1,083 research outputs found
IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation
During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture
Utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) for overcrowding level risk assessment in railway stations
The railway network plays a significant role (both economically and socially) in assisting the reduction of urban traffic congestion. It also accelerates the decarbonization in cities, societies and built environments. To ensure the safe and secure operation of stations and capture the real-time risk status, it is imperative to consider a dynamic and smart method for managing risk factors in stations. In this research, a framework to develop an intelligent system for managing risk is suggested. The adaptive neuro-fuzzy inference system (ANFIS) is proposed as a powerful, intelligently selected model to improve risk management and manage uncertainties in risk variables. The objective of this study is twofold. First, we review current methods applied to predict the risk level in the flow. Second, we develop smart risk assessment and management measures (or indicators) to improve our understanding of the safety of railway stations in real-time. Two parameters are selected as input for the risk level relating to overcrowding: the transfer efficiency and retention rate of the platform. This study is the world’s first to establish the hybrid artificial intelligence (AI) model, which has the potency to manage risk uncertainties and learns through artificial neural networks (ANNs) by integrated training processes. The prediction result shows very high accuracy in predicting the risk level performance, and proves the AI model capabilities to learn, to make predictions, and to capture risk level values in real time. Such risk information is extremely critical for decision making processes in managing safety and risks, especially when uncertain disruptions incur (e.g., COVID-19, disasters, etc.). The novel insights stemmed from this study will lead to more effective and efficient risk management for single and clustered railway station facilities towards safer, smarter, and more resilient transportation systems
Modern Information Systems
The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this book. Therefore, this book aims to present a number of innovative and recently developed information systems. It is titled "Modern Information Systems" and includes 8 chapters. This book may assist researchers on studying the innovative functions of modern systems in various areas like health, telematics, knowledge management, etc. It can also assist young students in capturing the new research tendencies of the information systems' development
Aeronautical Engineering: A continuing bibliography, supplement 120
This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980
Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways
[Abstract] Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431C 2016-045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED341D R2016/012Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ED431G/01Agencia Estatal de Investigación (España); TEC2013-47141-C4-1-RAgencia Estatal de Investigación (España); TEC2015-69648-REDCAgencia Estatal de Investigación (España); TEC2016-75067-C4-1-
Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013
Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners.
The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation.
With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration
Automatic data for applied railway management : passenger demand, service quality measurement, and tactical planning on the London Overground Network
Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 201-209).The broad goal of this thesis is to demonstrate the potential positive impacts of applying automatic data to the management and tactical planning of a modern urban railway. Tactical planning is taken here to mean the set of transport-specific analysis and decisions required to manage and improve a railway with time horizons measured in weeks, months, or up to a year and little or no capital investment requirements. This thesis develops and tests methods to (i) estimate on-train loads from automatic measurements of train payload weight, (ii) estimate origin-destination matrices by combining multiple types of automatic data, (iii) study passenger incidence (station arrival) behavior relative to the published timetable, (iv) characterize service quality in terms of the difference between automatically measured passenger journey times and journey times implied by the published timetable. It does so using (i) disaggregate journey records from an entry- and exit-controlled automatic fare collection system, (ii) payload weight measurements from "loadweigh" sensors in train suspension systems, and (iii) aggregate passenger volumes from electronic station gatelines. The methods developed to analyze passenger incidence behavior and service quality using these data sources include new methodologies that facilitate such analysis under a wide variety of service conditions and passenger behaviors. The above methods and data are used to characterize passenger demand and service quality on the rapidly growing, largely circumferential London Overground network in London, England. A case study documents how a tactical planning intervention on the Overground network was influenced by the application of these methods, and evaluates the outcomes of this intervention. The proposed analytical methods are judged to be successful in that they estimate the desired quantities with sufficient accuracy and are found to make a positive contribution to the Overground's tactical planning process. It is concluded that relative measures of service quality such as the one developed here can be used in cross-sectional analysis to inform tactical planning activity. However, such measures are of less utility for longitudinal evaluation of tactical planning interventions when the basis against which service quality is judged (in this case the timetable) is changed. Under such circumstances, absolute measures, such as total observed passenger journey times, should be used as well.by Michael S. Frumin.S.M.S.M.in Transportatio
Analisis Prediksi Okupansi Jumlah Penumpang Kereta Api dengan Metode Support Vector Regression dan Gaussian Process Regression (Studi Kasus: Kereta Api Argo Parahyangan)
SVR (support vector regression) dan GPR (gaussian process regression) adalah beberapa metode di dalam pembelajaran mesin yang sering digunakan untuk mengakomodasi masalah regresi. SVR dan GPR memiliki keunggulan dibandingkan menggunakan fungsi regresi biasa. Kedua metode ini merupakan model pembelajaran mesin non-deep learning, dimana model pembelajarannya dibangun dengan menggunakan fungsi matematis. Sebagai studi kasus, di dalam makalah diteliti tentang prediksi okupansi penumpang Kereta Api Argo Parahyangan yang dioperasikan oleh PT Kereta Api Indonesia (Persero) untuk melayani lintas kota Bandung–Gambir dan sebaliknya. Penelitian dilakukan dengan menggunakan data berupa jumlah penumpang per hari selama satu tahun pada kelas ekonomi dan kelas eksekutif Kereta Api Argo Parahyangan. Skenario pengujian dilakukan dengan membandingkan antara rata-rata error kuadratik (RMSE) antara prediksi dan target pelatihan dengan metode SVR dan GPR
Maximum risk reduction with a fixed budget in the railway industry
Decision-makers in safety-critical industries such as the railways are frequently faced with the complexity of selecting technological, procedural and operational solutions to minimise staff, passengers and third parties’ safety risks. In reality, the options for maximising risk reduction are limited by time and budget constraints as well as performance objectives.
Maximising risk reduction is particularly necessary in the times of economic recession where critical services such as those on the UK rail network are not immune to budget cuts. This dilemma is further complicated by statutory frameworks stipulating ‘suitable and sufficient’ risk assessments and constraints such as ‘as low as reasonably practicable’. These significantly influence risk reduction option selection and influence their effective implementation.
This thesis provides extensive research in this area and highlights the limitations of widely applied
practices. These practices have limited significance on fundamental engineering principles and
become impracticable when a constraint such as a fixed budget is applied – this is the current reality
of UK rail network operations and risk management. This thesis identifies three main areas of weaknesses to achieving the desired objectives with current risk reduction methods as:
Inaccurate, and unclear problem definition;
Option evaluation and selection removed from implementation subsequently resulting in misrepresentation of risks and costs;
Use of concepts and methods that are not based on fundamental engineering principles, not
verifiable and with resultant sub-optimal solutions.
Although not solely intended for a single industrial sector, this thesis focuses on guiding the railway
risk decision-maker by providing clear categorisation of measures used on railways for risk reduction.
This thesis establishes a novel understanding of risk reduction measures’ application limitations and respective strengths. This is achieved by applying ‘key generic engineering principles’ to measures employed for risk reduction. A comprehensive study of their preventive and protective capability in different configurations is presented.
Subsequently, the fundamental understanding of risk reduction measures and their railway applications, the ‘cost-of-failure’ (CoF), ‘risk reduction readiness’ (RRR), ‘design-operationalprocedural-technical’ (DOPT) concepts are developed for rational and cost-effective risk reduction. These concepts are shown to be particularly relevant to cases where blind applications of economic and mathematical theories are misleading and detrimental to engineering risk management.
The case for successfully implementing this framework for maximum risk reduction within a fixed budget is further strengthened by applying, for the first time in railway risk reduction applications, the dynamic programming technique based on practical railway examples
Railway Engineering: Timetable Planning and Control, Artificial Intelligence and Externalities
This chapter is a case study of the dissemination of railway engineering research in Latin America developed by a railway engineering research group. The leader of the group is a female researcher. The
authors aim to inspire to other women researchers in Latin American and Caribbean (LAC) countries
who are trying to develop research in IT areas, many times facing serious difficulties, incomprehension,
and great challenges. This chapter is divided in set sections like introduction, background, development
of railway engineering research. This third section is divided into subsections like timetable planning
and trains control, characterization of Panama metro line 1, dwelling times, fuzzy logic, artificial intelligence, social-economics railway externalities, and environmental railway externalities. The fourth
section presents the results of the relationship between research activity and teaching of railway engineering obtained in this case study. Finally, the authors present a brief vision about future and emerging
regional trends about railway engineering projects.This chapter is a case study of the dissemination of railway engineering research in Latin America developed by a railway engineering research group. The leader of the group is a female researcher. The
authors aim to inspire to other women researchers in Latin American and Caribbean (LAC) countries
who are trying to develop research in IT areas, many times facing serious difficulties, incomprehension,
and great challenges. This chapter is divided in set sections like introduction, background, development
of railway engineering research. This third section is divided into subsections like timetable planning
and trains control, characterization of Panama metro line 1, dwelling times, fuzzy logic, artificial intelligence, social-economics railway externalities, and environmental railway externalities. The fourth
section presents the results of the relationship between research activity and teaching of railway engineering obtained in this case study. Finally, the authors present a brief vision about future and emerging
regional trends about railway engineering projects
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