Model-Based Fault Detection Among Freeway Loop Sensors

Loop detectors are installed along many of the freeways across the state of California to provide real-time and historical traffic data. These data are used by Caltrans for traffic management operations, such as freeway ramp metering, and to evaluate the performance of freeway corridor traffic management systems. These data are also being used to calibrate traffic flow models and to perform model-based predictions of freeway corridor congestion and traffic throughput performance. However, such detection is prone to contain errors and inconsistencies, which can pose problems in further use of the data, and is also of such large quantities that identification of errors can be tedious. This paper proposes a fault detection algorithm associating loop detector data to the cell transmission model to identify significant errors among such detectors. It discusses how such an algorithm would apply to loop detection along the mainline freeway, as well as extends the algorithm to determine errors along on and off ramp detectors. It also gives a real-life example with appropriate identification of detectors in error.