Ensuring the Accuracy of Traffic Monitoring Using Unmanned Aerial Vehicles Vision Systems

  •  Nikolay Kim    
  •  Nikolay Bodunkov    
  •  Roman Cherkezov    


The paper is dedicated to the organization of traffic monitoring using unmanned aerial vehicles (UAV). It is demonstrated that the monitoring of traffic makes high demands on the accuracy of determining the position of the vehicle on the road.

It is assumed that the purpose of monitoring is detecting specific situations, which may include accident, in particular, car collision; traffic accidents, reducing the bandwidth of the road section; movement of the vehicle, being a threat to other road users.

Detection of such situations requires assessment of the following at the received images:

  • Vehicles position relatively to the road markings;
  • Vehicles position relatively to each other;
  • Vehicles speed.

Review of the literature showed that the existing tools for tracking ground objects movements provide sufficiently accurate assessment of the vehicles coordinates at the images. Thus, an important issue is the estimation of vehicle position with respect to the road, i.e. in the ground coordinate system of the road.

Different options of the vehicle position assessment relatively the road are researched.

Evaluation of the content and accuracy of the standard UAV navigation system showed that the option of monitoring based on the use of UAV position assessment relative to the ground coordinate system and the vehicles is non-implementable because of lack of precision at the standard navigation system, including, corrected using the satellite navigation system.

Assessing the position of the vehicle relative to the roadside is proposed to be made using image processing algorithms, particularly the contour lines highlighting and the Hough algorithm for straight segments highlighting.

The research shows that this option based on direct assessment of the situation with respect to the vehicle position on the road image is physically implementable.

This work is licensed under a Creative Commons Attribution 4.0 License.