This research project evaluated an algorithm developed in the previous project (Nihan et al., Detector Data Validity), and developed a new data error detection algorithm by employing a video imaging data collection technology called Autoscope™. This new algorithm was calibrated with data from the Seattle metropolitan area. It helps to determine the reliability of 20-second loop detector data that are used for the operation of the ramp metering system. Both the existing and the new algorithms were tested for their effectiveness with an extensive data set that contains manually simulated erroneous data. The test data were collected from various locations on I-5 that covered different characteristics such as lane type, lane configuration, and geometrics. While both algorithms were effective in screening out hanging-off errors, chattering, and spurious pulses, the new algorithm provides a much more effective detection for hanging-on errors, especially in congested conditions.
The principal findings and recommendations of this research were as follows:
The Autoscope™ system can be used for algorithm development and for calibration of other facilities, such as HOV lanes. It can also be used for real-time data collection, analysis, and traffic control particularly at construction sites, where detection loop operations are usually interrupted.