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Mr. Benedikt Schwab
AUDI AG

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Research Keywords & Expertise

0 Automated Driving
0 Semantic 3D City Models
0 Driving Simulation
0 Sensor Modeling
0 Road Space Modeling

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Journal article
Published: 07 May 2020 in Sustainability
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Automated driving technologies offer the opportunity to substantially reduce the number of road accidents and fatalities. This requires the development of systems that can handle traffic scenarios more reliable than the human driver. The extreme number of traffic scenarios, though, causes enormous challenges in testing and proving the correct system functioning. Due to its efficiency and reproducibility, the test procedure will involve environment simulations to which the system under test is exposed. A combination of traffic, driving and Vulnerable Road User (VRU) simulation is therefore required for a holistic environment simulation. Since these simulators have different requirements and support various formats, a concept for integrated spatio-semantic road space modeling is proposed in this paper. For this purpose, the established standard OpenDRIVE, which describes road networks with their topology for submicroscopic driving simulation and HD maps, is combined with the internationally used semantic 3D city model standard CityGML. Both standards complement each other, and their combination opens the potentials of both application domains—automotive and 3D GIS. As a result, existing HD maps can now be used by model processing tools, enabling their transformation to the target formats of the respective simulators. Based on this, we demonstrate a distributed environment simulation with the submicroscopic driving simulator Virtual Test Drive and the pedestrian simulator MomenTUM at a sensitive crossing in the city of Ingolstadt. Both simulators are coupled at runtime and the architecture supports the integration of automated driving functions.

ACS Style

Benedikt Schwab; Christof Beil; Thomas H. Kolbe. Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems. Sustainability 2020, 12, 3799 .

AMA Style

Benedikt Schwab, Christof Beil, Thomas H. Kolbe. Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems. Sustainability. 2020; 12 (9):3799.

Chicago/Turabian Style

Benedikt Schwab; Christof Beil; Thomas H. Kolbe. 2020. "Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems." Sustainability 12, no. 9: 3799.

Journal article
Published: 23 September 2019 in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Automated driving has received a high degree of public attention in recent years as it will lead to profound changes in mobility, society and urban development. Despite several product announcements from automobile manufacturers and mobility providers, many questions have not yet been answered completely. The need of lane-level HD maps was widely discussed and has been the reason for company acquisitions. HD maps are tailored towards supporting the operation of an automated vehicle. However, the development of this technology also requires road space models, but with a completely different focus and level of detail. Therefore, this article investigates the system development and testing challenges of automated driving. Based on this, requirements of road space models for developing automated driving are derived and gaps to current standards are indicated.

ACS Style

B. Schwab; T. H. Kolbe. REQUIREMENT ANALYSIS OF 3D ROAD SPACE MODELS FOR AUTOMATED DRIVING. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, IV-4/W8, 99 -106.

AMA Style

B. Schwab, T. H. Kolbe. REQUIREMENT ANALYSIS OF 3D ROAD SPACE MODELS FOR AUTOMATED DRIVING. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; IV-4/W8 ():99-106.

Chicago/Turabian Style

B. Schwab; T. H. Kolbe. 2019. "REQUIREMENT ANALYSIS OF 3D ROAD SPACE MODELS FOR AUTOMATED DRIVING." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W8, no. : 99-106.

Conference paper
Published: 01 November 2018 in 2018 21st International Conference on Intelligent Transportation Systems (ITSC)
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This work presents a distributed real-time simulation setup for automated driving function testing in urban environments. In the automotive domain, a large number of simulation frameworks are utilized which are tailored towards a specific application. However, virtual testing of automated driving functions requires a holistic simulation of realistic urban traffic environments. We set up a distributed simulation framework, integrated an ego-vehicle and linked a pedestrian simulator. Further, we developed a pedestrian behavior model, which is able to interact with all agents of the different simulation instances. Our simulation setup was evaluated from different perspectives including a performance test and comparing the developed model to real life data.

ACS Style

Christoph Sippl; Benedikt Schwab; Peter Kielar; Anatoli Djanatliev. Distributed Real-Time Traffic Simulation for Autonomous Vehicle Testing in Urban Environments. 2018 21st International Conference on Intelligent Transportation Systems (ITSC) 2018, 2562 -2567.

AMA Style

Christoph Sippl, Benedikt Schwab, Peter Kielar, Anatoli Djanatliev. Distributed Real-Time Traffic Simulation for Autonomous Vehicle Testing in Urban Environments. 2018 21st International Conference on Intelligent Transportation Systems (ITSC). 2018; ():2562-2567.

Chicago/Turabian Style

Christoph Sippl; Benedikt Schwab; Peter Kielar; Anatoli Djanatliev. 2018. "Distributed Real-Time Traffic Simulation for Autonomous Vehicle Testing in Urban Environments." 2018 21st International Conference on Intelligent Transportation Systems (ITSC) , no. : 2562-2567.