详情

Optimal Loop Placement and Models for Length-Based Vehicle Classification and Stop-and-Go Traffic

项目名称：	Optimal Loop Placement and Models for Length-Based Vehicle Classification and Stop-and-Go Traffic
摘要：	Loops are increasingly used for vehicle length-based classification. The Ohio Department of Transportation (ODOT) currently utilizes a number of in-pavement sensors to collect traffic data most of which rely on constant velocity to determine speeds and correctly classify vehicles. The capability of measuring vehicle lengths makes dual-loop detectors a potential real-time data source for enhancing travel demand and freight studies. Accurate data from traffic detectors plays a key role in decision-making and control actions. To increase accuracy of vehicle volume and length based vehicle classification, methods and stands for loops detectors need to be evaluated to provide a basis for developing applicable models and strategies for the distinct travel behaviors and environments of Ohio highways. Upgraded software VEVID (Vehicle Video-Capture Data Collector), developed by Dr. Heng Wei, will allow efficient collection of more accurate trajectory data over time intervals in dilemma zones. The goal of this research is: (1) to construct loop models for length-based vehicle classification under stop-and-go conditions; and (2) to develop standards for optimal loop installations and locations for reliable traffic measurements from loops.
状态：	Completed
资金：	106073.00
资助组织：	Ohio Transportation Consortium
执行机构：	University of Cincinnati
开始时间：	20090306
实际结束时间：	20101130
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management；Planning and Forecasting