Conference: Aggregation of Road Characteristics from Online Maps and Evaluation of Datasets

Automated driving functions have received a lot of attention from the scientific community and the general public in the recent years. However, safety assurance, verification and validation of automated driving systems remain as a huge challenge, among others, towards making automated vehicles available to a broader public. For tackling these challenges, scenario-based validation, as one building block, can be used to show the effect and the impact of automated vehicles in (safety-) relevant scenarios. As of now, this is mainly done without considering external factors that can have a major impact on the performance of humans and systems such as road characteristics and adverse weather conditions. In this paper we focus on the aspect of road characteristics. We present a method to extract road characteristics from online map data and compare that data to the coverage of road characteristics in various datasets. This can be used for the comparison with recorded datasets and thereby give an overview of covered road characteristics as well as the gaps in those characteristics which still need to be covered by further recordings or datasets.

IEEE Xplore (DOI)

Recommended citation:

@InProceedings{Hiller2021,
  author    = {Johannes Hiller and Fabian M{\"u}ller and Lutz Eckstein},
  booktitle = {2021 {IEEE} Intelligent Vehicles Symposium ({IV})},
  title     = {Aggregation of Road Characteristics from Online Maps and Evaluation of Datasets},
  year      = {2021},
  month     = {jul},
  publisher = ,
  doi       = {10.1109/iv48863.2021.9575339},
}