Mobile application for efficient taxi allocation at airports

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 52-54).The important role that taxis play in bringing passengers from an airport terminal to their final destination is often overlooked in airport operations and design. Due to varying flight arrival patterns at different terminals, taxi drivers are often unsure which terminal they should queue at. In this thesis, we present ChangiNOW, a mobile app that uses a predictive queueing model to efficiently allocate taxis. The ChangiNOW system uses observed taxi and flight data at each of the four terminals of Singapores Changi Airport to estimate the expected waiting time and queue length for taxis arriving at these terminals, and then sends taxis to terminals where waiting time is shortest. The app communicates this information to taxi drivers in a visually intuitive and appealing way, motivating them to service those terminals with the highest taxi demand. We present the theoretical details that underpin our prediction engine and validate our theory with several targeted numerical simulations. Finally, we evaluate the performance of this system in large-scale experiments and show that our system achieves a significant improvement in both passenger and taxi waiting time.by Afian Anwar.S.M. in Transportatio

ChangiNOW: A mobile application for efficient taxi allocation at airports

We present an application that uses a predictive queueing model to efficiently allocate taxis. The system uses observed taxi and flight data at each of the four terminals of Singapore's Changi Airport to estimate the expected waiting time and queue length for taxis arriving at these terminals, and then sends taxis to terminals where demand is highest. We propose a service model that enables our system to be deployed on a smartphone platform to participating taxi drivers. We present the theoretical details which underpin our prediction engine and corroborate our theory with several targeted numerical simulations. Finally, we evaluate the performance of this system in large-scale experiments and show that our system achieves a significant improvement in both passenger and taxi waiting time.Singapore-MIT Alliance for Research and Technology (Innovation Center Explorer Grant 015824-119)United States. Office of Naval Research (Grant N00014-09-11051

Gender Differences and Cockpit Design

The design project reported in this paper examined female pilots’ experiences with how well or poorly cockpit design allowed them to safely accomplish their flying missions. The general aviation aircraft cockpit is not designed for female pilots, often causing them to find ways to adapt to the cockpit in order to operate the aircraft safely. Two primary focal areas for adaptations address issues with accessibility of controls and “viewability” inside and outside the cockpit. The design team used a Situation Awareness-Oriented Interface Design (SAOD) approach in preparing cockpit design recommendations for general aviation aircraft that would accommodate female pilots

Equity research - Ryanair Holding PLC

Mestrado em FinançasEquity Research sobre a Ryanair Holdings PLC (RYA), elaborado segundo as recomendações do CFA Institute, que integra a avaliação minuciosa de toda a sua atividade, com o objetivo final de se perspetivar o valor intrínseco das suas ações a 31 de Dezembro de 2020. A estrutura orgânica do presente documento é dividida em duas partes distintas: uma primeira parte, onde se analisa e se apresenta a RYA e a indústria onde se insere e uma segunda parte, onde, considerando as informações da primeira parte, se projeta e se mensura o desenvolvimento da empresa nos próximos anos, recorrendo a modelos de avaliação como o dos Fluxos de Caixa Atualizados e o Valor Atual Ajustado (métodos absolutos) e ainda ao modelo dos Múltiplos comparáveis (método relativo). Todo o conteúdo deste projeto contempla informações passíveis de análise até dia 27 de Setembro de 2019. Com um preço-alvo de €10,95, no final de 2020, calculado através do modelo dos Fluxos de Caixa Atualizados, representando um potencial de valorização de 6,37% considerando o preço de €10,29, a 27 de Setembro de 2019, a nossa recomendação de investimento é MANTER, ou seja, não se considera a existência de razões fortes para a compra, nem de razões negativas para a venda. Seguindo as especificações do modelo de Valor Atual Ajustado, alcança-se um resultado idêntico que sustenta a mesma recomendação. Com um preço-alvo de €11,10, o que totaliza um potencial de valorização de 7,90%, o conselho de MANTER, preserva-se.As part of the Master's Final Work in Finance, and according to the recommendations of the CFA Institute, this project about Ryanair Holdings PLC (RYA), which integrates the scrupulous analysis of all its business activity, has been settled with the main purpose of knowing the intrinsic value of its shares, on the 31st December, 2020. The organic structure of this project is divided into two distinct parts. The first part where RYA is analyzed and also the industry in which the Company operates; the second part, in which, the information in the first part is considered and it is forecasted and measured the Company's growth, over the next few years, using valuation models as Discounted Cash Flows (DCF), Adjusted Present Value (absolute methods) and the Multiples Approach (relative method). All of the developments of this project include information until 27th September 2019. With a target price of €10.95 at the end of 2020, given the DCF Model, representing an upside potential of 6.37% over the price of €10.29, on 27th September 2019, our investment recommendation is HOLD, that is no strong reasons for buying or selling. Considering the main features of Adjusted Present Value Model, an identical result was reached that supports the same investment recommendation. With a target price of €11.10, which adds up to a 7.90% upside potential, the advice of HOLD is well-maintained.info:eu-repo/semantics/publishedVersio

Passenger Air Service in Michigan’s Upper Peninsula: Overview and Analysis

[Excerpt] Rural America needs safe, efficient, reliable, and accessible passenger air service. Federal government subsidies have long been necessary to assure that residents in smaller, less profitable markets have access to the nation’s transportation network. That access is necessary for a community’s economic health, is arguably a right of all taxpayers and residents, and is in public interest. But market forces within the aviation industry are today driving a restructuring that may curtail or eliminate service to many communities in the nation. And the present political climate raises a serious question about the federal government’s continued commitment to the nation’s rural air transportation system. This report focuses on the state of passenger air service in Michigan’s Upper Peninsula [U.P.]. The U.P. is among the most geographically remote areas in the eastern half of the United States. The region’s economic, social, and cultural institutions are increasingly related to a global marketplace. These depend, in varying degrees, on access to the national and global transportation network. Scheduled, commercial passenger air service is especially critical for this area too distant from passenger rail, without adequate commercial bus service, with few four-lane highways and very limited connection to the Interstate Highway system

Equity research - Ryanair Holdings Plc

Mestrado em FinançasA Ryanair Holdings plc (Ryanair Holdings) é uma holding da Ryanair Limited. Trata-se de uma companhia aérea de transporte de passageiros que possui uma estratégia de preço ultra reduzido associado a um serviço standard de qualidade reduzida, em que os serviços extra são pagos pelo consumidor. Estes serviços auxiliares dividem-se em "non-flight", relacionados com a Internet e ainda "in-flight", onde se incluem a venda de bebidas, alimentos e mercadorias. Adicionalmente, comercializa serviços de alojamento e seguro de viagem através do seu site e ainda fornece os seus próprios serviços de bagagem no aeroporto de Dublin. Serve rotas de curta distância ("ponto-a-ponto") entre a Irlanda, o Reino Unido, a Europa continental, Marrocos e Israel. Em Junho de 2017, a Ryanair tinha uma frota principal de mais de 360 aeronaves Boeing 737-800 e ofereceu mais de 2.000 vôos regulares de curta distância por dia, servindo aproximadamente 200 aeroportos em toda a Europa. O principal objetivo deste projeto de pesquisa de patrimônio é determinar o valor intrínseco da ação da Ryanair através de uma análise detalhada do desempenho da empresa nos últimos anos e também através de uma prospeção o mais precisa possível do mercado. A avaliação da empresa baseou-se nos fluxos de caixa descontados (DCF) para a empresa e na metodologia WACC que foi considerada a mais adequada para a empresa de acordo com a revisão da literatura. Além disso, também realizamos uma Avaliação Relativa para complementar a nossa análise.Ryanair Holdings plc (Ryanair Holdings) is a holding company of Ryanair Limited. It is a passenger transport airline which has an ultra-low-price strategy coupled with a standard reduced quality service, where extra services are paid by the consumer. These nominated ancillary services are divided into non-flight, Internet-related and in-flight, which include the sale of beverages, food and goods. Additionally, it markets accommodation and travel insurance services through its website and even provides its own baggage services at Dublin airport. It serves short-haul routes ("point-to-point") between Ireland, the United Kingdom, continental Europe, Morocco and Israel. In June 2017, Ryanair had a main fleet of more than 360 Boeing 737-800 aircraft and offered more than 2,000 regular short-haul flights per day, serving approximately 200 airports throughout Europe. The main goal of this Equity Research project is to determine Ryanair's stock intrinsic value through a detailed analysis of the company performance in the last couple of years and also through the most accurate prospecting of the market. The valuation of the company was based on the Free Cash Flows to the Firm and the WACC methodology which was considered the most suitable for the company according to the literature review. In addition, we also performed a Relative Valuation to complement our analysis.info:eu-repo/semantics/publishedVersio

Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation

Shared-account Cross-domain Sequential Recommendation (SCSR) task aims to recommend the next item via leveraging the mixed user behaviors in multiple domains. It is gaining immense research attention as more and more users tend to sign up on different platforms and share accounts with others to access domain-specific services. Existing works on SCSR mainly rely on mining sequential patterns via Recurrent Neural Network (RNN)-based models, which suffer from the following limitations: 1) RNN-based methods overwhelmingly target discovering sequential dependencies in single-user behaviors. They are not expressive enough to capture the relationships among multiple entities in SCSR. 2) All existing methods bridge two domains via knowledge transfer in the latent space, and ignore the explicit cross-domain graph structure. 3) None existing studies consider the time interval information among items, which is essential in the sequential recommendation for characterizing different items and learning discriminative representations for them. In this work, we propose a new graph-based solution, namely TiDA-GCN, to address the above challenges. Specifically, we first link users and items in each domain as a graph. Then, we devise a domain-aware graph convolution network to learn userspecific node representations. To fully account for users' domainspecific preferences on items, two effective attention mechanisms are further developed to selectively guide the message passing process. Moreover, to further enhance item- and account-level representation learning, we incorporate the time interval into the message passing, and design an account-aware self-attention module for learning items' interactive characteristics. Experiments demonstrate the superiority of our proposed method from various aspects.Comment: 15 pages, 6 figure

Airport service quality and passenger satisfaction : the impact of service failure on the likelihood of promoting an airport online

Based on the analysis of 2278 online passenger ratings of airports worldwide, this study uses a standard multinomial logit model to determine the likelihood of a passenger being a promoter of an airport when a service attribute has failed, controlling for several passenger and airport characteristics. Results show that failures associated with airport staff and queueing times are most likely to reduce the probability of a passenger being a promoter of an airport. Failures associated with airport shopping and wifi service are least likely to do so. More importantly, the failure of any service attribute in this study significantly reduces the probability of a passenger being a promoter of an airport. This suggests that all parts of the airport value chain are likely to suffer when a service attribute fails. Passenger and airport characteristics included in this study do not add significant explanation to whether a passenger becomes a promoter. Keywords: airport service quality, service failure, online ratings, airport value chain, passenger satisfactionpublishedVersio