Multimodal measurement system for road analysis and surveying of road surroundings

Olshausen, Philipp von; Roetner, Moritz; Koch, Carsten; Reiterer, Alexander

doi:10.1117/12.2592033

Cited by 4 publications

(4 citation statements)

References 3 publications

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“…A LiDAR (light detection and ranging) scanner, the clearance profile scanner (CPS) built by Fraunhofer IPM, is mounted at the back of the vehicle. This sensor is used to capture a 3D representation of the streets and their surroundings 3,4,7 . It is a profile scanner with a deflection mirror rotating at 200 Hz and covering about 345° scanning angle.…”

Section: Measurement Instrumentationmentioning

confidence: 99%

“…As an example, data from road surroundings can support the planning of infrastructure projects like the roll-out of glass fibres for telecommunication 2 . Also, the state of roads can automatically and quickly be assessed 3,4 . The demand for this data is quickly growing so that the usage of mobile platforms like drones and cars, called mobile mapping, is getting more important.…”

Section: Introductionmentioning

confidence: 99%

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Mobile mapping system for high-resolution imaging

Olshausen

Stahl²,

Blattmann³

et al. 2022

Remote Sensing Technologies and Applications in Urban Environments VII

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Mobile mapping vehicles are rapidly gaining in importance as they accelerate the digitization of road surroundings. This data is indispensable for municipalities as a quantification of the state of the art as well as for planning of infrastructure projects. Fast laser scanners for 3D point cloud generation and high-resolution cameras are becoming more readily available, increasing not only data quality but also the amount of acquired raw data. Thus, taking advantage of modern computing power and developing strategies for data handling is getting crucial. In this paper, a measurement vehicle is presented that handles up to 4 GB/s of raw data. The vehicle is based on a modular system platform from the Fraunhofer Institute for Physical Measurement Techniques IPM. A Clearance Profile Scanner built by Fraunhofer IPM scans a 345° area almost perpendicular to the driving direction and delivers 3D data with 2 MHz sampling rate and millimeter precision. A high-end positioning solution provides the absolute location at any time. Two off-the-shelf panoramic cameras provide images for standard use cases. As a special feature, six 31 megapixels CMOS cameras acquire highresolution image data from which a panoramic image can also be computed. A special network controller running custom software handles the large amount of network traffic. Additionally, a sophisticated on-board data processing pipeline was developed which performs image compression on a graphic card before the data is stored in permanent memory. Thus, all raw data can be managed and stored for driving speeds up to 144 km/h.

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Section: Measurement Instrumentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mobile mapping system for high-resolution imaging

Olshausen

Stahl²,

Blattmann³

et al. 2022

Remote Sensing Technologies and Applications in Urban Environments VII

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“…For this reason, the demand for 3D data processing is extremely high. The range of interest extends from autonomous driving [1][2][3] to infrastructure mapping [4][5][6][7] up to biomedical analysis [8].…”

Section: Introductionmentioning

confidence: 99%

Reconstructing Geometrical Models of Indoor Environments Based on Point Clouds

Kellner,

Stahl,

Reiterer

2023

Remote Sensing

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In this paper, we present a workflow that combines supervised and unsupervised methods for the reconstruction of geometric models with architectural information from unordered 3D data. Our method uses a downsampling strategy to enrich features to provide scalability for large datasets, increase robustness, and be independent of the sensor used. A Neural Network is then used to segment the resulting point cloud into basic structures. This removes furniture and clutter and preserves the relevant walls, ceilings, floors, and openings. A 2D projection combined with a graph structure is used to find a Region of Interest within the cleaned point cloud, indicating a potential room. Each detected region is projected back into a 3D data patch to refine the room candidates and allow for more complex room structures. The resulting patches are fitted with a polygon using geometric approaches. In addition, architectural features, such as windows and doors, are added to the polygon. To demonstrate that the presented approach works and that the network provides usable results, even with changing data sources, we tested the approach in different real-world scenarios with different sensor systems.

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“…Systems that take less time and are less labor intensive than traditional methods, for example, terrestrial laser scanning (TLS) (7), mobile laser systems (MLS) (2,8), airborne LiDAR systems (ALS) (9), and photogrammetry (10)(11)(12), have begun to be used to obtain road geometry. In addition to these systems, pavement profile scanner technology has been used to measure transverse smoothness in roadworks (13).…”

mentioning

confidence: 99%

Comparison of Unmanned Aerial Vehicle-LiDAR and Image-Based Mobile Mapping System for Assessing Road Geometry Parameters via Digital Terrain Models

Suleymanoglu

Gürtürk

Yilmaz

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Road condition analysis is an important research topic in many fields (such as intelligent transportation, road safety, road design analysis, and traffic analysis) and depends on road geometry parameters such as longitudinal profile and cross-slope. In this study, the extraction of road geometry parameters by unmanned aerial vehicle (UAV) with LiDAR and by a mobile photogrammetric system (MPS) designed by our research group was investigated. The purpose of this study was to obtain geometric parameters (such as road longitudinal profile and cross-slope) by using digital terrain model (DTM) surfaces derived from point cloud data acquired using UAV-LiDAR and MPS. For this purpose, a framework was developed for the extraction and comparison of longitudinal and cross-sectional profiles. First, the ground filtering approach was used to extract ground points and DTM surfaces generated from an appropriate interpolation algorithm by using ground points. Cross-sectional/longitudinal profiles of the road sections were extracted and compared with reference data. A comparison of the longitudinal profiles obtained from DTMs derived from the MPS and from UAV-LiDAR revealed root mean square error values of 1.8 cm and 2.3 cm, respectively. The average deviation of cross-slopes for both surfaces was 0.19% and 0.18%, respectively. These results show that road geometric parameters can be obtained from DTM surfaces with high accuracy. It can be concluded from the results of this study that MPS can be a favorable alternative for studies on road geometry parameters extraction.

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Multimodal measurement system for road analysis and surveying of road surroundings

Cited by 4 publications

References 3 publications

Mobile mapping system for high-resolution imaging

Mobile mapping system for high-resolution imaging

Reconstructing Geometrical Models of Indoor Environments Based on Point Clouds

Comparison of Unmanned Aerial Vehicle-LiDAR and Image-Based Mobile Mapping System for Assessing Road Geometry Parameters via Digital Terrain Models

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