The Concept of Lidar Data Quality Assessment in the Context of Bim Modeling

Warchoł, A.

doi:10.5194/isprs-archives-xlii-1-w2-61-2019

Cited by 12 publications

(11 citation statements)

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“…This raises the need for methods and metrics by which the sensors in the simulation can be calibrated to match the sensors used on the real vehicle. Metrics that can assess the performance and quality of sensors can be a valuable tool for such calibration [37]. This will be investigated in an upcoming paper.…”

Section: Discussionmentioning

confidence: 99%

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips

Anih

Kolekar²,

Dargahi

et al. 2023

IEEE Access

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The commercial adoption of Autonomous Vehicles (AVs) and the positive impact they are expected to have on traffic safety depends on appropriate insurance products due to the high potential losses. A significant proportion of these losses are expected to occur from the out-of-distribution risks which arise from situations outside the AV's training experience. Traditional vehicle insurance products (for humandriven vehicles) rely on large data sets of drivers' background and historical incidents. However, the lack of such datasets for AVs makes it imperative to exploit the ability to deploy AVs in simulated environments. In this paper, the data collected by deploying Autonomous Driving Systems (ADSs) in simulated environments is used to develop models to answer two questions: (1) how risky a road section is for an AV to drive? and (2) how does the risk profile vary with different (SAE levels) of ADSs? A simulation pipeline was built on the CARLA (Car Learning to Act): an open-source simulator for autonomous driving research). The environment was specified using parameters such as weather, lighting, traffic density, traffic flow, no. of lanes, etc. A metric -risk factor was defined as a combination of harsh accelerations/braking, inverse Time to Collision, and inverse Time Headway to capture the crashes and near crashes. To assess the difference between ADSs, two ADSs: OpenPilot (Level 2/3) and Pylot (Level 4) were implemented in the simulator. The results (from data and model predictions) show that the trends in the relation between the environment features and risk factor for an AV are similar to those observed for human drivers (e.g., risk increases with traffic flow). The models also showed that junctions were a risk hot-spot for both ADSs. The feature importance of the model revealed that the Level 2/3 ADS is more sensitive to no. of lanes and the Level 4 ADS is sensitive to traffic flow. Such differences in feature importance provide valuable insights into the risk characteristics of different ADSs. In the future, this base model will be extended to include other features (other than the environment), e.g., take over requests, and also address the deficiencies of the current simulation data in terms of insensitivity to weather and lighting.

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Section: Discussionmentioning

confidence: 99%

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips

Anih

Kolekar²,

Dargahi

et al. 2023

IEEE Access

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“…The northeastern façade reflects this evolution over time, showing ashlar masonry interlinked over more than four centuries, which is why it has been taken as the object of study. It has been analysed and connected to the data obtained at documentary level and the geometric data obtained accurately (± 5 mm of error in its total set) [36][37][38], with the data obtained from the lithological studies of its masonry.…”

Section: Discussionmentioning

confidence: 99%

Use of LiDAR Technology for the Study and Analysis of Construction Phases and Deformations in the Gothic Church of Biar (Spain)

Huesca-Tortosa,

Spairani-Berrio,

Saura-Gómez

2023

Heritage

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This work provides new data on the church of Nuestra Señora de la Asunción in Biar, combining the investigation of documentary sources with the analysis of the geometry obtained using LiDAR technology and the study of stone materials. This monument has a Proto-Renaissance façade of great architectural value, as it was the first building in the province of Alicante, in Spain, to use Renaissance decorations at the beginning of the 16th century. Its main façade reflects the four centuries of its construction from the 15th to the 18th centuries. The building has been digitised using LiDAR technology and photogrammetry. The graphic representation of the point cloud obtained from the aforementioned techniques makes it possible to study deformations in colour gradient with respect to a reference plane. The results obtained after the analysis of these data show that the method used in this work has served to detect and corroborate the constructive evolutions of the church obtained from the documentary sources investigated. This work serves as an example for similar works, proposing the incorporation of the analysis of anomalies in the geometry of the facings as a new variable that should be considered to complement the rest of the usual studies, bringing to light deformations and irregularities that at first sight may go unnoticed.

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“…Fully digital characterization, high degree of automation, easy information transmission, processing, expression, and convenient operation. Even though the accuracy of current 3D laser scanners is very high, it is still necessary to strictly ensure that the measurement method of the scanning instrument is accurate to ensure the accuracy of the scanning results [38,39].…”

Section: Methodsmentioning

confidence: 99%

Research on Pathology Information Management of Educational Architectural Heritage Based on Digital Technology: The Case of James Jackson Gymnasium

Wang,

He,

Yan

et al. 2024

Buildings

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Rapid advances in technology have led to an increasing demand for this type of information in the field of cultural heritage and architectural conservation. The article aims to use digital technology to obtain, record, store, and display accurate and intuitive information about architectural heritage for daily management and repair of that heritage. This article conducts a comprehensive and in-depth study of the pathology information from the James Jackson Gymnasium, a typical case of the modern educational architectural heritage of Wuhan. Research contents include obtaining point cloud data through 3D scanning, constructing Building Information Modeling (BIM) 3D models and pathological information models to visualize the affected parts, using the Monument Damage Diagnostic System (MDDS) to establish a pathological information map management system, using virtual simulation technology and digital repair technology to diagnose and repair the affected parts, and establishing a systematic architectural pathology information database to explore the causes of architectural pathology from a multidisciplinary perspective. The authors aim to gradually promote this method and build a systematic pathological information database of architectural heritage. This utilizes the sharing characteristics of information technology to transcend the barriers of time and space and provide important support for heritage protection and pathology management. The Architectural Pathology Information Management System is proposed as an innovative solution to promote the sustainable conservation of architectural heritage through digital technology.

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The Concept of Lidar Data Quality Assessment in the Context of Bim Modeling

Cited by 12 publications

References 0 publications

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips

Use of LiDAR Technology for the Study and Analysis of Construction Phases and Deformations in the Gothic Church of Biar (Spain)

Research on Pathology Information Management of Educational Architectural Heritage Based on Digital Technology: The Case of James Jackson Gymnasium

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