Urban and traffic data systems, 2013. Volume 2.
- Washington, D.C. : Transportation Research Board, 2013.
- Physical Description:
- vii, 127 pages : illustrations, maps, charts ; 28 cm.
- Additional Creators:
- National Research Council (U.S.). Transportation Research Board
- trb.metapress.com , Free access for TRB sponsors only
- Evaluation of Axle-Based and Length-Based Vehicle Classification Stations - Use of Reduction-Effectiveness Ratios to Evaluate Reduced Traffic Data Collection Plans - Length-Based Vehicle Classification Schemes and Length Bin Boundaries - Locating Traffic Sensors on a Highway Network - Tablet-Based Traffic Counting Application Designed to Minimize Human Error - Sensor Performance in Measuring Vehicle Length - Quality Counts for Pedestrians and Bicyclists - Classification of Bicycle Traffic Patterns in Five North American Cities - Toward a Flexible System for Pedestrian Data Collection with a Microsoft Kinect Motion-Sensing Device - Estimating Annual Average Daily Bicyclists - Generating Site-Specific Axle Load Factors for the Mechanistic-Empirical Pavement Design Guide - Correlation-Based Clustering of Traffic Data for the Mechanistic-Empirical Pavement Design Guide - Hybrid Approach for Clustering Vehicle Classification Data to Support Regional Implementation of the Mechanistic-Empirical Pavement Design Guide - Impact of Various Trucks on Pavement Design and Analysis
- "TRB's Transportation Research Record: Journal of the Transportation Research Board, No. 2339 consists of 14 papers that explore axle-based and length-based vehicle classification stations; an evaluation of reduced traffic data collection plans; length-based vehicle classification schemes and length bin boundaries; the placement of traffic sensors on a highway network; and tablet-based traffic counting applications. This issue of the TRR also examines sensor performance in measuring vehicle length; the quality of counts for pedestrians and bicyclists; bicycle traffic patterns; a flexible system for pedestrian data collection; estimating annual average daily bicyclists; generating site-specific axle load factors and the correlation-based clustering of traffic data for the Mechanistic-Empirical Pavement Design Guide; a hybrid approach for clustering vehicle classification data to support regional implementation of the Mechanistic-Empirical Pavement Design Guide; and the impacts of various trucks on pavement design and analysis."--Online abstract
- Bibliography Note:
- Includes bibliographical references.
- Other Forms:
- Individual TRR papers are available online. TRB sponsors have free access to the full-texts.
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