The North Carolina Department of Transportation (NCDOT) Ferry Division operates vessels on seven routes alongthe eastern coast of North Carolina, catering to a variety of users, from tourists to daily commuters. Just like trafficsignals on roadways, queuing and waiting are inherent at ferry terminals, and understanding wait times and queuelengths is crucial for customer satisfaction. Currently, NCDOT ferry customers lack real-time information on waittimes and queue lengths. To address this, the NCDOT Ferry Division aims to implement technology that accuratelymeasures and tracks wait times. The goal of this project are to expand on the findings from the previous NCDOT/ITREstudy that aimed to 1) evaluate and test various options for measuring wait times and 2) recommend a system fortracking and managing wait times to be installed at ferry terminals.
This research conducted another systematic review of the state-of-the-art of technologies that can be used for measuring wait times. This included field tests of different Bluetooth and License Plate Recognition (LPR) technologies from the previous NCDOT /ITRE study to compare their ability to track vehicles and estimate waiting times at ferry terminals. Based on a series of tests, this research revealed that the tested LPR technology has a capture rate of 80 percent and read rate of 86 percent. This suggests a strong likelihood that the LPR technology to achieve a significantly higher match rate than the estimated match rate of Bluetooth devices (ranging from 35 to 55 percent). There are other factors that impact recommendations for use like the physical durability of the devices in which the Bluetooth devices seem to exceed the LPR technology. The wait times found determined from the Bluetooth device data has proprietary post-processing proprietary methods of improving the accuracy of the wait time estimations, though there were still significant deviance from the estimated ground-truth wait times. Therefore, use of the LPR technology is still recommended for tracking and estimating waiting times at ferry terminals due to the robustness and accuracy of the wait time data.
