Automatic detection to inventory road slopes using open LiDAR point clouds

The transport infrastructure of a country facilitates the development and growth of its economy and improves the quality of life of its inhabitants. Increasing its resilience to different types of risks to improve performance is becoming more important. In the current context of climate change, natural hazards are more severe and frequent. In this article, we focus on rockfall as a natural hazard for roads that occurs in small areas in the vicinity of natural or cut slopes, causing road safety problems by invading part of the road. This article aims to inventory the slopes along the road, identifying the area of the road which would be invaded in case of a rockfall. A methodology divided into two blocks is proposed. First, for slope detection and inventory, an algorithm is developed based on open LiDAR point clouds analysis. The second block consists of estimating the invaded road area if a rockfall occurs on each of the inventoried slopes, using a combination of RockGIS software and the Monte Carlo method. The methodology was applied in five case studies: three sections on motorways and two sections on national roads. The results obtained for slope detection show higher rates in the case studies analyzing motorways, with a precision of 100%, a recovery rate of greater than 93.4%, and an F1 score of greater than 0.96. The results in the invaded area of the road show that 11 slopes would cause a total cut of the motorway in one of the directions if a rockfall occurs. These results are useful for infrastructure managers to remotely obtain an inventory of road slopes and know which of them would affect road safety. Also, the results can serve as input for the Intelligent Transportation System and allow the exchange of information under the Building Information Model approach.Ministerio de Ciencia, Innovación y Universidades | Ref. PID2019-108816RB-I00Ministerio de Ciencia, Innovación y Universidades | Ref. PRE2020-096222European Commission | Ref. H2020, n. 95533

A top-down approach for a multi-scale identification of risk areas in infrastructures: particularization in a case study on road safety

Introduction: Transport infrastructures have an important function in society and the development of a country. In Spain, the most used modes of traveler transport are road and rail, far ahead of other means of transport such as air or maritime transport. Both rail and road infrastructures can be affected by numerous hazards, endangering their performance and the safety of users. This study proposes a methodology with a multiscale top-down approach to identify the areas affected by fire, landslide, and safety in road and rail infrastructures in Galicia (Northwest Spain).Methodology: The methodology is developed in three steps, coinciding with the three scales considered in this work: network-, system-, and object-level. In the first step, risk areas are identified and prioritized, resulting in the most critical safety risk in a motorway section. This area defines a study scenario composed of a location (A-55 motorway) and the associated risk (road safety). In the second step, the road safety factors within this scenario are selected, hierarchized, and weighted using a combination of Multi-Criteria Decision-Making methods including the Analytical Hierarchy Process and the Best–Worst Method. Finally, a risk map is generated based on the weighting of infrastructure-related safety factors and compared to real historical accident data for validation. The methodology is based on road and risk assessment standards and only information in the public domain is used.Results: Results show that only 3 segments out of 153 were classified incorrectly, which supports a probability higher than 95% of agreement with real data (at 5% significance level). In a conclusion, the overall methodology exhibits a high potential for hazard prevention and road-safety enhancement.Agencia Estatal de Investigación | Ref. PID2019-108816RB-I00Agencia Estatal de Investigación | Ref. PRE2020-09622

Obtaining of variable geometry beam models for steel beams with corrosion

The most common pathology that causes the main maintenance and durability problems in steel structures is corrosion, since it causes the loss of material from the beams that form the structure, diminishing its properties and therefore the general resistance of the structure. After cleaning the corrosion on a beam, its surface becomes very irregular and it is very difficult to measure and extract the geometry of these shapes and surfaces manually. To this end, laser scanning and its subsequent point cloud is a promising method. The objective of this work is to show how obtaining beam models with extruded slices of one beam affected by corrosion for subsequent analysis structural from the laser scanning. The proposed steps were applied and validated in laboratory study cases.Agencia Estatal de Investigación | Ref. RTI2018-095893-B-C21European Regional Development Fund (ERDF) | Ref. EAPA_826/201