Control Strategy of Frequent Overflow at Intersection Based on Remote Sensing of Unmanned Aerial Vehicle and Vehicle Trajectory Data

Abstract

This paper proposed an effective method, the overflow control strategy, for identifying and controlling the frequent overflow of signalized intersections based on the unmanned aerial vehicle (UAV) remote sensing and vehicle trajectory data that provide multi-dimensional vehicle dynamic data. This strategy can effectively control the overflow intersection and restore normal operation as soon as possible. The strategy was implemented as follows. First, UAV remote sensing was used to quickly find the overflow precursor at the intersection. Second, by using moving trajectory data, the second-flow model of the road section was constructed, and overflow identification indexes were established. Third, considering the traffic demand of controlled intersection and non-overflow phase from the global perspective, the queue length model of the non-overflow phase based on moving trajectory data was established and overflow identification indexes were taken as the objective function to design overflow control strategy set. Finally, according to the sampling rate requirement of moving trajectory data and the field traffic survey, the Changping District in Beijing, which meets the requirements, is selected as the case study for simulation and verification. Usually, when overflow occurs, total delay time and the average number of stop cycles at intersections are relatively high. However, by taking the proposed method, overflow at intersections was identified quickly, and a control strategy was implemented immediately, which alleviated the overflow and eventually eliminated it. The results show that the method proposed in this paper can accurately detect the occurrence of overflow, restrain and eliminate the overflow eventually.