Representing Road Related Laserscanned Data in Curved Regular Grid: A Support to Autonomous Vehicles

Potó, Vivien; Csepinszky, Andràs; Barsi, Árpád

doi:10.5194/isprs-archives-xlii-2-917-2018

Cited by 6 publications

(7 citation statements)

References 2 publications

(2 reference statements)

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“…The flagship of the family is OpenDRIVE, developed to represent the road geometry and its environment. OpenCRG [15] contains an abbreviation for Curved Regular Grid, which is the macroscopic description for road surface in the form of a matrix-like notation [10,12,16,17]. The application of OpenSCENARIO [18] can introduce traffic flow.…”

Section: Road Modelling With Opendrive Standardmentioning

confidence: 99%

Creating an OpenDRIVE Model of the Campus of the Budapest University of Technology and Economics for Automotive Simulations

Barsi

Potó

Lógó

et al. 2020

Period. Polytech. Civil Eng.

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The development of automotive technologies requires quite a significant amount of time and money. To accelerate this procedure, the technology of now is strongly based on computer simulations, where the whole vehicle or its parts can be analyzed in a virtual environment. The behavior of cars, especially equipped with new sensors or assistants, requires long testing, where the automotive simulators can play a cardinal role. The precise vehicular tests request accurate environmental models. These new kinds of models are still standardized; one of the pioneer de facto standards is OpenDRIVE. This standard was initially defined to be able to express all elements with all potential parameters required in high precision simulations. The actual research focused on creating a compliant virtual model based on mobile mapping measurements. A Leica Pegasus Two mobile mapping system was applied to capture field data about the selected pilot area, which is the campus of Budapest University of Technology and Economics (BME). The obtained Lidar point cloud was georeferenced; the merged point cloud is tailored to the driven trajectory, and then it has been evaluated manually. The acquired land use map is converted – similarly manually – into basic road geometry elements: straight lane and bended lane segments. These objects are finally compiled into an XML format, which is compliant with the OpenDRIVE standard. The achieved virtual model has been tested in Driving Scenario Designer of Mathworks Matlab; however, it is promptly ready for use in other widely applied automotive simulators.

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Section: Road Modelling With Opendrive Standardmentioning

confidence: 99%

Creating an OpenDRIVE Model of the Campus of the Budapest University of Technology and Economics for Automotive Simulations

Barsi

Potó

Lógó

et al. 2020

Period. Polytech. Civil Eng.

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“…The preprocessing time cost for extracting the reference line by our previously presented method was less than 20 min. For comparison, a 259.55 m pilot site is used in the experiment in [23]. Their computational time for building the CRG model was 3 h. Since there is no detailed explanation on the composition of computational time, we assumed that the running time during the data preprocessing phase was also counted in this (e.g., manually finding the road surface region, manually finding the reference line, etc.).…”

Section: Building the Crg Modelmentioning

confidence: 99%

“…Therefore, most strategies focus on the transition curves. In [23,24], the authors demonstrate a workflow for representing point cloud data in a curved regular grid model. The input laser-scanned point clouds and geometric description of the road both need strong manual intervention in the preparation phase.…”

Section: Introductionmentioning

confidence: 99%

“…It can also provide a guarantee of high resolution, where the grid resolution can be selected by the user. Secondly, to improve the time and space efficiency compared with the nearest-neighbour search approach used in [23], the two-step method can decrease the storage and query execution time. Furthermore, our previous work results provide precise road surface region point cloud and trajectory points.…”

Section: Introductionmentioning

confidence: 99%

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High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model

Miyazaki

Tamaki

et al. 2019

Sensors

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As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model.

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“…Unity 3D is then used to create realistic visualization with the obtained vehicle parameters. For a higher level of accuracy, an Open Curved Regular Grid (CRG) based test scenario is also implemented, providing a more complex way of testing and validation of the results (Potó et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Estimating Vehicle Suspension Characteristics for Digital Twin Creation with Genetic Algorithm

Ormándi

Varga

Tettamanti

2021

Period. Polytech. Transp. Eng.

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Usage of simulation techniques like Vehicle-in-the-Loop, Scenario-in-the-Loop, and other mixed-reality systems are becoming inevitable in autonomous vehicle development, particularly in testing and validation. These methods rely on using digital twins, realistic representations of real vehicles, and traffic in a carefully rebuilt virtual world. Recreating them precisely in a virtual ecosystem requires many parameters of real vehicles to follow their properties in a simulation. This is especially true for vehicle dynamics, where these parameters have high impact on the simulation results. The paper's objective is to provide a method that can help reverse engineering a real car's suspension characteristics with the help of a genetic algorithm. A detailed description of the method is presented, guiding the reader through the whole process, including the meta-heuristic function's settings and how it interfaces with IPG Carmaker. The paper also presents multiple measurements, which can be effortlessly recreated without expensive devices or the need to disassemble any vehicle parts. Measurements are reproduced in two separate simulation tools with special scenarios providing an efficient way to analyze and verify the results. The provided method creates vehicle suspension characteristics with adequate quality, opening up the possibility to use them in the creation of digital twins or creating virtual traffic with realistic vehicle dynamics for high-quality visualization. Results show satisfying accuracy when tested with OpenCRG.

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Representing Road Related Laserscanned Data in Curved Regular Grid: A Support to Autonomous Vehicles

Cited by 6 publications

References 2 publications

Creating an OpenDRIVE Model of the Campus of the Budapest University of Technology and Economics for Automotive Simulations

Creating an OpenDRIVE Model of the Campus of the Budapest University of Technology and Economics for Automotive Simulations

High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model

Estimating Vehicle Suspension Characteristics for Digital Twin Creation with Genetic Algorithm

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