Drone-based traffic flow estimation and tracking using computer vision

摘要

According to the National Traffic Information System, there are currently around 11 million registered vehicles on South African roads (National Department of Transport 2014). This number is increasing at an alarming rate, which requires that roads be upgraded continually. The study of traffic flow estimation is used to evaluate how well a particular road segment is accommodating traffic, as well as to determine the priority of road upgrades. Current traffic monitoring techniques make use of intrusive static sensors in the form of inductive loop detectors, IR detectors and radar guns (Thies et al 2013). Visual monitoring is often done manually with the operator watching hours of video footage while counting the cars as they pass through an area. Two of the significant problems associated with the above-mentioned techniques are that they are intrusive and time consuming. Traffic cameras are mounted around most urban areas and are used primarily for security reasons. In the City of Cape Town alone there are around 300 traffic cameras streaming live video directly to the Traffic Message Channel (TMC) database. The cameras cover the majority of the roads throughout Cape Town, and could therefore provide unparalleled access to essential video data.