  Autonomous driving functions (ADFs) in public traffic have to comply with
complex system requirements that are based on knowledge of experts from
different disciplines, e.g., lawyers, safety experts, psychologists. In this
paper, we present a research preview regarding the validation of ADFs with
respect to such requirements. We investigate the suitability of Traffic
Sequence Charts (TSCs) for the formalization of such requirements and present a
concept for monitoring system compliance during validation runs. We find TSCs,
with their intuitive visual syntax over symbols from the traffic domain, to be
a promising choice for the collaborative formalization of such requirements.
For an example TSC, we describe the construction of a runtime monitor according
to our novel concept that exploits the separation of spatial and temporal
aspects in TSCs, and successfully apply the monitor on exemplary runs. The
monitor continuously provides verdicts at runtime, which is particularly
beneficial in ADF validation, where validation runs are expensive. The next
open research questions concern the generalization of our monitor construction,
the identification of the limits of TSC monitorability, and the investigation
of the monitor's performance in practical applications. Perspectively, TSC
runtime monitoring could provide a useful technique in other emerging
application areas such as AI training, safeguarding ADFs during operation, and
gathering meaningful traffic data in the field.
