The standard OpenDRIVE is widely used for exchanging road space models in order to simulate the traffic of a city or individual
driving situations. For modeling continuous road courses at lane level, OpenDRIVE utilizes its own parametric geometry model.
However, violations of continuity requirements due to geometric leaps or kinks can cause the vehicle dynamics simulation to
fail when testing vehicle components. But also defective lane predecessor and successor relations can result in an OpenDRIVE
dataset not being usable as a reference map for vehicle navigation. Since these geometric, topological, and semantic constraints go
beyond the rules encoded in the schema, this article presents a framework and a first implementation for validating OpenDRIVE
datasets. As the lane widths are defined parametrically relative to the reference line of the respective road, lane connectivities at
road transitions are evaluated using explicit geometries derived from the parametric geometry representations. Moreover, a derived
CityGML representation enables a visual inspection of the parametric models to identify unexpected but visible defects. The
implemented framework is applied to examine a total of 99 OpenDRIVE datasets, where significant lane gaps were detected in the
explicit representation for about 20% of the datasets.
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The standard OpenDRIVE is widely used for exchanging road space models in order to simulate the traffic of a city or individual
driving situations. For modeling continuous road courses at lane level, OpenDRIVE utilizes its own parametric geometry model.
However, violations of continuity requirements due to geometric leaps or kinks can cause the vehicle dynamics simulation to
fail when testing vehicle components. But also defective lane predecessor and successor relations can result in an Open...
»