Real-time Density Estimation on Freeway with Loop Detector and Probe Data

Tony Z. Qiu, Xiao-Yun Lu, Andy H. F. Chow and Steven Shladover

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: Density, speed and flow are the three critical parameters for traffic analysis. Traffic management and control with high performance require accurate estimation/prediction of distance mean speed and density for large spatial and temporal coverage. Speed, including time mean speed and distance mean speed, and flow estimation are relatively easy to be measured and estimated in the practical site, but accurate density estimation is very difficult. Inductive loop detector systems have been widely deployed, it makes better sense to fully adopt available infrastructure to achieve required traffic measurement. As a new promising technology for transportation system, Vehicle Infrastructure Integration (VII) is developing rapidly with the market penetration of cell phone and GPS systems. This report proposed a method for real-time estimation of density using synchronized loop detector data and VII probe vehicle data. Berkeley Highway Laboratory (BHL) loop detector data and the field collected Probe Vehicle data have been used in the method validation. Density estimated from the vehicle-by-vehicle trajectory tracking in Next Generation Simulation (NGSIM) data has also been used as the second data source for validating the algorithm. Comparison of the two results – that form the loop and VII probe vehicle data and that from NGSIM data, showed that they are very close except a small offset which needs further investigation.

Keywords: Engineering; Density Estimation; Vehicle Infrastructure Integration (VII); Loop Detector; Probe Vehicle (search for similar items in EconPapers)
Date: 2009-04-01
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