Abstract:
To overcome the challenges regarding the fixed place camera installation we introduce a
drone based real time traffic flow parameter estimation. With the recent convenience of
UAV (Unmanned aerial vehicles) videos begins a new smart transportation application.
We Captured the live vehicles traffic data using DJI Phantom 4 pro drone from 8 AM
- 6 PM. We manually annotated the vehicles instances of about 6000 using LabelImg
tool. Our dataset comprises of 6000 images of resolution 3840 x 2160 and 4096 x 2160
and collectively contain 35000 vehicle instances in 17 different categories of vehicles
that are bike, car, bus, suzuki pickup, suzuki bolan, mazda container, Double cabin,
Mini Van, Van, Cart, Tractor, Cement Mixer Container, Water Tank, Pajero, Jeep and
Coaster. These vehicle instances will be annotated by incorporating there purpose and
classes in mind. We manually annotated the speed estimation dataset using on screen
pixel measurement tool. We calibrate the frames with the ground truth real frames
to generate accurate results related to traffic flow parameter. With the help of our
customized vehicles dataset and models, we will be able to detect vehicles of diverse
nature of classes (buses, cars, bikes, trucks, mini-trucks, MPVs) and estimate real time
traffic flow. Now we are capable to find the traffic flow parameters on local highways.
We prepared dataset of different classes and estimate real time traffic flow of vehicles
in transportation industry from different road segments on Kashmir HighWay Vehicle
Dataset known as KHWD. Our model can be used for vehicles detections, traffic flow
estimations, Vehicles speed estimation, anomaly detection, vehicle surveillance, Lane
changing behavior, traffic monitoring. Our model will be applicable where it is difficult
to install camera sensors or radar sensors.
