Safety of Automated Driving Systems (ADSs) is arguably one of the main remaining
barriers before widespread market deployment. While there exists a plethora of
methods for planning a trajectory that fulfils certain constraints, what those
constraints should look like, to enable effective planning of safe trajectories,
is still being discussed. In this article, we generalize the concept of
Precautionary Safety (PCS) and present a framework providing constraints on the
tactical and operational decisions of the ADS. Such constraints consider the
ADS’ capabilities, the external conditions, knowledge of statistically relevant
events and behaviors of other traffic actors, as well as the controllability of
these events. The proposed framework enables assessment of the statistical
fulfilment of quantitative risk acceptance criteria (QRACs), including
requirements on accident, injury, and fatality rates. The framework further
provides a means to dynamically adapt the constraints used for trajectory
planning, i.e., to adapt the driving to the situation at hand. A case study,
considering a possible collision scenario with a jaywalking pedestrian and a
rear-end collision with a trailing vehicle, is provided to showcase the
applicability and usefulness of the presented framework. The simulation-based
case study displays the safety benefits from considering QRACs with multiple
injury risk levels and further shows how the proposed PCS framework can be
applied in practice.
