  The development of Automated Driving Systems (ADSs) has made significant
progress in the last years. To enable the deployment of Automated Vehicles
(AVs) equipped with such ADSs, regulations concerning the approval of these
systems need to be established. In 2021, the World Forum for Harmonization of
Vehicle Regulations has approved a new United Nations regulation concerning the
approval of Automated Lane Keeping Systems (ALKSs). An important aspect of this
regulation is that "the activated system shall not cause any collisions that
are reasonably foreseeable and preventable." The phrasing of "reasonably
foreseeable and preventable" might be subjected to different interpretations
and, therefore, this might result in disagreements among AV developers and the
authorities that are requested to approve AVs.
  The objective of this work is to propose a method for quantifying what is
"reasonably foreseeable and preventable". The proposed method considers the
Operational Design Domain (ODD) of the system and can be applied to any ODD.
Having a quantitative method for determining what is reasonably foreseeable and
preventable provides developers, authorities, and the users of ADSs a better
understanding of the residual risks to be expected when deploying these systems
in real traffic.
  Using our proposed method, we can estimate what collisions are reasonably
foreseeable and preventable. This will help in setting requirements regarding
the safety of ADSs and can lead to stronger justification for design decisions
and test coverage for developing ADSs.
