Using UAVs for vehicle tracking and collision risk assessment at intersections

ABSTRACT Assessing collision risk is a critical challenge to effective traffic safety management. The deployment of unmanned aerial vehicles (UAVs) to address this issue has shown much promise, given their wide visual field and movement flexibility. This research demonstrates the application of UAVs and V2X connectivity to track the movement of road users and assess potential collisions at intersections. The study uses videos captured by UAVs. The proposed method combines deeplearning based tracking algorithms and time-to-collision tasks. The results not only provide beneficial information for vehicle's recognition of potential crashes and motion planning but also provided a valuable tool for urban road agencies and safety management engineers. INTRODUCTION It has been prognosticated that unmanned aerial vehicles (UAVs) will play a vital role in various application or context areas of transportation systems management. This is motivated by the success of UAVs in other domains including photography, photogrammetry, agriculture, terrain mapping, monitoring, disaster relief and rescue operations, and recreational purposes (1). Due to these applications, the emerging global market for drone-enabled services has been valued by the 2016 Middle East and North Africa Business Report at over $127B (2).