Download or read book Development and Application of Dynamic Models for Predicting Transit Arrival Times written by Yuqing Ding and published by . This book was released on 2000 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic variations in traffic conditions and ridership often have a negative impact in transit operations resulting in the deterioration of schedule/headway adherence and lengthening of passenger wait times. Providing accurate information on transit vehicle arrival times is critical to reduce the negative impacts on transit users. In this study, models for dynamically predicting transit arrival times in urban settings are developed, including a basic model, a Kalman filtering model, link-based and stop-based artificial neural networks (ANNs) and Neural/Dynamic (ND) models. The reliability of these models is assessed by enhancing the microscopic simulation program CORSIM which can calculate bus dwell and passenger wait times based on time-dependent passenger demands and vehicle inter-departure times (headways) at stops. The proposed prediction models are integrated with the enhanced CORSIM individually to predict bus arrival times while simulating the operations of a bus transit route in New Jersey. The reliability analysis of prediction results demonstrates that ANNs are superior to the basic and Kalman filtering models. The stop-based ANN generally predicts more accurately than the link-based ANN. By integrating an ANN (either link-based or stop-based) with the Kalman filtering algorithm, two ND models (NDL and NDS) are developed to decrease prediction error. The results show that the performance of the ND models is fairly close. The NDS model performs better than the NDL model when stop-spacing is relatively long and the number of intersections between a pair of stops is relatively large. In the study, an application of the proposed prediction models to a real-time headway control model is also explored and experimented through simulating a high frequency light rail transit route. The results show that with the accurate prediction of vehicle arrival information from the proposed models, the regularity of headways between any pair of consecutive operating vehicles is improved, while the average passenger wait times at stops are reduced significantly.

Download or read book Use of Neural Network dynamic Algorithms to Predict Bus Travel Times Under Congested Conditions written by I-Jy Steven Chien and published by . This book was released on 2003 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, a dynamic model for predicting bus arrival times is developed using data collected by a real-world Automatic Passenger Counter (APC) system. The model consists of two major elements. The first one is an artificial neural network model for predicting bus travel time between time points for a trip occurring at given time-of-day, day-of-week, and weather condition. The second one is a Kalman filter based dynamic algorithm to adjust the arrival time prediction using up-to-the-minute bus location (operational) information. Test runs show that the developed model is quite powerful in dealing with variations in bus arrival times along the service route.

Download or read book Schedule Based Dynamic Transit Modeling written by Nigel H. M. Wilson and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Schedule-Based Dynamic Transit Modeling: Theory and Applications outlines the new schedule-based dynamic approach to mass transit modeling. In the last ten years the schedule-based dynamic approach has been developed and applied especially for operational planning. It allows time evolution of on-board loads and travel times for each run of each line to be obtained, and uses behavioral hypotheses strictly related to transit systems and user characteristics. It allows us to open new frontiers in transit modelling to support network design, timetable setting, investigation of congestion effects, as well as the assessment of new technologies introduction, such as information to users (ITS technologies). The contributors and editors of the book are leading researchers in the field of transportation, and in this volume they build a solid foundation for developing still more sophisticated models. These future models of mass transit systems will continue to add higher levels of accuracy and sensitivity desired in forecasting the performance of public transport systems.

Download or read book Development of Dynamic Real time Integration of Transit Signal Priority in Coordinated Traffic Signal Control System Using Genetic Algorithms and Artificial Neural Networks written by Mohammad Shareef Ghanim and published by . This book was released on 2008 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Prediction of Bus Arrival Time Using Automatic Vehicle Location Systems Data written by Ran Hee Jeong and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Use of Neural Network dynamic Algorithms to Predict Bus Travel Times Under Congested Conditions written by and published by . This book was released on 2003 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Schedule Based Modeling of Transportation Networks written by Nigel H. M. Wilson and published by Springer Science & Business Media. This book was released on 2008-10-22 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Schedule-Based Modeling of Transportation Networks: Theory and Applications" follows the book Schedule-Based Dynamic Transit Modeling, published in this series in 2004, recognizing the critical role that schedules play in transportation systems. Conceived for the simulation of transit systems, in the last few years the schedule-based approach has been expanded and applied to operational planning of other transportation schedule services besides mass transit, e.g. freight transport. This innovative approach allows forecasting the evolution over time of the on-board loads on the services and their time-varying performance, using credible user behavioral hypotheses. It opens new frontiers in transportation modeling to support network design, timetable setting, and investigation of congestion effects, as well as the assessment of such new technologies, such as users system information (ITS technologies).

Download or read book A Kalman Filter based Dynamic Model for Bus Travel Time Prediction written by Abdulaziz Aldokhayel and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Urban areas are currently facing challenges in terms of traffic congestion due to city expansion and population increase. In some cases, physical solutions are limited. For example, in certain areas it is not possible to expand roads or build a new bridge. Therefore, making public transpiration (PT) affordable, more attractive and intelligent could be a potential solution for these challenges. Accuracy in bus running time and bus arrival time is a key component of making PT attractive to ridership. In this thesis, a dynamic model based on Kalman filter (KF) has been developed to predict bus running time and dwell time while taking into account real-time road incidents. The model uses historical data collected by Automatic Vehicle Location system (AVL) and Automatic Passenger Counters (APC) system. To predict the bus travel time, the model has two components of running time prediction (long and short distance prediction) and dwell time prediction. When the bus closes its doors before leaving a bus stop, the model predicts the travel time to all downstream bus stops. This is long distance prediction. The model will then update the prediction between the bus's current position and the upcoming bus stop based on real-time data from AVL. This is short distance prediction. Also, the model predicts the dwell time at each coming bus stop. As a result, the model reduces the difference between the predicted arrival time and the actual arrival time and provides a better understanding for the transit network which allows lead to have a good traffic management.

Download or read book Departments of Transportation and Housing and Urban Development and Related Agencies Appropriations for 2016 written by United States. Congress. House. Committee on Appropriations. Subcommittee on Transportation, Housing and Urban Development, and Related Agencies and published by . This book was released on 2015 with total page 1508 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Development of Dynamic Travel Time Prediction Models for South Jersey Real Time Motorist Information System written by I-Jy Steven Chien and published by . This book was released on 2004 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of Dynamic Network Models for Intelligent Transportation Systems Applications written by Wŏn-jae Chang and published by . This book was released on 2003 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Transit written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2005 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: "No. 1927 is a five-part volume that focuses on such topics as coordinating public and school transportation in Iowa; using a performance-based approach for funding public transit; introducing contactless, smart card technology in rural New Mexico; evaluating the accuracy and value of automatic passenger counters; and examining the quality of service in an urbanized area in Ontario, Canada, using the revised Transit Capacity and Quality of Service Manual."--pub. website.

Download or read book Advances in Dynamic Network Modeling in Complex Transportation Systems written by Satish V. Ukkusuri and published by Springer Science & Business Media. This book was released on 2013-03-21 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book focuses on recent developments in Dynamic Network Modeling, including aspects of route guidance and traffic control as they relate to transportation systems and other complex infrastructure networks. Dynamic Network Modeling is generally understood to be the mathematical modeling of time-varying vehicular flows on networks in a fashion that is consistent with established traffic flow theory and travel demand theory. Dynamic Network Modeling as a field has grown over the last thirty years, with contributions from various scholars all over the field. The basic problem which many scholars in this area have focused on is related to the analysis and prediction of traffic flows satisfying notions of equilibrium when flows are changing over time. In addition, recent research has also focused on integrating dynamic equilibrium with traffic control and other mechanism designs such as congestion pricing and network design. Recently, advances in sensor deployment, availability of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states and have contributed to new research problems which advance previous models in dynamic modeling. A recent National Science Foundation workshop on “Dynamic Route Guidance and Traffic Control” was organized in June 2010 at Rutgers University by Prof. Kaan Ozbay, Prof. Satish Ukkusuri , Prof. Hani Nassif, and Professor Pushkin Kachroo. This workshop brought together experts in this area from universities, industry and federal/state agencies to present recent findings in this area. Various topics were presented at the workshop including dynamic traffic assignment, traffic flow modeling, network control, complex systems, mobile sensor deployment, intelligent traffic systems and data collection issues. This book is motivated by the research presented at this workshop and the discussions that followed.

Download or read book Transportation Land Use and Integration written by I.M. Schoeman and published by WIT Press. This book was released on 2017-05-30 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many years the integration of the location of land use and activities in spatial systems, as well as the provision of transport in movement of goods, services and people, has been recognized as a challenge amongst various specialists, including: engineers, transportation planners, economists, environmentalists, urban and regional planners and developers. The purpose of this book is to address transportation modelling in terms of technology, techniques and methodology application in context to the interface between transportation systems, land use planning, and environmental challenges and application. The methodology of transportation modelling is applied to international practices and application based on specific case studies, inclusive of public transportation projects; transportation modelling techniques in practice; international research agenda; network design and channel strategies; strategic planning; application of technology in traffic surveys and interpretation; emissions from transportation systems; application of mathematical models and the interface between environment, land use and development in terms of location in space and the resulting activities. Of value to both theorists and practitioners, this book references the integration of transportation modelling techniques within an interdisciplinary environment inside all spatial systems.

Download or read book Panels for Transportation Planning written by Thomas F. Golob and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panels for Transportation Planning argues that panels - repeated measurements on the same sets of households or individuals over time - can more effectively capture dynamic changes in travel behavior, and the factors which underlie these changes, than can conventional cross-sectional surveys. Because panels can collect information on household attributes, attitudes and perceptions, residential and employment choices, travel behavior and other variables - and then can collect information on changes in these variables over time - they help us to understand how and why people choose to travel as they do, and how and why these choices are likely to evolve in the future. This book is designed for a wide audience: survey researchers who seek information on methodological advancements and applications; transportation planners who want an improved understanding of dynamic changes in travel behavior; and instructors of graduate courses in urban and transportation planning, research methods, economics, sociology, and public policy. Each chapter has been prepared to stand alone to illustrate a particular theme or application. The book is divided into topical parts which address the most salient issues in the use of panels for transportation planning: panels as evaluation tools, regional planning applications, accounting for response bias, and modeling and forecasting issues. These parts describe panel applications in the US, Australia, Great Britain, Japan, and the Netherlands. Each chapter is supplemented by extensive references; more than 400 studies, reflecting the work of more than 700 authors, are cited in the text.

Download or read book Dynamics of Vehicles on Roads and Tracks Vol 2 written by Maksym Spiryagin and published by CRC Press. This book was released on 2017-12-06 with total page 1101 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Symposium on Dynamics of Vehicles on Roads and Tracks is the leading international gathering of scientists and engineers from academia and industry in the field of ground vehicle dynamics to present and exchange their latest innovations and breakthroughs. Established in Vienna in 1977, the International Association of Vehicle System Dynamics (IAVSD) has since held its biennial symposia throughout Europe and in the USA, Canada, Japan, South Africa and China. The main objectives of IAVSD are to promote the development of the science of vehicle dynamics and to encourage engineering applications of this field of science, to inform scientists and engineers on the current state-of-the-art in the field of vehicle dynamics and to broaden contacts among persons and organisations of the various countries engaged in scientific research and development in the field of vehicle dynamics and related areas. IAVSD 2017, the 25th Symposium of the International Association of Vehicle System Dynamics was hosted by the Centre for Railway Engineering at Central Queensland University, Rockhampton, Australia in August 2017. The symposium focused on the following topics related to road and rail vehicles and trains: dynamics and stability; vibration and comfort; suspension; steering; traction and braking; active safety systems; advanced driver assistance systems; autonomous road and rail vehicles; adhesion and friction; wheel-rail contact; tyre-road interaction; aerodynamics and crosswind; pantograph-catenary dynamics; modelling and simulation; driver-vehicle interaction; field and laboratory testing; vehicle control and mechatronics; performance and optimization; instrumentation and condition monitoring; and environmental considerations. Providing a comprehensive review of the latest innovative developments and practical applications in road and rail vehicle dynamics, the 213 papers now published in these proceedings will contribute greatly to a better understanding of related problems and will serve as a reference for researchers and engineers active in this specialised field. Volume 2 contains 135 papers under the subject heading Rail.

Download or read book Utilizing Aggregate Transit Demand with Dynamic Transit Assignment Models written by Patrick Todd Jordan and published by . This book was released on 2016 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Activity based models and dynamic traffic assignment models have begun to emerge in the transportation planning industry as an alternative method to the traditional four-step model by more realistically representing trip tours on a finer time scale and depicting the effects of time-dependent traffic flow throughout the network. A barrier, however, for many MPOs across the country to developing ABMs and DTA models is the immense amount of resources required to produce and validate a complete network. Having the capability of using trip tables produced using the four-step model allows MPOs to benefit from the advantages of using a dynamic model while accepting some inaccuracies due to inherent incompatibilities between model methodologies. DTA models have predominately lacked the ability to represent transit apart from pre-specified dwell times, yet current initiatives are focused on developing FAST-TrIPs as a dynamic transit assignment model capable of integrating with DTA software packages to better account for variations in transit ridership. This thesis seeks to act as a guide for MPOs looking to implement existing transit trip tables from a four-step model in conjunction with FAST-TrIPs dynamic transit assignment software to analyze the affects of transit vehicle congestion and schedule reliability at the passenger level. Due to innate assumptions made when modeling transit in the four-step model such as transit schedule and accessibility, modelers must take particular care in characterizing inputs for the dynamic model. Proposals are made related to developing the transit network, processing transit demand, and creating configuration settings for the model. A case study set in Austin, TX uses the regional transit network and transit demand to emphasize particular inputs that are susceptible to causing passengers to go unassigned due to the inconsistency of the models while suggesting opportunities to limit such issues. Due to the high variability in current four-step model structures, the goal of this thesis provides readers with the proper knowledge necessary to develop unique processes applicable to their own region.