Traffic Data Collection and Analysis

Traffic Data Collection and Analysis PDF

Author: Alexander French

Publisher: Transportation Research Board National Research

Published: 1986

Total Pages: 68

ISBN-13:

DOWNLOAD EBOOK →

This synthesis will be of interest to traffic engineers, highway planners, and others concerned with the collection of traffic data for traffic engineering studies, for long-range planning, and for evaluation of traffic law enforcement. Information is presented on current practice in traffic data collection and analysis. Although types of highway traffic data collected over the past 50 years have not changed significantly, the quantities, analysis procedure, and presentations of these data have changed as a result of changing policies, operational concerns, and capabilities resulting from new technologies. This report of the Transportation Research Board describes the technology (both hardware and software) that is being used for traffic data collection, and discusses technological advances that have not yet been applied to the acquisition and presentation of traffic data.

Validation of Urban Vehicle Classification Sampling Methodology

Validation of Urban Vehicle Classification Sampling Methodology PDF

Author:

Publisher:

Published: 2005

Total Pages: 104

ISBN-13:

DOWNLOAD EBOOK →

The Mobility Analysis Section of the CDOT Division of Transportation Development (DTD) developed this study to determine whether the cluster count method developed by CDOT is statistically reliable for estimating vehicle classification on urban roadways with average daily traffic volumes exceeding 15,000 vehicles per day. Specifically, CDOT needed to assess whether or not the percentages of vehicles in the 13 FHWA vehicle classifications estimated by the cluster count method differ significantly from expected percentages obtained by 24-hour counts. Since vehicle classification is expensive to perform by manual observation over long periods of time, a statistically reliable method of estimating vehicle type percentages on urban roadways using a less time-consuming method is desirable. The study team utilized the chi-square statistical test to evaluate the similarity between vehicle classifications collected using the cluster count method and 24-hour vehicle counts collected using other data collection methods. Vehicle classification data were collected at 12 sites around Denver, Colorado that represented different roadway classes. The statistical tests between the data collected using the cluster count method and the 24-hour counts revealed that the current cluster count method varied beyond an acceptable statistical similarity to the 24-hour counts. Upon reaching this conclusion, the study panel simulated various changes to the short duration count methodology in an effort to identify the greatest improvement in statistical accuracy. As a result of this study, the recommended short duration vehicle classification methodology requires vehicle counts to be performed for 15 minutes every hour for a 24-hour period. This method exhibits strong statistical similarity to the 24-hour classification counts for all roadway classes and study sites included in this analysis. This collection method is statistically accurate, easy for field personnel to understand and collect, and is about onethird of the cost of a manual 24-hour count. The Mobility Analysis Section of DTD has developed a guidebook on the recommended short duration count methodology that will be available to CDOT staff, data collectors, consultants, and other public agencies. This guidebook outlines how to collect the short duration classification data, process and manage the data, and perform quality control checks.

Data Systems and Travel Survey Methods 2010

Data Systems and Travel Survey Methods 2010 PDF

Author:

Publisher:

Published: 2010

Total Pages: 168

ISBN-13: 9780309142885

DOWNLOAD EBOOK →

"The 17 papers in this issue are concerned with data systems and travel survey methods. Specific topics discussed include the following: evaluating highway safety hardware improvements using benefit-cost analysis; transportation asset management; road inventory data collection and integration; multipurpose location-based services; travel time estimation algorithms; travel data collection with Bluetooth sensors; traffic monitoring of motorcycles; nonintrusive sensors for vehicle classification; validating an automatic bottleneck detection tool; temporal data aggregation; axle load measurement errors; cluster analysis of traffic data; volume data correction for single-channel advance loop detectors; automated vehicle identification at weigh-in-motion inspection stations; and collecting local freight data."--pub. desc.