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Enabling Near Term Prediction Of Status For Intelligent Transportation Systems Management Techniques For Data On Mobile Objects
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Book Synopsis Enabling Near-term Prediction of Status for Intelligent Transportation Systems: Management Techniques for Data on Mobile Objects by : Lasanthi Nilmini Heendaliya
Download or read book Enabling Near-term Prediction of Status for Intelligent Transportation Systems: Management Techniques for Data on Mobile Objects written by Lasanthi Nilmini Heendaliya and published by . This book was released on 2015 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Location Dependent Queries (LDQs) benefit from the rapid advances in communication and Global Positioning System (GPS) technologies to track moving objects' locations, and improve the quality-of-life by providing location relevant services and information to end users. The enormity of the underlying data maintained by LDQ applications - a large quantity of mobile objects and their frequent mobility - is, however, a major obstacle in providing effective and efficient services. Motivated by this obstacle, this thesis sets out in the quest to find improved methods to efficiently index, access, retrieve, and update volatile LDQ related mobile object data and information. Challenges and research issues are discussed in detail, and solutions are presented and examined."--Abstract, page iii.
Book Synopsis Intelligent Transportation Systems: Theory and Practice by : Amit Kumar Tyagi
Download or read book Intelligent Transportation Systems: Theory and Practice written by Amit Kumar Tyagi and published by Springer Nature. This book was released on 2022-11-25 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides fundamental principles of intelligent transport systems with comprehensive insight and state of the art of vehicles, vehicular technology, connecting vehicles, and intelligent vehicles/autonomous intelligent vehicles. The book discusses different approaches for multiple sensor-based multiple-objects tracking, in addition to blockchain-based solutions for building tamper-proof sensing devices. It introduces various algorithms for security, privacy, and trust for intelligent vehicles. This book countermeasures all the drawbacks and provides useful information to students, researchers, and scientific communities. It contains chapters from national and international experts and will be essential for researchers and advanced students from academia, and industry experts who are working on intelligent transportation systems.
Book Synopsis Advanced Intelligent Predictive Models for Urban Transportation by : R. Sathiyaraj
Download or read book Advanced Intelligent Predictive Models for Urban Transportation written by R. Sathiyaraj and published by CRC Press. This book was released on 2022-03-27 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book emphasizes the predictive models of Big Data, Genetic Algorithm, and IoT with a case study. The book illustrates the predictive models with integrated fuel consumption models for smart and safe traveling. The text is a coordinated amalgamation of research contributions and industrial applications in the field of Intelligent Transportation Systems. The advanced predictive models and research results were achieved with the case studies, deployed in real transportation environments. Features: Provides a smart traffic congestion avoidance system with an integrated fuel consumption model. Predicts traffic in short-term and regular. This is illustrated with a case study. Efficient Traffic light controller and deviation system in accordance with the traffic scenario. IoT based Intelligent Transport Systems in a Global perspective. Intelligent Traffic Light Control System and Ambulance Control System. Provides a predictive framework that can handle the traffic on abnormal days, such as weekends, festival holidays. Bunch of solutions and ideas for smart traffic development in smart cities. This book focuses on advanced predictive models along with offering an efficient solution for smart traffic management system. This book will give a brief idea of the available algorithms/techniques of big data, IoT, and genetic algorithm and guides in developing a solution for smart city applications. This book will be a complete framework for ITS domain with the advanced concepts of Big Data Analytics, Genetic Algorithm and IoT. This book is primarily aimed at IT professionals. Undergraduates, graduates and researchers in the area of computer science and information technology will also find this book useful.
Book Synopsis Intelligent Road Transport Systems by : Yunpeng WANG
Download or read book Intelligent Road Transport Systems written by Yunpeng WANG and published by Springer Nature. This book was released on 2022-05-17 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the application of intelligent transportation systems (ITS) has steadily expanded, and has become a hot spot of common interest to universities, scientific research institutes, enterprises and institutions in the transportation field. ITS is the product of the deep integration of modern high-tech in the transportation industry, and its development has accompanied that of modern high-tech. ITS is now also becoming part of the Internet of Things (IoT), and is expected to contribute significantly to making our cities smarter and connecting with other infrastructure. Although there are many monographs and textbooks on intelligent transportation, with the advancement of technology and changes in demand, the key technologies of ITS are also rapidly changing. This book chiefly focuses on the main technologies of ITS, examining them from four perspectives: “sense” (perception and management of traffic information, chapters 2 & 3), “transmission” (interaction of traffic information, chapter 4), “prediction” (prediction of traffic states, chapter 6) and “application” (intelligent transportation applications, chapters 6 through 10). Given its scope, the book can be used as a textbook for undergraduates or graduates, as well as a reference book for research institutes and enterprises. This book emphasizes the use of basis traffic engineering principles and state-of-art methodologies to develop functional designs. It largely reflects the authors’ own experience in adapting these methodologies to ITS design. For example, the book addresses various forms of data collection, models used to predict and evaluate traffic states, comprehensive description in connected vehicles, applications for users and traffic managers, etc. The knowledge gained here will allow designers to estimate the performance differences among alternatives and gauge their potential benefits for functional design purposes. To gain the most from the book, readers should be somewhat familiar with the field of traffic engineering and interested in ITS.
Book Synopsis Data Science Application in Intelligent Transportation Systems by : Lei Lin
Download or read book Data Science Application in Intelligent Transportation Systems written by Lei Lin and published by . This book was released on 2015 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the great progress in information and communications technologies in the past few decades, intelligent transportation systems (ITS) have accumulated vast amounts of data regarding the movement iof people and goods from one location to another. Besides the traditional fixed sensors and GPS devices, new emerging data sources and approaches such as social media and crowdsourcing can be used to extract travel-related data, especially given the wide popularity of mobile devices such as smartphones and tablets, along with their associated apps. To take advantage of all these data and to address the associated challenges, big data techniques, and a new emerging field called data science, are currently receiving more and more attention. Data science employs techniques and theories from many fields such as statistics, machine learning, data mining, analytical models and computer programming to solve the data analysis task. It is therefore timely and important to explore how data science may be best employed for transportation data analysis. In this doctoral study, an integrative approach is proposed for data science applications in ITS. The proposed approach constitutes to an integration of multiple steps in the data analysis process, or integration of different models to build a more powerful one. The integrative approach is applied and tested on two case studies: border crossing delay prediction and traffic accident data analysis. For the first case study, a two-step border crossing delay prediction model is proposed, consisting of a short-term traffic volume prediction model and a multi-server queueing model. As such, this can be seen as an integration of data-driven models and analytical models. For the first step, the short-term traffic volume prediction model, an integration of data "width" decreasing (i.e., data grouping) step and model development step is applied. For model development, a model combination step of a Seasonal Autoregressive Integrated Moving Average Model (SARIMA) and Support Vector Regression (SVR) is applied to realize better performance than when using each single model. In addition, the spinning network (SPN) forecasting paradigm is enhanced for border crossing traffic prediction through the utilization of a dynamic time warping (DTW) similarity metric. The DTW-SPN is shown to yield several advantages such as computational efficiency and accuracy as demonstrated by a promising Mean Absolute Percent Error (MAPE) compared to SARIMA and SVR. This dissertation also proposes the introduction of a data diagnosis step before short-term traffic prediction. In order to develop a methodology for model selection guidance, the author calculated the statistical measures of nonlinearity and complexity for multiple datasets and correlated those to the performances of multiple models SARIMA, SVR and k nearest neighbor (k-NN). Based on this, useful insights are revealed pertaining to parameter setting and model selection based on the data diagnosis results. For the second step, namely the queueing model development, heuristic solutions are presented for two types of queueing models M/E_K/n and BMAP/PH/n. These models take the predicted traffic volume as input, and use it to calculate future waiting time. The analytical results are compared to the results from a VISSIM model simulation results, and shown to be comparable. . Finally, an android smartphone app, which utilizes the two-step border prediction model methodology described above, is developed to collect, share and predict waiting time at the three Niagara Frontier border crossings. For the second case study involving traffic accident data analysis, first an integration of a data "depth" decreasing step and a model development step is once again applied. To do this, the modularity-optimizing community detection algorithm is used to cluster the dataset, and for each cluster, the association rule algorithm is applied to yield insight into traffic accident hotspots and incident clearance time. The results show that more meaningful association rules can be derived when the data is clustered compared to when using the whole dataset directly. Secondly, an integration of a data "width" decreasing step (variable selection) and model development step is applied for real-time traffic accident risk prediction. For this, a novel variable selection method based on the Frequent Pattern tree (FP tree) algorithm is proposed and tested, before applying Bayesian networks and the k-NN algorithms. The experiment shows the models based on variables selected by FP tree always performed better than those using variables selected by the random forecast method. Lastly, an integration of the data mining model, M5P tree, and the hazard-based duration model (HBDM) statistical method is applied to traffic accident duration prediction. The M5P-HBDM method is shown to be capable of identifying more meaningful factors that impact the traffic accident duration, and to have a better prediction performance, than either M5P or HBDM. The two case studies considered in this dissertation serve to illustrate the advantages of an integrative data science approach to analyzing transportation data. With this approach, invaluable insight is gained that can help solve transportation problems and guide public policy.
Book Synopsis Emerging Cutting-Edge Developments in Intelligent Traffic and Transportation Systems by : M. Shafik
Download or read book Emerging Cutting-Edge Developments in Intelligent Traffic and Transportation Systems written by M. Shafik and published by IOS Press. This book was released on 2024-03-05 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent and development of AI and other new technologies, traffic and transportation have changed enormously in recent years, and the need for more environmentally-friendly solutions is also driving innovation in these fields. This book presents the proceedings of ICITT 2023, the 7th International Conference on Intelligent Traffic and Transportation, held from 18-20 September 2023 in Madrid, Spain. This annual conference is becoming one of the leading international conferences for presenting novel and fundamental advances in the fields of intelligent traffic and transportation. It also serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in intelligent traffic and transportation and related techniques. ICITT welcomes scholars and researchers from all over the world to share experiences and lessons with other enthusiasts, and develop opportunities for cooperation. The 27 papers included here represent an acceptance rate of 64% of submissions received, and were selected following a rigorous review process. Topics covered include autonomous technology; industrial automation; artificial intelligence; machine, deep and cognitive learning; distributed networking; transportation in future smart cities; hybrid vehicle technology; mobility; cyber-physical systems; design and cost engineering; enterprise information management; product design; intelligent automation; ICT-enabled collaborative global manufacturing; knowledge management; product-service systems; optimization; product lifecycle management; sustainable systems; machine vision; Industry 4.0; and navigation systems. Offering an overview of recent research and current practice, the book will be of interest to all those working in the field.
Book Synopsis Data Analytics for Intelligent Transportation Systems by : Mashrur Chowdhury
Download or read book Data Analytics for Intelligent Transportation Systems written by Mashrur Chowdhury and published by Elsevier. This book was released on 2017-04-05 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Includes case studies in each chapter that illustrate the application of concepts covered Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies Contains contributors from both leading academic and commercial researchers Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications
Book Synopsis Moving Objects Management by : Xiaofeng Meng
Download or read book Moving Objects Management written by Xiaofeng Meng and published by Springer Science & Business Media. This book was released on 2011-01-27 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in an age of rapid technological development. The Internet already affects our lives in many ways. Indeed, we continue to depend more, and more intrinsically, on the Internet, which is increasingly becoming a fundamental piece of societal infrastructure, just as water supply, electricity grids, and transportation networks have been for a long time. But while these other infrastructures are relatively static, the Internet is undergoing swift and fundamental change: Notably, the Internet is going mobile. The world has some 6.7 billion humans, 4 billion mobile phones, and 1.7 billion Internet users. The two most populous continents, Asia and Africa, have relatively low Internet penetration and hold the greatest potentials for growth. Their mobile phone users by far outnumber their Internet users, and the numbers are growing rapidly. China and India are each gaining about half a dozen million new phone users per month. Users across the globe as a whole increasingly embrace mobile Internet devices, with smart phone sales are starting to outnumber PC sales. Indeed, these and other facts suggest that the Internet stands to gain a substantial mobile component. This mega trend towards “mobile” is enabled by rapid and continuing advances in key technology areas such as mobile communication, consumer electronics, g- positioning, and computing. In short, this is the backdrop for this very timely book on moving objects by Xiaofeng Meng and Jidong Chen.
Book Synopsis Intelligent Transportation Systems Leveraging Next-generation Mobile Devices, Sensors, and Networks by : Jason Hao Gao
Download or read book Intelligent Transportation Systems Leveraging Next-generation Mobile Devices, Sensors, and Networks written by Jason Hao Gao and published by . This book was released on 2016 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban transportation is becoming increasingly intelligent and connected, with the potential for high societal, economic, and environmental impact as it changes the way we work and live in cities. Mobile apps today already provide navigation, transit prediction, mobility-on-demand, and other transportation services. Other urban transportation challenges, such as managing traffic congestion with high granularity and wide coverage, accessing real-time transportation and city information on-the-go, and deploying driver-less vehicles at scale, are still difficult to address pervasively because existing approaches require costly and slow-to-deploy infrastructure. Our goal is to leverage the technological and marketplace forces of the mobile revolution to build and rapidly deploy pervasive, widespread, infrastructure-less intelligent transportation systems (ITS) that can address the needs of future smart cities. This thesis presents fully-integrated hardware and software systems with working, phone-based prototype deployments in cities. By focusing on pushing new technologies into the device rather than infrastructure, we can realize future ITS for smart cities more rapidly. Together, these systems enable a foundation for resilient, next-generation ITS apps that blur the line between city and software. In the first part of this thesis, we observe the trend of increasingly diverse and varied wireless communications interfaces available on mobile phones, and design and build a prototype of an 802.11p radio that is suited for the power and size constraints mobile devices, allowing them to communicate directly with each other without routing through a router or cellular network. Our evaluation shows reductions in power consumption of 47-56% compared to an off-the-shelf 802.11p radio, and a significantly reduced system footprint, showing that 802.11p can be integrated as a future wireless communications interface on mobile devices. We then propose and design a future ITS application that leverages device-to-device (D2D) communications to enable highly granular, widespread traffic management in cities: RoadRunner. We evaluate RoadRunner with both simulation studies and an experimental deployment on real vehicles to show that it achieves fine-grained traffic management and reduces traffic congestion, while eliminating the need for the costly and coarse-grained infrastructure of existing traffic management systems. In the second part of this thesis, we observe that mobile computing performance is improving rapidly, and propose that future ITS can eschew the traditional client-server approach and instead leverage the heavy-duty computation and D2D communications on the devices to improve user experience. We propose and design a suitable programming model and framework that seamlessly ties together device-centric computation and communications, allowing mobile app develops to easily develop applications in this proposed paradigm. We build and evaluate this programming framework, DIPLOMA, and an example ITS application on top of it, and demonstrate order-of-magnitude improvements in responsiveness/latency and reduced dependence on infrastructure-centric cellular networking. In the final part of this thesis, we observe that mobile sensing is evolving rapidly and incorporating different sensing modalities. We propose that future ITS can use new sensors, such as laser distance sensors, by leveraging heavy-duty mobile computing performance, and design a low-cost laser distance sensor on a mobile phone. We build and evaluate our laser distance sensor in real-world conditions and on autonomous vehicles, and show that our prototype achieves performance suitable for collision avoidance for driver-less vehicles operating at up to 15-18 km/h, costs a fraction of the cost of other comparable laser distance sensors, and straightforwardly leverages improvements in mobile computing performance.
Book Synopsis Smart Mobility and Intelligent Transportation Systems for Commercial and Hazardous Vehicles by : Naga Swetha Pasupuleti
Download or read book Smart Mobility and Intelligent Transportation Systems for Commercial and Hazardous Vehicles written by Naga Swetha Pasupuleti and published by CRC Press. This book was released on 2024-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume considers the use of smart technologies in commercial and hazardous vehicles, looking at the challenges and solutions to transportation issues that can be solved with such intelligent applications as artificial intelligence, Internet of Things, neural networks, blockchain, machine learning, big data, etc. The book illustrates the use these smart technologies for vehicle pedestrian detection, in the planning of smart cities for traffic patterns, for the improvement of transportation power stations, for smart railway cargo management systems, and more.
Book Synopsis Deep Learning and Big Data for Intelligent Transportation by : Khaled R. Ahmed
Download or read book Deep Learning and Big Data for Intelligent Transportation written by Khaled R. Ahmed and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today's technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle's speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.
Book Synopsis Big Data Transportation Systems by : Guanghui Zhao
Download or read book Big Data Transportation Systems written by Guanghui Zhao and published by World Scientific. This book was released on 2021-07-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a popular science book on big data analytics in intelligent transportation systems. It aims to provide an introduction to big-data transportation starting from an overview on the development of big data transportation in various countries. This is followed by a discussion on the blueprint strategies of big data transportation which include innovative models, planning, transportation logistics, and application case studies. Finally, the book discusses applications of big data transportation platforms.
Book Synopsis Interest Management Scheme and Prediction Model in Intelligent Transportation Systems by : Ying Li
Download or read book Interest Management Scheme and Prediction Model in Intelligent Transportation Systems written by Ying Li and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on two important problems related to DDDAS: interest management (data distribution) and prediction models. In order to reduce communication overhead, we propose a new interest management mechanism for mobile peer-to-peer systems. This approach involves dividing the entire space into cells and using an efficient sorting algorithm to sort the regions in each cell. A mobile landmarking scheme is introduced to implement this sort-based scheme in mobile peer-to-peer systems. The design does not require a centralized server, but rather, every peer can become a mobile landmark node to take a server-like role to sort and match the regions. Experimental results show that the scheme has better computational efficiency for both static and dynamic matching. In order to improve communication efficiency, we present a travel time prediction model based on boosting, an important machine learning technique, and combine boosting and neural network models to increase prediction accuracy. We also explore the relationship between the accuracy of travel time prediction and the frequency of traffic data collection with the long term goal of minimizing bandwidth consumption. Several different sets of experiments are used to evaluate the effectiveness of this model. The results show that the boosting neural network model outperforms other predictors.
Book Synopsis Intelligent Transportation Related Complex Systems and Sensors by : Kyandoghere Kyamakya
Download or read book Intelligent Transportation Related Complex Systems and Sensors written by Kyandoghere Kyamakya and published by MDPI. This book was released on 2021-09-01 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems.
Book Synopsis Smart Societies, Infrastructure, Technologies and Applications by : Rashid Mehmood
Download or read book Smart Societies, Infrastructure, Technologies and Applications written by Rashid Mehmood and published by Springer. This book was released on 2018-07-21 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the First International Conference on Smart Cities, Infrastructures, Technologies and Applications, SCITA 2017, held in Jeddah, Saudi Arabia, in November 2017. The 35 revised full papers were carefully reviewed and selected from 62 submissions. The papers are grouped in topical sections: infrastructure track, e-governance and transportation track, healthcare track, applications track.
Book Synopsis Wavelets in Intelligent Transportation Systems by : Hojjat Adeli
Download or read book Wavelets in Intelligent Transportation Systems written by Hojjat Adeli and published by John Wiley & Sons. This book was released on 2005 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: &Quot;This book shows how wavelets can be used to enhance computational intelligence for chaotic and complex pattern recognition problems. By integrating wavelets with other soft computing techniques such as neurocomputing and fuzzy logic, complicated and noisy pattern recognition problems can be solved effectively. The book focuses on applications in intelligent transportation systems (ITS) where a number of very complicated pattern recognition problems have eluded researchers over the past few decades.". "Wavelets in Intelligent Transportation Systems is an invaluable resource for computational intelligence researchers and transportation engineers involved in the application of advanced computational techniques for ITS."--BOOK JACKET.
Book Synopsis Artificial Intelligence and Smart Vehicles by : Mehdi Ghatee
Download or read book Artificial Intelligence and Smart Vehicles written by Mehdi Ghatee and published by Springer Nature. This book was released on 2023-10-04 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence and Smart Vehicles, ICAISV 2023, held in Tehran, Iran, during May 24-25, 2023. The 14 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: machine learning, data mining, machine vision, image processing, signal analysis, decision support systems, expert systems, and their applications in smart vehicles.
