Runtime monitoring of complex scenario-based requirements for autonomous driving functions

Abstract

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.