Autonomous driving functions (ADFs) are becoming more relevant and complex. Still, their safe and correct operation must be guaranteed. Scenario-based testing, i.e. confronting the ADF under test with other traffic in specified scenarios is an established approach for the validation and verification of ADFs, but tests currently often only consider simple technical requirements. Safe and correct operation is not only the absence of collisions but involves complex spatio-temporal requirements on the externally observable, functional driving behaviour in traffic. In this work, we consider Traffic Sequence Charts (TSCs) as a visual formalism for the specification of complex, functional ADF requirements. We define a monitoring problem for TSCs and finite, sampled observations of ADF behaviour and discuss how monitor verdicts contribute to requirements testing. We show that such monitors can effectively be constructed for realistic requirements and that they can contribute to efficient testing by assessing ADF behaviour at runtime.

Unfoldings are a well known partial-order semantics of P/T Petri nets that can be applied to various model checking or verification problems. For high-level Petri nets, the so-called symbolic unfolding generalizes this notion. A complete finite prefix of a P/T Petri net’s unfolding contains all information to verify, e.g., reachability of markings. We unite these two concepts and define complete finite prefixes of the symbolic unfolding of high-level Petri nets. For a class of safe high-level Petri nets, we generalize the well-known algorithm by Esparza et al. for constructing small such prefixes. We evaluate this extended algorithm through a prototype implementation on four novel benchmark families. Additionally, we identify a more general class of nets with infinitely many reachable markings, for which an approach with an adapted cut-off criterion extends the complete prefix methodology, in the sense that the original algorithm cannot be applied to the P/T net represented by a high-level net.