Abstract
Traffic monitoring using Bluetooth MAC addresses has been intensively studied for a decade. Nevertheless, estimation of Origin-Destination volume is still challenging, because the detection probability is unstable and sensitive to the installation positions and environments. With the aim to reveal the factors affecting the detection probability of MAC addresses, this study conducted a series of driving tests to collect detection samples from moving Bluetooth device under various scenarios. The data was then fed in a Logistic Regression Model to estimate the contribution of the factors, such as the installation positions of the scanner and the driving speed of the experiment car, to the detection probability. The results agreed on the significance of distance and angle between the scanner and the car, as well as the car speed, as reported in preceding studies. This study further identified the contribution of driving direction and timeout duration of the scanner. The proposed model successfully estimated the detection probability with a reasonable accuracy.
