Citation

Pérez JA, Gonçalves GR, Morillo Barragan JR, Fuentes Ortega P, Caracol Palomo AAM. Heliyon 2024; 10(9): e29709.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.heliyon.2024.e29709

PMID

38698986

PMCID

PMC11064080

Abstract

Investigations into traffic accidents that lead to the determination of their causes and consequences are useful to all interested parties, both in the public and private sectors. One of the phases of investigation is the capture of data enabling the complete reconstruction of the accident scene, which is usually the point at which a conflict arises between the slow process of information gathering and the need to restore normal traffic flow. To reduce to a minimum the time the traffic is halted, this paper follows a methodology to reconstruct traffic accidents and puts forward a series of procedures and tools that are applicable to both large and small scenarios. The methodology uses low-cost UAV-SfM in combination with UAS aerial image capture systems and inexpensive GNSS equipment costing less than €900. This paper describes numerous tests and assessments that were carried out on four potential work scenarios (E-1 and E-2 urban roads with several intersections; E-3, an urban crossing with medium slopes; and E-4, a complex road section with different land morphologies), assessing the impact of using simple or double strip flights and the number of GCPs, their spacing distance and different distribution patterns. From the different configurations tested, the best results were achieved in those offset-type distributions where the GCPs were placed on both sides of the working area and at each end, with a spacing between 100 and 50 m and using double strip flights. Our conclusion is that the application of this protocol would be highly efficient and economical in the reconstruction of traffic accidents, provide simplicity in implementation, speed of capture and data processing, and provide reliable results quite economically and with a high degree of accuracy with RMSE values below 5 cm.

Language: en

Keywords

3D point cloud; Accuracy assessment; Ground control points (GCPs); Traffic accident; Unmanned aerial vehicle (UAV)