Researchers
About the research
This study investigated the viability of using crowdsourced data sets, specifically segment speed data (SSD) and connected vehicle data (CVD), for providing real-time traffic information to the public. After a literature review and interviews with state department of transportation personnel were conducted, the study focused on work zone queue warning systems (QWS). Data from six work zones in Iowa were analyzed and compared in terms of data completeness, accuracy, and latency between SSD, CVD, and sensor data. The SSD showed high data completeness but poor performance in terms of missed and false calls, latency, and queue warning display. CVD, despite having challenges with overnight data coverage, achieved low missed calls and better latency than SSD. A virtual QWS approach was developed to evaluate the effectiveness of combining SSD and CVD. This involved using the archived data as a data feed to determine whether a queue warning would have been displayed. The SSD and CVD were compared against when the sensor data would have supplied a warning. In addition, an option combining both the SSD and CVD was tested. For this test, CVD performed better than SSD. The option combining both CVD and SSD was incrementally better than CVD alone. The study suggests that CVD has some potential for QWS applications, although low data coverage during overnight hours may be challenging. While SSD has good data coverage, it is less effective at identifying congestion. Further refinement in data processing and integration methods may be able to reduce false calls and improve overall performance.