Abstract
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.
Highlights
The automation of the driving task offers the potential to substantially transform the mobility of the future
As this paper focuses on vehicle-pedestrian-simulation, a further investigation has yet to be conducted for additional Vulnerable Road User (VRU), such as e-scooter drivers, skateboarders or wheelchair users
This paper proposes the concept of the OpenDRIVE-CityGML duality
Summary
The automation of the driving task offers the potential to substantially transform the mobility of the future. Higher automation levels can enable the provision of mobility as a service and thereby significantly reduce costs for the customer by sharing capital as well as operating expenses of a vehicle [1,2]. The technology can further contribute to more convenient rides and provide new mobility freedoms for children, seniors and the disabled [3]. A central benefit of automated driving is clearly the increased road safety and the subsequent reduction in road fatalities. Increasing road safety is a mere benefit but rather a moral imperative. The safety has a profound impact on the societal acceptance of the technology [5,6]
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