. When the flight hasn't yet departed, a preliminary structure for both the economy and the business class will be obtained. In terms of revenue management, it is expected to optimize income, change capacities, efficiency of flight routes, forecasts for special days and certain flight days and months.
Global Airfreight Networks and Regional Competitiveness: Modeling Value in Minnesota’s Evolving Medical Supply Chain
Travis Fried, World Resources Institute (WRI)Show Abstract View Presentation
Lee Munnich, University of Minnesota Hubert H Humphrey School of Public Affairs
Thomas Horan, University of Redlands
Minnesota is home to large medical device industry headquarters, world-renowned healthcare centers, and a public/private transportation sector that relies on strategic freight network investments to promote regional economic competitiveness. While inherently multi-modal, a key to designing transportation policy that accommodates growth in Minnesota’s burgeoning medical sector is deciphering how airports not only serve hospitals and patients around the globe but also adapt to evolving supply chains. The current research on air cargo volume metrics, rather than value, fails to capture shifts within the medical technology and healthcare industry where rising commodity prices, advancing technology, and federal healthcare policy is altering supply chain management practices. Namely, medical manufacturers, shippers, and providers are increasingly relying on airports to ensure the secure, just-in-time delivery of products around the globe. Therefore, this study takes a multi-pronged methodological approach. First, a PostGIS-based, 4-step transportation model analyzes and visualizes medical commodity value flows to and from Minnesota airports. The model reveals that Minneapolis-Saint Paul International Airport (MSP) is a dominate force that transports $8.6 billion annually in medical commodities (92 percent of the state’s total). The study then entails a qualitative case study of Rochester Airport (RST) and Mayo Clinic, revealing both the global reach of the Mayo supply chain and the role of secondary airports in enabling this reach. These results suggest that medical supply chain managers are increasingly seeking airfreight network investments that ensure the reliable and timely flow of medical devices and products. This study also recommends future research and policy strategies.
Changes in Air Service Provision and Competition in the North Atlantic Market
Nigel Dennis, University of WestminsterShow Abstract View Presentation
Dr. David Pitfield, University of Westminster
This paper considers the changes to air services that have taken place on the North Atlantic from 2005-2018. The distribution of frequency and capacity by airport and airline is assessed and also for the airline alliance groups and the different aircraft types. Market concentration is analysed for the North Atlantic as a whole and for the principal airports in each region. It is shown that the major US domestic hubs have lost ground while the west coast and Canadian airports have gained market share. In Europe there has been greater dispersion, driven by the new entrant carriers with point to point flights and the growth of the Reykjavik and Dublin hubs. With the exception of Air Canada, the major operators (including merger partners) have all lost market share although Delta has almost held its position. The Star Alliance has slightly gained market share following the switch of Continental from SkyTeam and the addition of Swiss and Air India but the other global alliances have slipped back. The main beneficiaries are Norwegian, Thomas Cook, Tui, Aer Lingus, Icelandair and WOW. The HHI results indicate that the immunised joint ventures have greatly reduced competition but this has been partially counteracted by the growth of new entrants. Market concentration has increased at New York JFK and Frankfurt but reduced at the four other leading gateways. The aircraft analysis identifies the growing role of the mid-sized wide-body aircraft but the increased presence of the Boeing 757 is also notable.
Integrating Multi-Stop Service and Hub Effects into the Estimation of the Long-Term Impacts of the American Airlines and US Airways Merger
Ziwei Li, Cornell UniversityShow Abstract
Linda Nozick, Cornell University
This paper extends recent research into the long term pricing impacts of the American Airlines and US Airways merger in 2013. Zhang and Nozick (2018), using the 10% ticket sample, demonstrated that low cost carriers’ post-merger lowered prices for non-stop service post-merger and those reductions in fare were the largest where American Airlines and US Airways were more prominent pre-merger. The paper extend their analysis to include multi-hop service, the impact of hubs and focus cities, and to address the feedback between prices and market concentration by introducing population and income into the statistical models. The estimated models again show that (1) legacy carriers were able to raise prices after the merger and the amount of the increase was larger where American and US Airways played a smaller role in the market pre-merger; and (2) low cost carriers reduced their prices and the amount of the reduction was also heavily influenced by the role that US Airways and American Airlines played in the market pre-merger. For the legacy carriers these trends have generally increased across 2015, 2016 and 2017. For the low cost carriers, the reductions in price over these three years have generally decreased. Finally, we find that where service is provided using airports that are hubs or focus cities, prices are generally higher and that impact is more pronounced in 2016 and 2017 in contrast to 2015.
Reviewing the DATAS of Aviation Research Data: Diversity, Availability, Tractability, Applicability, and Sources
Max Li, Massachusetts Institute of Technology (MIT)Show Abstract View Presentation
Megan Ryerson, University of Pennsylvania
The field of aviation research is entering the era of big data. While data-driven advancements in aviation have clearly brought about applicable models and results with immediate implications, we argue that the influx of aviation data should be better characterized and documented to enable more efficient and standardized usage. To this end, we examine 200 well-cited research articles from sub-disciplines ranging from revenue management to air traffic control published on or after 2010 in order to analyze the diversity, availability, tractability, applicability, and sources (DATAS) of data utilized in aviation research. We find high levels of data diversity within aviation research, with 16 data categories ranging from air traffic flow management-type data to data from distributed sensors in line with the Internet-of-Things (IoT) paradigm. We identified a dominance of proprietary, non-public data in aviation research, with 68% of the 200 research articles utilizing solely proprietary data in deriving their results, and a further 8% utilizing a mixture of proprietary and publicly available data. The pervasiveness of proprietary data has implications on reproducibility and extending research results. We also highlight the increasing tractability of the data by surveying the computational power required to process the data sets, and present vignettes of applications and results that stem from these data-driven studies. Finally, we propose several recommendations regarding standardizing data source nomenclature as well as increasing the availability of and usage of publicly available data.
Simulating Airline Behavior: An Application for the Australian Domestic Market
Khan Doyme, University College LondonShow Abstract View Presentation
Lynnette Dray, Air Transportation Systems Laboratory, UCL Energy Institute, The Bartlett School of Environment Energy and Resources, 14 Upper Woburn Place, London, WC1H 0NN
Aidan O'Sullivan, Air Transportation Systems Laboratory, UCL Energy Institute, The Bartlett School of Environment Energy and Resources, 14 Upper Woburn Place, London, WC1H 0NN
Andreas Schafer, University College London
In this paper we demonstrate the ability of a model, which simulates competition between airlines in a domestic aviation market, to accurately reproduce real world behaviour. The Australian market was chosen as a test case as it is a geographically isolated region with significant demand and complexity, including one of the busiest routes in the world, where connecting international passengers do not significantly skew the market. The model is based on an n-player noncooperative game, where each airline represents a player within the game. The primary assumption is that each airline attempts to maximise profits by adjusting the decision variables of airfares, flight frequency and choice of aircraft on routes within its network. The approach works iteratively, allowing each airline to respond to the decisions made by other airlines during each successive optimisation. The model is said to reach convergence when there is no significant change in any airline's profit from one iteration to the next. Once this occurs, the predictions of each airline's decision variables can be compared to real data. The model gives highly detailed predictions of airline specific airfares, flight frequencies on segments, passenger flows and airline market share, which strongly correlate with observed values.
A Model to Optimize Air Travel Passenger Screening for Global Outbreak Response and Mitigation
Aleksa Zlojutro, University of New South WalesShow Abstract
David Rey, University of New South Wales
Lauren Gardner, Johns Hopkins University
The introduction and spread of emerging infectious diseases is increasing in both prevalence and scale. Whether naturally, accidentally or maliciously introduced, the substantial uncertainty surrounding the emergence of novel viruses, specifically where they may come from and how they will spread, demands robust and quantifiably validated outbreak control policies that can be implemented in real time. This work proposes an ensemble of new control strategies for mitigating infectious disease pandemics that spread through human contact. The strategies are defined within a novel mathematical modeling framework that accounts for both the outbreak dynamics and control decisions. The proposed control mechanism evaluated in this work is air-travel passenger screening, however the modelling framework is applicable to alternative control mechanisms. Each strategy varies in its selection procedure of where and how much screening is assigned, with all strategies constrained by a pre-determined monetary budget. We evaluate each control strategy using a meta-population stochastic simulation model, and compare the strategies based on their effectiveness of reducing the outbreak size and spread. Sensitivity analysis is conducted to illustrate the robustness of the strategies across a range of outbreak scenarios, disease parameters, and modelling assumptions. Finally, a case study is presented for the 2009 H1N1 influenza pandemic. The results highlight the importance of strategically allocating outbreak control resources, and identify the most robust border control policies that can be implemented in the early stages of an outbreak.
Allowing for Heterogeneity in the Consideration of Airport Access Modes: The Case of Bari Airport
Angela Stefania Bergantino, University of BariShow Abstract View Presentation
Mauro Capurso, University of Leeds
Thijs Dekker, University of Leeds
Stephane Hess, University of Leeds
Mode choice models traditionally assume that all objectively available alternatives are considered. This might not always be a reasonable assumption, even when the number of alternatives is limited. Consideration of alternatives, like many other aspects of the decision-making process, cannot be observed by the analyst, and can only be imperfectly measured. As part of a stated choice survey aimed at unveiling air passengers’ preferences towards access modes to Bari International Airport, in Italy, we collected a wide set of indicators that either directly or indirectly measure respondents’ consideration for the public transport alternative. In our access mode choice model, consideration for public transport services is treated as a latent variable, and enters the utility function for this mode through a ‘discounting’ factor. The proposed Integrated Choice and Latent Variable approach allows the analyst not only to overcome potential endogeneity and measurement error issues associated with the indicators, but also makes the model suitable for forecasting. As a result of accounting for consideration effects, we observe an improvement in fit which also holds in a validation sample; moreover, the effects of policy changes aimed at improving modal share for public transport are considerably reduced.
Research on the Classification of Air Route Intersections in the Airspace of China
Lili Wang, Civil Aviation University of ChinaShow Abstract View Presentation
Wanle Wang, Civil Aviation University of China
Fang Wei, Civil Aviation University of China
Yakun Hu, University of China
As the intersection point for crossing traffic flows, air route intersections are the major bottlenecks in the whole airspace. In order to reduce controller workload and maintain traffic safety, air traffic operation units in China came up with the idea of developing an “overpass” at busy intersections due to restricted airspace use and rapid growth of air traffic. The basic idea is to strategically separate flows of aircraft on intersecting routes vertically by allocating distinct flight levels to them. As such practice of requiring aircraft to maintain an agreed flight level long before they cross the intersections exhausts available flight levels for flights departing from many locations and reduces operation efficiency, the air traffic management unit hopes to use a quantification indicator for intersections which can serve as a metric to decide whether an overpass should be established at an intersection. In this paper, such an indicator – a classification index - is proposed for air route intersections based on the intersection complexity and collision risk at the air route intersection. Besides, according to the calculation results of the classification index for typical intersections in Chinese airspace, a classification system is established, which can serve as a guidance for the establishment of overpasses in the future. A case study is provided to demonstrate the working of the system. The proposed intersection classification method combining both intersection complexity and collision risk should help the decision-makers better understand the operation characteristics of intersections and make informed decisions to balance workload and efficiency.
Aircraft Carbon Dioxide Emission and Spatial Characteristics of a Regional Multi-Airport
Rong Hu, Nanjing UniversityShow Abstract View Presentation
Jialin Zhu, Nanjing University
Yu Zhang, University of South Florida
Junfeng Zhang, Nanjing University
Airports are essential parts of the air transport system, but also are local sources of environmental impacts. Aircraft CO2 emissions at airports are among the most relevant because of their potential greenhouse effects. This paper evaluates aircraft CO2 emission quantity and intensity (per passenger and per landing and take-off, LTO) during LTO cycles at nine airports in Jiangsu province from 2007-2016. Then, spatial distribution and classification are performed by indicators of CO2 emission quantity and intensity. Moran’s I index is used to determine the spatial aggregation effect. Finally, policy implications are provided due to these spatial characteristics at different administrative levels. The main findings are as follows: (1) Airports in South Jiangsu exhibit higher emission quantity and intensity per LTO and lower intensity per passenger; (2) Most airports in South Jiangsu are categorized into the classes of “high quantity–low intensity per passenger” and “high quantity–high intensity per LTO”, whereas airports in North Jiangsu are “low quantity–high intensity per passenger” and “low quantity–low intensity per LTO”; (3) significant spatial correlations exist among airports in Jiangsu province in terms of CO2 emission intensity per passenger; airports in South Jiangsu have relatively low emission intensity and tend to have a positive spillover effect on neighboring airports.
Assessing the Impact of High-Speed Rail on Domestic Aviation CO2 Emissions in China
Bojun Wang, University College LondonShow Abstract
Aidan O'Sullivan, Air Transportation Systems Laboratory, UCL Energy Institute, The Bartlett School of Environment Energy and Resources, 14 Upper Woburn Place, London, WC1H 0NN
Andreas Schafer, University College London
ABSTRACT This paper examines the beneficial impact of high-speed rail (HSR) on reducing aviation CO2 emissions in China. As a fast-growing economy and the world’s largest CO2 emitter, China has made massive infrastructure investments but has also committed to reducing emissions across all sectors. In this study we demonstrate that investments in China’s HSR can effectively contribute to emissions reduction from domestic aviation, a sector that is particularly challenging to decarbonize. Although a wide body of literature has assessed the competition between HSR and air transport, little attention has been paid to the climate implications of such phenomenon. From our estimation, through mode substitution for air transport, HSR generates a cumulative net CO2 savings of between 1.76 and 2.76 million tons from 2012 to 2015. This was equivalent to 3.2-5.1% of 2015 domestic aviation emissions. Importantly, we also demonstrate that by not taking into account the electricity consumption of HSR, the environmental benefits of HSR would be overestimated. Lastly, through analysis on future energy mix scenarios this study highlights that HSR has a great potential to reduce CO2 emissions even further if China achieved its climate pledge in the Paris Agreement in terms of decarbonizing its electricity generation sector by 2030. Keywords: High-speed rail, Air transportation, Substitution, Net CO2 savings, China