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

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.