## 2 Materials and Methods
### Experiment to obtain the IRI  
Figure 3 represents where the survey was conducted. The experiment carried out is detailed below, which aims to obtain IRI values that match reality. This experiment looked to reproduce the proposed methods with the main goal of obtaining IRI values on working routes. Adjacent to the main route, there is a deflection to an area used as a viewpoint and a parking lot. This was defined as the area to be surveyed, so vehicle traffic for this experiment was not a potential parameter or element to consider. Furthermore, there is a low amount of vegetation on the sides of the viewpoint, which facilitates the flyover. IRI values are in the order of 2.5 mm/m for new roads and 12 mm/m for roads with greater use and deterioration. In order to capture this range of deformations, a GSD \(<\) 0.5 cm/px is necessary [3]. This is achieved, for the drone used at heights less than 10 m. For this experiment, the range of heights considered is between 1 to 10 m, where higher-altitude photographs use Nadir approaches to contextualize the environment to be mapped. In contrast, lower-rise ones consider obliqueness of approximately 45 degrees to capture greater details on the pavement surface. The sector evaluated has a left turn and a continuous downward slope of 6%, where the difference in dimensions between the start and end of the sector surveyed is 8 m, the total length of the stretch is 170 m. It should be noted that the weather conditions during the survey were favorable in terms of luminosity and wind speed. The flight plan executed in the first instance corresponded to a flyover at 10 m high, where it a speed of 1.5 m/s was adopted in order to maintain a minimum overlap between photos of 80%, the camera timer was set for obtaining photographs every 2 s, in addition to a Nadir approach. The piloting of the UAV was manual and moved along the central axis of the road in both directions. In a second instance, heights of between 1 and 3 m with oblique focus were considered by 45 degrees, the flight speed was reduced to 1 m/s, and the timer between photographic records was also reduced from 2 to 1 s. Further, to the photographs recorded along the direction of the road, photographs were added, which were taken perpendicular to the longitudinal axis in order to provide higher quality in the generated virtual model. A total of 734 photographs were recorded, and the imaging procedure took about 30 min. For this experiment, the use of GCP was not considered since the UAV equipment had integrated satellite location sensors granting automatic positioning of the model in the global GPS network. Once the set of images that were used to recreate the virtual scenario was obtained, the photographs were loaded into a program that can triangulate the positioning of the UAV equipment, using the metadata information provided by the satellite positioning sensors according to the direction and angle of focus that each image possessed, in order to build virtual 3D models using photogrammetric and SfM techniques. Specifically, the UAV equipment used for this information collection campaign is detailed in Table 1.  
For the correct creation of a 3D model, it was necessary to meet certain computational requirements that allow obtaining higher quality results. The product of the long dimensions of the model is that a high-end processor is required, in conjunction with RAM capacity close to 32 Gb and a graphics card of at least 2 Gb. The Bentley Context Capture software has been used, based on the conclusions of [41], where the lowest levels of error in 3D models have been found in this software, compared to Pix4D and Agisoft PhotoScan. The research considers the limitations of access to these two software, which is  
Figure 3: Analyzed area Mirador Ruta F-190, Source: Google Earth. why no comparative tests have been done with them.