  Environment perception and representation are some of the most critical tasks
in automated driving. To meet the stringent needs of safety standards such as
ISO 26262 there is a need for efficient quantitative evaluation of the
perceived information. However, to use typical methods of evaluation, such as
comparing using annotated data, is not scalable due to the manual effort
involved.
  There is thus a need to automate the process of data annotation. This paper
focuses on the LiDAR sensor and aims to identify the limitations of the sensor
and provides a methodology to generate annotated data of a measurable quality.
The limitations with the sensor are analysed in a Systematic Literature Review
on available academic texts and refined by unstructured interviews with
experts.
  The main contributions are 1) the SLR with related interviews to identify
LiDAR sensor limitations and 2) the associated methodology which allows us to
generate world representations.
