Macroscopic Traffic State Estimation for Large Scale Freeway Network Using Wireless Network Data

Macroscopic Traffic State Estimation for Large Scale Freeway Network Using Wireless Network Data PDF Author: Zhijun Qiu
Publisher:
ISBN:
Category :
Languages : en
Pages : 166

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Macroscopic Traffic State Estimation for Large Scale Freeway Network Using Wireless Network Data

Macroscopic Traffic State Estimation for Large Scale Freeway Network Using Wireless Network Data PDF Author: Zhijun Qiu
Publisher:
ISBN:
Category :
Languages : en
Pages : 166

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Dissertation Abstracts International

Dissertation Abstracts International PDF Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 522

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Transport Analytics Based on Cellular Network Signalling Data

Transport Analytics Based on Cellular Network Signalling Data PDF Author: David Gundlegård
Publisher: Linköping University Electronic Press
ISBN: 9176851729
Category :
Languages : en
Pages : 76

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Book Description
Cellular networks of today generate a massive amount of signalling data. A large part of this signalling is generated to handle the mobility of subscribers and contains location information that can be used to fundamentally change our understanding of mobility patterns. However, the location data available from standard interfaces in cellular networks is very sparse and an important research question is how this data can be processed in order to efficiently use it for traffic state estimation and traffic planning. In this thesis, the potentials and limitations of using this signalling data in the context of estimating the road network traffic state and understanding mobility patterns is analyzed. The thesis describes in detail the location data that is available from signalling messages in GSM, GPRS and UMTS networks, both when terminals are in idle mode and when engaged in a telephone call or a data session. The potential is evaluated empirically using signalling data and measurements generated by standard cellular phones. The data used for analysis of location estimation and route classification accuracy (Paper I-IV in the thesis) is collected using dedicated hardware and software for cellular network analysis as well as tailor-made Android applications. For evaluation of more advanced methods for travel time estimation, data from GPS devices located in Taxis is used in combination with data from fixed radar sensors observing point speed and flow on the road network (Paper V). To evaluate the potential in using cellular network signalling data for analysis of mobility patterns and transport planning, real data provided by a cellular network operator is used (Paper VI). The signalling data available in all three types of networks is useful to estimate several types of traffic data that can be used for traffic state estimation as well as traffic planning. However, the resolution in time and space largely depends on which type of data that is extracted from the network, which type of network that is used and how it is processed. The thesis proposes new methods based on integrated filtering and classification as well as data assimilation and fusion that allows measurement reports from the cellular network to be used for efficient route classification and estimation of travel times. The thesis also shows that participatory sensing based on GPS equipped smartphones is useful in estimating radio maps for fingerprint-based positioning as well as estimating mobility models for use in filtering of course trajectory data from cellular networks. For travel time estimation, it is shown that the CEP-67 location accuracy based on the proposed methods can be improved from 111 meters to 38 meters compared to standard fingerprinting methods. For route classification, it is shown that the problem can be solved efficiently for highway environments using basic classification methods. For urban environments the link precision and recall is improved from 0.5 and 0.7 for standard fingerprinting to 0.83 and 0.92 for the proposed method based on particle filtering with integrity monitoring and Hidden Markov Models. Furthermore, a processing pipeline for data driven network assignment is proposed for billing data to be used when inferring mobility patterns used for traffic planning in terms of OD matrices, route choice and coarse travel times. The results of the large-scale data set highlight the importance of the underlying processing pipeline for this type of analysis. However, they also show very good potential in using large data sets for identifying needs of infrastructure investment by filtering out relevant data over large time periods.

Multisensor Data Fusion

Multisensor Data Fusion PDF Author: Hassen Fourati
Publisher: CRC Press
ISBN: 1482263750
Category : Technology & Engineering
Languages : en
Pages : 639

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Book Description
Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world’s leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.

Smart Cities, Green Technologies, and Intelligent Transport Systems

Smart Cities, Green Technologies, and Intelligent Transport Systems PDF Author: Cornel Klein
Publisher: Springer Nature
ISBN: 3031170989
Category : Computers
Languages : en
Pages : 468

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Book Description
​This book includes extended and revised selected papers from the 10th International Conference on Smart Cities and Green ICT Systems, SMARTGREENS 2021, and 7th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2021, held as virtual event, in April 28–30, 2021. The conference was held virtually due to the COVID-19 crisis. The 22 full papers included in this book were carefully reviewed and selected from 140 submissions. The papers present research on advances and applications in the fields of smart cities, electric vehicles, sustainable computing and communications, energy aware systems and technologies, intelligent vehicle technologies, intelligent transport systems and infrastructure, connected vehicles.

Models for Vehicular Traffic on Networks

Models for Vehicular Traffic on Networks PDF Author: Mauro Garavello
Publisher:
ISBN: 9781601330192
Category : Conservation laws (Mathematics)
Languages : en
Pages : 0

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Emission estimation based on traffic models and measurements

Emission estimation based on traffic models and measurements PDF Author: Nikolaos Tsanakas
Publisher: Linköping University Electronic Press
ISBN: 9176850927
Category :
Languages : en
Pages : 143

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Book Description
Traffic congestion increases travel times, but also results in higher energy usage and vehicular emissions. To evaluate the impact of traffic emissions on environment and human health, the accurate estimation of their rates and location is required. Traffic emission models can be used for estimating emissions, providing emission factors in grams per vehicle and kilometre. Emission factors are defined for specific traffic situations, and traffic data is necessary in order to determine these traffic situations along a traffic network. The required traffic data, which consists of average speed and flow, can be obtained either from traffic models or sensor measurements. In large urban areas, the collection of cross-sectional data from stationary sensors is a costefficient method of deriving traffic data for emission modelling. However, the traditional approaches of extrapolating this data in time and space may not accurately capture the variations of the traffic variables when congestion is high, affecting the emission estimation. Static transportation planning models, commonly used for the evaluation of infrastructure investments and policy changes, constitute an alternative efficient method of estimating the traffic data. Nevertheless, their static nature may result in an inaccurate estimation of dynamic traffic variables, such as the location of congestion, having a direct impact on emission estimation. Congestion is strongly correlated with increased emission rates, and since emissions have location specific effects, the location of congestion becomes a crucial aspect. Therefore, the derivation of traffic data for emission modelling usually relies on the simplified, traditional approaches. The aim of this thesis is to identify, quantify and finally reduce the potential errors that these traditional approaches introduce in an emission estimation analysis. According to our main findings, traditional approaches may be sufficient for analysing pollutants with global effects such as CO2, or for large-scale emission modelling applications such as emission inventories. However, for more temporally and spatially sensitive applications, such as dispersion and exposure modelling, a more detailed approach is needed. In case of cross-sectional measurements, we suggest and evaluate the use of a more detailed, but computationally more expensive, data extrapolation approach. Additionally, considering the inabilities of static models, we propose and evaluate the post-processing of their results, by applying quasi-dynamic network loading.

Traffic Signal Systems

Traffic Signal Systems PDF Author:
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 94

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Nonlinear Control Under Nonconstant Delays

Nonlinear Control Under Nonconstant Delays PDF Author: Nikolaos Bekiaris-Liberis
Publisher: SIAM
ISBN: 1611973171
Category : Mathematics
Languages : en
Pages : 293

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Book Description
The authors have developed a methodology for control of nonlinear systems in the presence of long delays, with large and rapid variation in the actuation or sensing path, or in the presence of long delays affecting the internal state of a system. In addition to control synthesis, they introduce tools to quantify the performance and the robustness properties of the designs provided in the book. The book is based on the concept of predictor feedback and infinite-dimensional backstepping transformation for linear systems and the authors guide the reader from the basic ideas of the concept?with constant delays only on the input?all the way through to nonlinear systems with state-dependent delays on the input as well as on system states. Readers will find the book useful because the authors provide elegant and systematic treatments of long-standing problems in delay systems, such as systems with state-dependent delays that arise in many applications. In addition, the authors give all control designs by explicit formulae, making the book especially useful for engineers who have faced delay-related challenges and are concerned with actual implementations and they accompany all control designs with Lyapunov-based analysis for establishing stability and performance guarantees.

Environmental Issues 2007

Environmental Issues 2007 PDF Author: National Research Council (U.S.). Transportation Research Board
Publisher:
ISBN:
Category : Air
Languages : en
Pages : 224

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Book Description
This document discusses the energy and environmental issues of the transportation systems.