Recently, intelligent transportation systems (ITS) are utilizing information and communication technologies to improve transportation systems performance. ITS heavily depends on gathering and processing real-time traffic information. Vehicles queue length at signalized intersection is a significant piece of information towards transportation improvements. Many attempts have been made to estimate vehicles queue length at signalized intersections by using different means such as inductive loop, road side sensors, vehicle-to-infrastructure communications, etc... . The majority of state of the art approaches are suffering from being invasive, high cost to deploy, hard to maintain or limited to modern vehicles. In this project, we utilize Bluetooth simplicity, cost-effectiveness, low maintenance requirements, and privacy preserving nature to develop BlueEye, a location identification system to estimate vehicles queue length at signalized intersections. In fact, the received Bluetooth radio signal strength varies depending on transmitter distance. By providing BlueEye system with the signal strength distribution over vehicles locations at traffic intersection, it becomes able to identify vehicles locations at the site using a probabilistic approach. Despite the noise and randomness associated with the Bluetooth radio signals, and the dissimilarity between mobile devices, BlueEye showed high locating accuracy with limited location error. However, this project is addressing number of challenges such as the impact of surrounding environment on Bluetooth radio signal, Bluetooth devices heterogeneity, and the Bluetooth standards restrictions that strangles system's throughput.