1# Library to Find Best eBook for Read
Author : Benjamin André Coifman
Release : 2007
Genre : Detectors
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Vehicle Classification from Single Loop Detectors by : Benjamin André Coifman
Download or read book Vehicle Classification from Single Loop Detectors written by Benjamin André Coifman. This book was released on 2007. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Benjamin André Coifman
Release : 2009
Genre : Vehicle detectors
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Length Based Vehicle Classification on Freeways from Single Loop Detectors by : Benjamin André Coifman
Download or read book Length Based Vehicle Classification on Freeways from Single Loop Detectors written by Benjamin André Coifman. This book was released on 2009. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Seoungbum Kim
Release : 2008
Genre : Vehicle detectors
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Length Based Vehicle Classification from Single Loop Detector Data by : Seoungbum Kim
Download or read book Length Based Vehicle Classification from Single Loop Detector Data written by Seoungbum Kim. This book was released on 2008. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Over the years many vehicle classification schemes have been developed to sort passing vehicles into several classes according to their length, number of axles, axle spacing, number of units or some other combination of vehicle features. Vehicle classification is important for infrastructure management, traffic modeling, and quantifying emissions along highways. Weigh-in-motion (WIM), axle counting, and length from dual loop detectors are commonly used for vehicle classification on freeways.
Author : Stanley G. Burns
Release : 2009
Genre : Detectors
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis In-situ Vehicle Classification Using an ILD and a Magnetoresistive Sensor Array by : Stanley G. Burns
Download or read book In-situ Vehicle Classification Using an ILD and a Magnetoresistive Sensor Array written by Stanley G. Burns. This book was released on 2009. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Sudhir Reddy Itekyala
Release : 2010
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Vehicle Classification Under Congestion Using Dual Loop Data by : Sudhir Reddy Itekyala
Download or read book Vehicle Classification Under Congestion Using Dual Loop Data written by Sudhir Reddy Itekyala. This book was released on 2010. Available in PDF, EPUB and Kindle. Book excerpt: The growing congestion problem on Interstates has been identified as a serious problem for accurate data collection from automatic sensors like Inductive loop detectors (ILD). Traffic speed and vehicle classification data are typically collected by dual-loop detectors on freeways. During congestion, measurement of vehicle lengths which is based on detector ON and OFF timestamps (raw loop event data) often lead to misclassification of vehicle data. Accurate detection of raw event data and modified classification algorithm are increasingly important for higher data accuracy needs for agencies such as Advanced Traffic Management Systems (ATMS) and Advanced Traffic Information Systems (ATIS). Vehicle classification algorithm works on the assumption of constant vehicle speed in the detection area. This assumption is violated during congestion which induces errors in to vehicle length estimates leading to more inaccurate vehicle classification data. This paper unlike in preceding works presents a model which is simple enough to be implemented using existing loop detector hardware. This new model assumes vehicle travels with constant acceleration over loop detection area and thus named as --Constant Acceleration based Vehicle Classification model (CAVC)". This model first identifies traffic flow state and later uses Kinematic equations for estimating vehicle length values. Data is collected by videotaping dual loop station and also simultaneously collecting raw loop event data. Ground truth vehicle data is then extracted using Vehicle Video-Capture Data Collector (VEVID) [Wei et al. 2005] from video data. This improved model (CAVC model) is then validated using ground truth classification data and also compared with the results from existing vehicle classification model for different traffic flow states (under specific scenarios).
