| dc.contributor.author | Soilán Rodríguez, Mario | |
| dc.contributor.author | González Aguilera, Diego | |
| dc.contributor.author | Campo Sánchez, Ana del | |
| dc.contributor.author | Hernández López, David | |
| dc.contributor.author | Pozo Aguilera, Susana del | |
| dc.date.accessioned | 2024-09-10T11:00:04Z | |
| dc.date.available | 2024-09-10T11:00:04Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | Soilán, M., González-Aguilera, D., del-Campo-Sánchez, A., Hernández-López, D., & Del Pozo, S. (2022). Road marking degradation analysis using 3D point cloud data acquired with a low-cost Mobile Mapping System. Automation in Construction, 141, 104446. https://doi.org/10.1016/j.autcon.2022.104446 | es_ES |
| dc.identifier.issn | 0926-5805 | |
| dc.identifier.uri | http://hdl.handle.net/10366/159496 | |
| dc.description.abstract | [EN] Road maintenance is an important task that ensures the availability and correct function of the road infrastructure. This work presents a methodology that, first, offers an empirical radiometric analysis of the Velodyne
VLP-32C laser scanner. Second, it defines a road marking degradation model that estimates the coefficient of
retroreflected luminance (night visibility, RL) using the intensity attribute of 3D point clouds acquired with this
low-cost system. This model is validated and applied to a case study road section of about 6 km in length, where a
continuous degradation map is defined together with data to assist decision-making for preventive and corrective
maintenance. This validation shows that the proposed method is capable of offering good qualitative visualizations of the degradation status of the road markings, as well as detecting those areas with high degradation
(RL< 100 mcd/m2
/lx) that require corrective maintenance. | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Elsevier | es_ES |
| dc.rights | Attribution-4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Mobile LiDAR system | es_ES |
| dc.subject | 3D point cloud | es_ES |
| dc.subject | Road markings | es_ES |
| dc.subject | Road maintenance | es_ES |
| dc.subject | Retroreflectivity degradation | es_ES |
| dc.title | Road marking degradation analysis using 3D point cloud data acquired with a low-cost Mobile Mapping System | es_ES |
| dc.type | info:eu-repo/semantics/article | es_ES |
| dc.subject.unesco | 2511.03 Cartografía de Suelos | es_ES |
| dc.identifier.doi | 10.1016/j.autcon.2022.104446 | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
| dc.journal.title | Automation in Construction | es_ES |
| dc.volume.number | 141 | es_ES |
| dc.page.initial | 1 | es_ES |
| dc.page.final | 11 | es_ES |
| dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es_ES |
| dc.description.project | Publicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024 | |