Improving the Quality of Motorcycle Travel Data Collection.

摘要

This report presents an analysis of traffic counting technologies and data collection protocols to improve the reliability of motorcycle travel data. The technologies included infrared classifiers, inductive loops/piezoelectric sensors, magnetometers, multi-sensor technologies, and tracking video. The report describes the performance of each technology in terms of accuracy, initial cost, portability, and ease of setup and operation. The report also evaluates and validates a hypothesis that motorcycle crash locations are reasonable predictors of traffic volume. A correlation between crash sites and volume enables a Department of Transportation to select traffic counting locations that will yield more accurate data on motorcycle traffic volumes. The report will provide valuable guidance to traffic engineers, transportation planners, and safety professionals who need more accurate data to determine motorcycle exposure risk based on vehicle-miles traveled (VMT).