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An Experimental Study on Real Time Bus Arrival Time Prediction with GPS Data

An Experimental Study on Real Time Bus Arrival Time Prediction with GPS Data PDF Author: Wei-Hua Lin
Publisher:
ISBN:
Category : Bus lines
Languages : en
Pages : 15

Book Description


An Experimental Study on Real Time Bus Arrival Time Prediction with GPS Data

An Experimental Study on Real Time Bus Arrival Time Prediction with GPS Data PDF Author: Wei-Hua Lin
Publisher:
ISBN:
Category : Bus lines
Languages : en
Pages : 15

Book Description


Real-time Bus Arrival Information Systems

Real-time Bus Arrival Information Systems PDF Author: Carol L. Schweiger
Publisher: Transportation Research Board
ISBN: 0309069653
Category : Bus lines
Languages : en
Pages : 71

Book Description
The synthesis describes the state of the practice in real-time bus arrival informations systems, including both U.S. and international experience. The panel for this project chose to focus on bus systems, rather than all transit modes, and on the following six elements of these systems: bus system characteristics; real-time bus arrival information system characteristics, including information about the underlying technology and dissemination media; system prediction, accuracy, and reliability; system costs; customer and media reactions; and institutional and organizational issues associated with the system.

Evaluating the Accuracy of Real-time Bus Arrival Predictions Using GPS Data

Evaluating the Accuracy of Real-time Bus Arrival Predictions Using GPS Data PDF Author: Soyoung Ahn
Publisher:
ISBN:
Category :
Languages : en
Pages : 140

Book Description


Soft Computing and Signal Processing

Soft Computing and Signal Processing PDF Author: Jiacun Wang
Publisher: Springer
ISBN: 9811333939
Category : Technology & Engineering
Languages : en
Pages : 765

Book Description
The book includes research papers on current developments in the field of soft computing and signal processing, selected from papers presented at the International Conference on Soft Computing and Signal Processing (ICSCSP 2018). It features papers on current topics, such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning. It also discusses various aspects of these topics, like technologies, product implementation, and application issues.

Service Science, Management, and Engineering:

Service Science, Management, and Engineering: PDF Author: Gang Xiong
Publisher: Academic Press
ISBN: 0123970377
Category : Business & Economics
Languages : en
Pages : 401

Book Description
The Intelligent Systems Series comprises titles that present state of the art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Service Science, Management, and Engineering presents the latest issues and development in service science. Both theory and applications issues are covered in this book, which integrates a variety of disciplines, including engineering, management, and information systems. These topics are each related to service science from various perspectives, and the book is supported throughout by applications and case studies that showcase best practice and provide insight and guidelines to assist in building successful service systems. Presents the latest research on service science, management and engineering, from both theory and applications perspectives Includes coverage of applications in high-growth sectors, along with real-world frameworks and design techniques Applications and case studies showcase best practices and provide insights and guidelines to those building and managing service systems

The Prediction of Bus Arrival Time Using Automatic Vehicle Location Systems Data

The Prediction of Bus Arrival Time Using Automatic Vehicle Location Systems Data PDF Author: Ran Hee Jeong
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Advanced Traveler Information System (ATIS) is one component of Intelligent Transportation Systems (ITS), and a major component of ATIS is travel time information. The provision of timely and accurate transit travel time information is important because it attracts additional ridership and increases the satisfaction of transit users. The cost of electronics and components for ITS has been decreased, and ITS deployment is growing nationwide. Automatic Vehicle Location (AVL) Systems, which is a part of ITS, have been adopted by many transit agencies. These allow them to track their transit vehicles in real-time. The need for the model or technique to predict transit travel time using AVL data is increasing. While some research on this topic has been conducted, it has been shown that more research on this topic is required. The objectives of this research were 1) to develop and apply a model to predict bus arrival time using AVL data, 2) to identify the prediction interval of bus arrival time and the probabilty of a bus being on time. In this research, the travel time prediction model explicitly included dwell times, schedule adherence by time period, and traffic congestion which were critical to predict accurate bus arrival times. The test bed was a bus route running in the downtown of Houston, Texas. A historical based model, regression models, and artificial neural network (ANN) models were developed to predict bus arrival time. It was found that the artificial neural network models performed considerably better than either historical data based models or multi linear regression models. It was hypothesized that the ANN was able to identify the complex non-linear relationship between travel time and the independent variables and this led to superior results because variability in travel time (both waiting and on-board) is extremely important for transit choices, it would also be useful to extend the model to provide not only estimates of travel time but also prediction intervals. With the ANN models, the prediction intervals of bus arrival time were calculated. Because the ANN models are non parametric models, conventional techniques for prediction intervals can not be used. Consequently, a newly developed computer-intensive method, the bootstrap technique was used to obtain prediction intervals of bus arrival time. On-time performance of a bus is very important to transit operators to provide quality service to transit passengers. To measure the on-time performance, the probability of a bus being on time is required. In addition to the prediction interval of bus arrival time, the probability that a given bus is on time was calculated. The probability density function of schedule adherence seemed to be the gamma distribution or the normal distribution. To determine which distribution is the best fit for the schedule adherence, a chi-squared goodness-of-fit test was used. In brief, the normal distribution estimates well the schedule adherence. With the normal distribution, the probability of a bus being on time, being ahead schedule, and being behind schedule can be estimated.

Algorithms and Architectures for Parallel Processing

Algorithms and Architectures for Parallel Processing PDF Author: Xiang-he Sun
Publisher: Springer
ISBN: 3319111949
Category : Computers
Languages : en
Pages : 711

Book Description
This two volume set LNCS 8630 and 8631 constitutes the proceedings of the 14th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2014, held in Dalian, China, in August 2014. The 70 revised papers presented in the two volumes were selected from 285 submissions. The first volume comprises selected papers of the main conference and papers of the 1st International Workshop on Emerging Topics in Wireless and Mobile Computing, ETWMC 2014, the 5th International Workshop on Intelligent Communication Networks, IntelNet 2014, and the 5th International Workshop on Wireless Networks and Multimedia, WNM 2014. The second volume comprises selected papers of the main conference and papers of the Workshop on Computing, Communication and Control Technologies in Intelligent Transportation System, 3C in ITS 2014, and the Workshop on Security and Privacy in Computer and Network Systems, SPCNS 2014.

Knowledge-Based Intelligent Information and Engineering Systems

Knowledge-Based Intelligent Information and Engineering Systems PDF Author: Mircea Gh. Negoita
Publisher: Springer Science & Business Media
ISBN: 3540232052
Category : Business & Economics
Languages : en
Pages : 962

Book Description
The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Computer-aided Systems in Public Transport

Computer-aided Systems in Public Transport PDF Author: Mark Hickman
Publisher: Springer Science & Business Media
ISBN: 3540733124
Category : Technology & Engineering
Languages : en
Pages : 437

Book Description
This volume consists of selected papers presented at the Ninth International Conference on Computer-Aided Scheduling of Public Transport. Coverage includes the use of computer-aided methods and operations research techniques to improve: information management; network and route planning; vehicle and crew scheduling and rostering; vehicle monitoring and management; and practical experience with scheduling and public transport planning methods.

Feature Papers of Forecasting

Feature Papers of Forecasting PDF Author: Sonia Leva
Publisher: MDPI
ISBN: 3036510303
Category : Science
Languages : en
Pages : 188

Book Description
Nowadays, forecast applications are receiving unprecedent attention thanks to their capability to improve the decision-making processes by providing useful indications. A large number of forecast approaches related to different forecast horizons and to the specific problem that have to be predicted have been proposed in recent scientific literature, from physical models to data-driven statistic and machine learning approaches. In this Special Issue, the most recent and high-quality researches about forecast are collected. A total of nine papers have been selected to represent a wide range of applications, from weather and environmental predictions to economic and management forecasts. Finally, some applications related to the forecasting of the different phases of COVID in Spain and the photovoltaic power production have been presented.