Crowdsourced GPS probe data, such as travel time on changeable-message signs and incident detection, have been gaining popularity in recent years as a source for real-time traffic information to driver operations and transportation systems management and operations. Efforts have been made to evaluate the quality of such data from different perspectives. Although such crowdsourced data are already in widespread use in many states, particularly the high traffic areas on the Eastern seaboard, concerns about latency—the time between traffic being perturbed as a result of an incident and reflection of the disturbance in the outsourced data feed—have escalated in importance. Latency is critical for the accuracy of real-time operations, emergency response, and traveler information systems. This paper offers a methodology for measuring probe data latency regarding a selected reference source. Although Bluetooth reidentification data are used as the reference source, the methodology can be applied to any other ground truth data source of choice. The core of the methodology is an algorithm for maximum pattern matching that works with three fitness objectives. To test the methodology, sample field reference data were collected on multiple freeway segments for a 2-week period by using portable Bluetooth sensors as ground truth. Equivalent GPS probe data were obtained from a private vendor, and their latency was evaluated. Latency at different times of the day, impact of road segmentation scheme on latency, and sensitivity of the latency to both speed-slowdown and recovery-from-slowdown episodes are also discussed.
Performance Accuracy of Real-Time GPS Asset Tracking Systems for Timber Haulage Trucks Travelling on Both Internal Forest Road and Public Road Networks
