scholarly journals A SIMPLE TECHNIQUE FOR ROAD SURFACE MODELLING

2016 ◽  
Vol 42 (3) ◽  
pp. 106-114 ◽  
Author(s):  
Khalid l. A. El-Ashmawy
Keyword(s):  
Laser Scanning ◽  
Survey Methods ◽  
Road Surface ◽  
Transverse Cracks ◽  
The Road ◽  
Surface Survey ◽  
Maintenance And Rehabilitation ◽  
Longitudinal Cracks ◽  
Road Mapping

Road surface survey is critical for road engineers to determine the needs of maintenance and rehabilitation for both network and project level study. This paper reviews the road surface survey methods, including image based, photogrammetric and stereo-vision, and mobile mapping systems. The merits and demerits of each method are outlined. The goal of this study is to develop simple software for facilitating the generation of the necessary road surface and distresses maps using surveying data from different sources. The software output has compatibility with known CAD/GIS packages to widen its scope of applications. Methodologies, examples and demonstration related to the use of the developed software and laser scanning data in road mapping for a case study are described. The results showed the flexibilities of the developed software and the proposed method for generating the necessary maps and data for road distresses such as longitudinal cracks, transverse cracks, patch deterioration, potholes, and ravelling. However, the present work shows that using terrestrial laser scanning technologies for modelling the road surface has advantages such as surveying speed, big roads, highways and tunnels. Also it provides the safety for surveyors and the absence of a disruption to traffic. The developed software and methodology are suitable for universities, academic centres and are of great interest to small engineering firms for the generation of road surface maps.

scholarly journals Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

2020 ◽  
Vol 12 (6) ◽  
pp. 942 ◽  
Author(s):  
Maria Rosaria De Blasiis ◽  
Alessandro Di Benedetto ◽  
Margherita Fiani
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Road Traffic ◽  
Single Point ◽  
Three Dimensional ◽  
Point Clouds ◽  
Road Surface ◽  
Important Indicator ◽  
The Road ◽  
Laser Systems

The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and the wellbeing of people. The traditional characterization of the different types of distress often involves complex activities, sometimes inefficient and risky, as they interfere with road traffic. The mobile laser systems (MLS) are now widely used to acquire detailed information about the road surface in terms of a three-dimensional point cloud. Despite its increasing use, there are still no standards for the acquisition and processing of the data collected. The aim of our work was to develop a procedure for processing the data acquired by MLS, in order to identify the localized degradations that mostly affect safety. We have studied the data flow and implemented several processing algorithms to identify and quantify a few types of distresses, namely potholes and swells/shoves, starting from very dense point clouds. We have implemented data processing in four steps: (i) editing of the point cloud to extract only the points belonging to the road surface, (ii) determination of the road roughness as deviation in height of every single point of the cloud with respect to the modeled road surface, (iii) segmentation of the distress (iv) computation of the main geometric parameters of the distress in order to classify it by severity levels. The results obtained by the proposed methodology are promising. The procedures implemented have made it possible to correctly segmented and identify the types of distress to be analyzed, in accordance with the on-site inspections. The tests carried out have shown that the choice of the values of some parameters to give as input to the software is not trivial: the choice of some of them is based on considerations related to the nature of the data, for others, it derives from the distress to be segmented. Due to the different possible configurations of the various distresses it is better to choose these parameters according to the boundary conditions and not to impose default values. The test involved a 100-m long urban road segment, the surface of which was measured with an MLS installed on a vehicle that traveled the road at 10 km/h.

scholarly journals TECHNOLOGICAL MEASURES OF FOREFRONT ROAD IDENTIFICATION FOR VEHICLE COMFORT AND SAFETY IMPROVEMENT

Transport ◽  
2019 ◽  
Vol 34 (3) ◽  
pp. 363-372 ◽  
Author(s):  
Vidas Žuraulis ◽  
Vytenis Surblys ◽  
Eldar Šabanovič
Keyword(s):  
Image Analysis ◽  
Traffic Safety ◽  
Laser Scanning ◽  
Road Surface ◽  
The Road ◽  
Emergency Braking ◽  
Braking System ◽  
Safety Improvement ◽  
Road Friction ◽  
Surface Irregularities

This paper presents the technological measures currently being developed at institutes and vehicle research centres dealing with forefront road identification. In this case, road identification corresponds with the surface irregularities and road surface type, which are evaluated by laser scanning and image analysis. Real-time adaptation, adaptation in advance and system external informing are stated as sequential generations of vehicle suspension and active braking systems where road identification is significantly important. Active and semi-active suspensions with their adaptation technologies for comfort and road holding characteristics are analysed. Also, an active braking system such as Anti-lock Braking System (ABS) and Autonomous Emergency Braking (AEB) have been considered as very sensitive to the road friction state. Artificial intelligence methods of deep learning have been presented as a promising image analysis method for classification of 12 different road surface types. Concluding the achieved benefit of road identification for traffic safety improvement is presented with reference to analysed research reports and assumptions made after the initial evaluation.

scholarly journals AUTOMATIC EXTRACTION OF ROAD SURFACE AND CURBSTONE EDGES FROM MOBILE LASER SCANNING DATA

2015 ◽  
Vol XL-4/W5 ◽  
pp. 119-124 ◽  
Author(s):  
A. Miraliakbari ◽  
M. Hahn ◽  
S. Sok
Keyword(s):  
Laser Scanning ◽  
Accuracy Assessment ◽  
Laser Scanner ◽  
Region Growing ◽  
Ground Truth ◽  
Road Surface ◽  
Automatic Extraction ◽  
Jump Detection ◽  
The Road ◽  
On The Road

We present a procedure for automatic extraction of the road surface from geo-referenced mobile laser scanning data. The basic assumption of the procedure is that the road surface is smooth and limited by curbstones. Two variants of jump detection are investigated for detecting curbstone edges, one based on height differences the other one based on histograms of the height data. Region growing algorithms are proposed which use the irregular laser point cloud. Two- and four-neighbourhood growing strategies utilize the two height criteria for examining the neighborhood. Both height criteria rely on an assumption about the minimum height of a low curbstone. Road boundaries with lower or no jumps will not stop the region growing process. In contrast to this objects on the road can terminate the process. Therefore further processing such as bridging gaps between detected road boundary points and the removal of wrongly detected curbstone edges is necessary. Road boundaries are finally approximated by splines. <br><br> Experiments are carried out with a ca. 2 km network of smalls streets located in the neighbourhood of University of Applied Sciences in Stuttgart. For accuracy assessment of the extracted road surfaces, ground truth measurements are digitized manually from the laser scanner data. For completeness and correctness of the region growing result values between 92% and 95% are achieved.

scholarly journals COMPARISON OF HIGH AND LOW DENSITY AIRBORNE LIDAR DATA FOR FOREST ROAD QUALITY ASSESSMENT

2016 ◽  
Vol III-8 ◽  
pp. 167-172
Author(s):  
K. Kiss ◽  
J. Malinen ◽  
T. Tokola
Keyword(s):  
Laser Scanning ◽  
High Density ◽  
Road Surface ◽  
Airborne Laser Scanning ◽  
Low Density ◽  
Surface Wear ◽  
Forest Roads ◽  
Density Data ◽  
The Road ◽  
Airborne Laser

Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31–92%) than on low-density data (25–40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.

scholarly journals Case Study: Road Embankment Foundation on Weak Organic Soils

2021 ◽  
Vol 1203 (3) ◽  
pp. 032092
Author(s):  
Stanisław Majer
Keyword(s):  
Low Cost ◽  
Mining Area ◽  
Organic Soils ◽  
Processing Plant ◽  
The Road ◽  
Additional Layer ◽  
Favorable Conditions ◽  
Longitudinal Cracks ◽  
The 19Th Century

Abstract The paper presents the problem of embankment foundation during reconstruction and extension of regional road 110 on the section Witomierz - Grądy. On this section the road crosses the valley of meltwater formed during the last Weichselian glaciation. It is a watershed area between the streams Stuchowska Struga and Otoczka Reska. In the Holocene a 961 ha fen peat called Wielki Smogorze has been formed. There are favorable conditions in the area for the formation of fen peats. The thickness of the peats is over 4 m, reaching almost 8.0 m in its peak. Since 1964 the Przybiernówko-Grądy II deposit (402 ha) is continuously exploited. Currently, the deposit is being used by a company called "Lasland". Extraction is conducted on the basis of a relevant concession within a designated mining area of 242.9 ha. The mining concession is valid until the end of 2030. The pits are deep and are located on both sides of the regional road no. 110. Peat is transported by narrow-gauge railroad to the nearby processing plant, where it is sieved, sorted and packed. Based on the analysis of available archival materials, the road as found today was functioning already in the middle of the 19th century. In the 1970s the road was widened to 6.0m In 2003 due to the bad condition of the surface the asphalt layer was renovated by applying a grid and new asphalt layers. During the renovation longitudinal cracks have been reported and there were problems with the compaction of the mix. The direct cause was the shallow layer of peat located just 1.1 - 1.3 m under the road. Conducted renovation did not bring expected results, so in 2019 the documentation for the reconstruction of the road was prepared. Different methods of road foundation were analyzed, from soil replacement through the use of piles. In the end the decision was made to directly settle the embankment with the use of geosynthetics. This study presents a selected solution and shows the results of calculations. Changes during the execution of the reconstruction were discussed. The applied solution allowed for simultaneous functioning of the mining plant and reconstruction of the regional road on the section of 1.2 km. geotextiles and geonets were used. The main argument for such solution was relatively low cost of reconstruction and time of execution. During construction there were problems with obtaining the parameters on the substructure for asphalt layers. Two alternative solutions were proposed, one of which required increasing the thickness of embankment reinforced with geo-mesh and an additional layer of CBGM mix substructure. The solution allowed to meet the design requirements and complete the reconstruction according to the plan without any problems.

scholarly journals Accuracy Comparison of Aerial Lidar, Mobile-Terrestrial Lidar, and UAV Photogrammetric Capture Data Elevations over Different Terrain Types

2020 ◽  
Vol 5 (8) ◽  
pp. 65
Author(s):  
Mandar Khanal ◽  
Mahamudul Hasan ◽  
Nikolaus Sterbentz ◽  
Ryen Johnson ◽  
Jesse Weatherly
Keyword(s):  
Cross Sections ◽  
Road Surface ◽  
Cost Comparison ◽  
Remotely Sensed Data ◽  
Terrestrial Lidar ◽  
The Road ◽  
Accuracy Comparison ◽  
Roadway Design ◽  
High Degree

Lidar and other remotely sensed data such as UAV photogrammetric data capture are being collected and utilized for roadway design on an increasing basis. These methods are desirable over conventional survey due to their efficiency and cost-effectiveness over large areas. A high degree of relative accuracy is achievable through the establishment of survey control. In this case study, elevations (z-values) derived from mobile-terrestrial lidar, aerial lidar, and UAV photogrammetric capture collected with survey control were statistically compared to conventionally surveyed elevations. A cost comparison of the methods is also included. Each set of z-values corresponds to a discrete horizontal point originally part of the conventional survey, collected as cross-sections. These cross-sections were surveyed at three approximate tenth-mile sample locations along US-30 near Georgetown, Idaho. The cross-sections were collected as elevational accuracy verification, and each sample location was selected as an area where the mobile-terrestrial lidar in particular was expected to have more difficulty achieving accuracy off the road surface. Processing and analysis were performed in Esri ArcMap 10.6, and all data were obtained from the Idaho Transportation Department, District 5. Overall, the aerial lidar elevations were found to be closest to conventionally surveyed elevations; on road surface and level terrain, mobile-terrestrial and UAV photogrammetric capture elevations were closer to the conventionally measured elevations.

scholarly journals The Hidden Cairns—A Case Study of Drone-Based ALS as an Archaeological Site Survey Method

2021 ◽  
Vol 13 (10) ◽  
pp. 2010
Author(s):  
Johanna Roiha ◽  
Einari Heinaro ◽  
Markus Holopainen
Keyword(s):  
Laser Scanning ◽  
Forest Cover ◽  
Visual Analysis ◽  
Survey Methods ◽  
Archaeological Site ◽  
High Accuracy ◽  
Survey Method ◽  
Survey Tool ◽  
Site Survey

Conducting archaeological site surveys is time consuming, and large sites may have many small features or structures that are difficult to locate and interpret. Vegetation cover and dense forest hide small structures, like cairns, while at the same time forest cover can cause problems for LiDAR tools. In this case study, drone-based ALS (airborne laser scanning) was tested as an archaeological site survey tool. The research site was complex and located partially in a forested area, which made it possible to evaluate how forest cover affects data. The survey methods used were rather simple: visual analysis, point density calculations in the forest area, and, for site interpretation purposes, digitizing observations and viewshed analysis. Using straightforward methods allowed us to evaluate the minimum time and skills needed for this type of survey. Drone-based ALS provided good results and increased knowledge of the site and its structures. Estimates of the number of cairns interpreted as graves more than doubled as a result of the high-accuracy ALS data. Based on the results of this study, drone-based ALS could be a suitable high-accuracy survey method for large archaeological sites. However, forest cover affects the accuracy, and more research is needed.

scholarly journals COMPARISON OF HIGH AND LOW DENSITY AIRBORNE LIDAR DATA FOR FOREST ROAD QUALITY ASSESSMENT

2016 ◽  
Vol III-8 ◽  
pp. 167-172 ◽  
Author(s):  
K. Kiss ◽  
J. Malinen ◽  
T. Tokola
Keyword(s):  
Laser Scanning ◽  
High Density ◽  
Road Surface ◽  
Airborne Laser Scanning ◽  
Low Density ◽  
Surface Wear ◽  
Forest Roads ◽  
Density Data ◽  
The Road ◽  
Airborne Laser

Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31–92%) than on low-density data (25–40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.

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