Techniques for Validating an Automatic Bottleneck Detection Tool Using Archived Freeway Sensor Data

Abstract

Bottlenecks are key features of freeway systems. Their effects in performance and emissions are of increasing importance as congestion worsens in urban areas. In the United States, FHWA has been working to identify and monitor key bottlenecks in each state. In Oregon, a freeway data archive known as the Portland Oregon Regional Transportation Archive Listing archives measured count, density, and speed data from more than 600 locations at 20-s intervals. This archive has enabled development of online freeway performance and reliability analysis tools. This paper describes the rigorous evaluation and refinement of an automated tool for identifying recurrent freeway bottlenecks using historical data within the framework of the data archive. Efforts have focused on identification and display of active bottleneck features by using graphical tools and the selection of optimal variables that enabled careful identification of active bottlenecks. This research aims to detect bottleneck activation historically and, through future work, in real time as well. Ultimately, the results of this research will enhance the prioritization of improvements and implementation of operational strategies on the freeway network.