Center for Traffic Simulation Studies

Accurate traffic data acquisition is essential for effective traffic surveillance, which is the backbone of advanced transportation management and information systems (ATMIS). Inductive loop detectors (ILDs) are still widely used for traffic data collection in the United States and many other countries. Three fundamental traffic parameters -- speed, volume and occupancy -- can be obtained via single or double (speed-trap) ILDs. Real-time knowledge of such traffic parameters is typically required for use in ATMIS from a single loop detector station, which is the most commonly used. However, vehicle speeds can not be directly obtained. Hence, the ability to accurately estimate vehicle speeds from single loop detectors is of considerable interest. In addition, operating agencies report that conventional loop detectors are unable to achieve volume count accuracies of more than 90%-95%. The main objective of this paper is to demonstrate the improved derivation of fundamental real-time traffic parameters such as speed, volume, occupancy and vehicle class from single loop detectors and inductive signatures.