Improved Model of Start-Wave Velocity at Intersections Based on Unmanned Aerial Vehicle Data

摘要

The basic parameters involved in current start-wave theoretical models such as density and velocity are difficult to obtain through traditional traffic detection devices. Thus it is hard to apply these theoretical models to the actual verification and prediction for real situation. Unmanned aerial vehicle( UAV),which can shoot aerial video and identify vehicles, roads and other objects, is introduced in this study as a new type of traffic information collection method to gather the real-time data of the necessary parameters. An improved start-wave velocity model is proposed,where the speed and density of traffic flow are converted into vehicle space headway,mean vehicle length and other auxiliary parameters which can be recognized from aerial video or other means. A UAV was used for video shooting at intersections in a flight experiment in order to verify the accuracy of the calculated start-wave velocity.The mean absolute error rate between the calculated velocity and the actual velocity is 2. 277%. Moreover, the improved start-wave velocity model showed much better accuracy than the traditional start-wave velocity model. The results indicate that the improved model is accurate enough to be used for model calibration and validation in signal timing optimization.