Individual Vehicle Speed Estimation Using Single Loop Inductive Waveforms PDF Download
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Author: C. Sun
Publisher:
ISBN:
Category : Automobiles
Languages : en
Pages : 30
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Book Description
Author: C. Sun
Publisher:
ISBN:
Category : Automobiles
Languages : en
Pages : 30
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Book Description
Author: Yinhai Wang
Publisher: Elsevier
ISBN: 0128170271
Category : Transportation
Languages : en
Pages : 302
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Book Description
Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. - Synthesizes the newest developments in data-driven transportation science - Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed - Useful for both theoretical and technically-oriented researchers
Author: Jinhua Guo
Publisher:
ISBN:
Category : Kalman filtering
Languages : en
Pages : 32
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Book Description
The ability to collect or estimate accurate speed information is of great importance to a large number of Intelligent Transportation Systems (ITS) applications. Estimating speeds from the widely used single inductive loop sensor has been a difficult, yet important challenge for transportation engineers. Based on empirical evidence observed from the sensor data from two metropolitan regions in Northern Virginia and California, this research effort developed a Kalman filter model to perform speed estimation for congested traffic. Taking advantage of the coexistence of dual loop and single loop stations in typical freeway management systems, a calibration procedure was proposed for seeding and initiating the algorithm. Empirical evaluation showed that the proposed algorithm can produce accurate speed estimates (on the order of 1-3 miles/hour error) under congested traffic conditions.
Author:
Publisher:
ISBN:
Category : Electronic traffic controls
Languages : en
Pages : 132
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Book Description
Author:
Publisher:
ISBN:
Category : Air travel
Languages : en
Pages : 912
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Book Description
Author: Stanley G. Burns
Publisher:
ISBN:
Category : Detectors
Languages : en
Pages : 108
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Book Description
This report provides a summary of results from a multi-year study that includes both the use of inductive loop detectors (ILDs) and magnetoresistive sensors for in-situ vehicle classification. There were strengths and weaknesses noted in both type of sensor systems. Although the magnetoresistive array provides the best vehicle profile resolution, the standard inductive loop detector provides a significant cost, hardware and software complexity, and reliability advantage. The ILD installed base far exceeds the number of magnetoresistive sensors. Several electrical and computer engineering students participated in the study and their contributions are included in the individual chapter headings. Under my direction, these students also presented project work and Research Day conferences at MN/DOT District 1 Headquarters.
Author: National Research Council (U.S.). Transportation Research Board
Publisher:
ISBN:
Category : Information storage and retrieval systems
Languages : en
Pages : 240
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Book Description
Author: Mihriban Sogutlugil
Publisher:
ISBN:
Category :
Languages : en
Pages : 394
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Book Description
Author:
Publisher:
ISBN:
Category : Computer-aided design
Languages : en
Pages : 894
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Book Description
Author: Zhirui Ye
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Flow speed describes general traffic operation conditions on a segment of roadway. It is also used to diagnose special conditions such as congestion and incidents. Accurate speed estimation plays a critical role in traffic management or traveler information systems. Data from loop detectors have been primary sources for traffic information, and single loop are the predominant loop detector type in many places. However, single loop detectors do not produce speed output. Therefore, speed estimation using single loop outputs has been an important issue for decades. This dissertation research presents two methodologies for speed estimation using single loop outputs. Based on findings from past studies and examinations in this research, it is verified that speed estimation is a nonlinear system under various traffic conditions. Thus, a methodology of using Unscented Kalman Filter (UKF) is first proposed for such a system. The UKF is a parametric filtering technique that is suitable for nonlinear problems. Through an Unscented Transformation (UT), the UKF is able to capture the posterior mean and covariance of a Gaussian random variable accurately for a nonlinear system without linearization. This research further shows that speed estimation is a nonlinear non-Gaussian system. However, Kalman filters including the UKF are established based on the Gaussian assumption. Thus, another nonlinear filtering technique for non-Gaussian systems, the Particle Filter (PF), is introduced. By combining the strengths of both the PF and the UKF, the second speed estimation methodology - Unscented Particle Filter (UPF) is proposed for speed estimation. The use of the UPF avoids the limitations of the UKF and the PF. Detector data are collected from multiple freeway locations and the microscopic traffic simulation program CORSIM. The developed methods are applied to the collected data for speed estimation. The results show that both proposed methods have high accuracies of speed estimation. Between the UKF and the UPF, the UPF has better performance but has higher computation cost. The improvement of speed estimation will benefit real-time traffic operations by improving the performance of applications such as travel time estimation using a series of single loops in the network, incident detection, and large truck volume estimation. Therefore, the work enables traffic analysts to use single loop outputs in a more cost-effective way.
