Download or read book Vehicle Classification from Single Loop Detectors written by Benjamin André Coifman and published by . This book was released on 2007 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Length Based Vehicle Classification on Freeways from Single Loop Detectors written by Benjamin André Coifman and published by . This book was released on 2009 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Length Based Vehicle Classification from Single Loop Detector Data written by Seoungbum Kim and published by . This book was released on 2008 with total page 260 pages. 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.
Download or read book In situ Vehicle Classification Using an ILD and a Magnetoresistive Sensor Array written by Stanley G. Burns and published by . This book was released on 2009 with total page 108 pages. 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.
Download or read book Vehicle Classification Under Congestion Using Dual Loop Data written by Sudhir Reddy Itekyala and published by . This book was released on 2010 with total page 90 pages. 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).
Download or read book Length based Vehicle Classification Using Dual loop Data Under Congested Traffic Conditions written by Qingyi Ai and published by . This book was released on 2013 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: The accurate measurement of vehicle classification is a highly valued factor in traffic operation and management, validations of travel demand models, freight studies, and even emission impact analysis of traffic operation. Inductive loops are increasingly used specifically for traffic monitoring at highway traffic data collection sites. Many studies have proven that the vehicle speed can be estimated accurately by using dual-loop data under free traffic condition, and then vehicle lengths can be estimated accurately. The capability of measuring vehicle lengths makes dual-loop detectors a potential real-time data source for vehicle classification. However, the existing dual-loop length-based vehicle classification model was developed with an assumption that the difference of a vehicle's speed on the first and the second single loop is not significant. Under congested traffic flows, vehicles' speeds change frequently and even fiercely, and the assumption cannot be met any more. The outputs of the existing models have a high error rate under non-free traffic conditions (such as synchronized and stop-and-go congestion states). The errors may be contributed by the complex characteristics of traffic flows under congestion; but quantification of such contributing factors remains unclear. In this study, the dual-loop data and vehicle classification models were evaluated with concurred video ground-truth data. The mechanism of the length-based vehicle classification and relevant traffic flow characteristics were tried to be revealed. In order to obtain the ground-truth vehicle event data, the software VEVID (Vehicle Video-Capture Data Collector) was used to extract high-resolution vehicle trajectory data from the videotapes. This vehicle trajectory data was used to identify the errors and reasons of the vehicle classifications resulted from the existing dual-loop model. Meanwhile, a probe vehicle equipped with a Global Positioning System (GPS) data logger was used to set up reference points for VEVID and to collect traffic profile data under varied traffic flow states for developing the new model under stop-and-go traffic flow. The research has proven inability of the existing vehicle classification model in producing satisfactory estimates of vehicle lengths under congestion, i.e., synchronized or stop-and-go traffic states. The Vehicle Classification under Synchronized Traffic Model (VC-Sync model) was developed to estimate vehicle lengths against the synchronized traffic flow and the Vehicle Classification under Stop-and-Go Model (VC-Stog model) was developed to estimate vehicle lengths against the stop-and-go traffic flow. Compare to the existing models, under the congested traffic flows, the newly developed models have improved the accuracy of vehicle length estimation significantly. The contribution of this research is reflected in the following aspects: 1) An innovative VEVID-based approach is developed for evaluating the concurred dual-loop data and resulted vehicle classification and relevant traffic flow characteristics against video-based ground-truth vehicle event trajectory data, which is difficult to conduct with traditional approaches; 2) Innovative vehicle classification models for both synchronized traffic and stop-and-go traffic states are developed through such an evaluation process; 3) The algorithms for processing the dual-loop vehicle event raw data have been improved by considering the influence of traffic flow characteristics;. 4) A GPS-based approach is developed for setting up the reference points in field in conjunction with application of VEVID, which is proven a safety and efficient approach compared to traditional manual approaches. And the GPS-based travel profile data is greatly helpful in developing the new models.
Download or read book Evaluation of Vehicle Classification Equipment written by Richard W. Lyles and published by . This book was released on 1982 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Improved Dual loop Detection System for Collecting Real time Truck Data written by Nancy L. Nihan and published by . This book was released on 2005 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Loop and Length based Vehicle Classification written by Erik D. Minge and published by . This book was released on 2012 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: While most vehicle classification currently conducted in the United States is axle-based, some applications could be supplemented or replaced by length-based data. Common length-based methods are more widespread and can be less expensive, including loop detectors and several types of non-loop sensors (both sidefire and in-road sensors). Loop detectors are the most frequently deployed detection system and most dual-loop installations have the capability of reporting vehicle lengths. This report analyzes various length-based vehicle classification schemes using geographically diverse data sets. This report also conducted field and laboratory tests of loop and non-loop sensors for their performance in determining vehicle length and vehicle speed. The study recommends a four bin length scheme with a fifth bin to be considered in areas with significant numbers of long combination vehicles. The field and laboratory testing found that across a variety of detection technologies, the sensors generally reported comparable length and speed data.
Download or read book Traffic Control Systems Handbook written by and published by . This book was released on 1976 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook, which was developed in recognition of the need for the compilation and dissemination of information on advanced traffic control systems, presents the basic principles for the planning, design, and implementation of such systems for urban streets and freeways. The presentation concept and organization of this handbook is developed from the viewpoint of systems engineering. Traffic control studies are described, and traffic control and surveillance concepts are reviewed. Hardware components are outlined, and computer concepts, and communication concepts are stated. Local and central controllers are described, as well as display, television and driver information systems. Available systems technology and candidate system definition, evaluation and implementation are also covered. The management of traffic control systems is discussed.
Download or read book Improved Vehicle Length Measurement and Classification from Freeway Dual loop Detectors in Congested Traffic written by Lan Wu and published by . This book was released on 2014 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure and for planning future improvements to the transportation network. Balancing the cost of data collection with the fidelity of the measurements, length-based vehicle classification is one of the most common techniques used to collect classified vehicle counts. Typically the length-based vehicle classification process uses a pair of detectors to measure effective vehicle length. The calculation is simple and seems well defined. In particular, most conventional calculations assume that acceleration can be ignored. Unfortunately, at low speeds this assumption is invalid and performance degrades in congestion. As a result of this fact, many operating agencies are reluctant to deploy classification stations on roadways where traffic is frequently congested.
Download or read book Mining Vehicle Classification from Archived Loop Detector Data written by Bo Huang and published by . This book was released on 2014 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vehicle classification data are used in many transportation applications, including: pavement design, environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count stations, supplemented by many more short-term count locations. Due to the high costs involved, the density of monitoring stations is still very low given the lane miles that are covered. This study leveraged the deployed detectors in the Columbus Metropolitan Freeway Management System (CMFMS) to collect and analyze classification data from critical freeways where the Ohio Department of Transportation has not been able to collect much classification data in the past due to site limitations. The CMFMS was deployed in an unconventional manner because it included an extensive fiber optic network, frontloading most of the communications costs, and rather than aggregating the data in the field, the detector stations sent all of the individual per-vehicle actuations (i.e., PVR data) to the traffic management center (TMC). The PVR data include the turn-on and turn-off time for every actuation at each detector at the given station. Our group has collected and archived all of the PVR data from the CMFMS for roughly a decade. The PVR data allows this study to reprocess the original actuations retroactively. As described in this thesis, the research undertook extensive diagnostics and cleaning to extract the vehicle classification data from detectors originally deployed for traffic operations. The work yielded length based vehicle classification data from roughly 40 bi-directional miles of urban freeways in Columbus, Ohio over a continuous monitoring period of up to 10 years. The facilities span I-70, I-71, I-270, I-670, and SR-315, including the heavily congested inner-belt. Prior to this study, these facilities previously had either gone completely without vehicle classification or were only subject to infrequent, short-term counts.
Download or read book Improving Truck and Speed Data Using Paired Video and Single loop Sensors written by and published by . This book was released on 2006 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Investigating Inductive Loop Signature Technology for Statewide Vehicle Classification Counts written by Chen-Fu Liao and published by . This book was released on 2018 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: An inductive loop signature technology was previously developed by a US Department of Transportation (DOT) Small Business Innovation Research (SBIR) program to classify vehicles along a section of the roadway using existing inductive loop detectors installed under the pavement. It was tested and demonstrated in California that the loop signature system could obtain more accurate, reliable and comprehensive traffic performance measures for transportation agencies. Results from the studies in California indicated that inductive loop signature technology was able to re-identify and classify vehicles along a section of roadway and provide reliable performance measures for assessing progress, at the local, State, or national level. This study aimed to take advantage of the outcomes from the loop signature development to validate the performance with ground truth vehicle classification data in the Twin Cities Metropolitan Area (TCMA). Based on the results from individual vehicle class verification, class 2 vehicles had the highest match rate of 90%. Possible causes of classification accuracy for other vehicle classes may include types of loops, sensitivity of inductive loops that generates a shadow loop signal on neighboring lanes, and classification library that was built based on California data. To further understand the causes of loop signature performance and improve the classification accuracy, the author suggests performing additional data verification at a permanent Automatic Traffic Recorder (ATR) site. There is also an opportunity to investigate the classification algorithm and develop an enhanced pattern recognition methodology based on the raw loop signature profile of various types of vehicles in Minnesota.
Download or read book Evaluation of Dual loop Data Accuracy Using Video Ground Truth Data written by Nancy L. Nihan and published by . This book was released on 2002 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Feasibility of Vehicle Classification Using the la Trobe Inductive Loop Vehicle Detector Air 373 1 written by K. J. Pye and published by . This book was released on 1984 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vehicle Classification Systems Study written by M. M. Alexander and published by . This book was released on 1975 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
