  Autonomous vehicles (AVs) must always have a safe motion to guarantee that
they are not causing any accidents. In an AV system, the motion of the vehicle
is represented as a trajectory. A trajectory planning component is responsible
to compute such a trajectory at run-time, taking into account the perception
information about the environment, the dynamics of the vehicles, the predicted
future states of other road users and a number of safety aspects.
  Due to the enormous amount of information to be considered, trajectory
planning algorithms are complex, which makes it non-trivial to guarantee the
safety of all planned trajectories. In this way, it is necessary to have an
extra component to assess the safety of the planned trajectories at run-time.
Such trajectory safety assessment component gives a diverse observation on the
safety of AV trajectories and ensures that the AV only follows safe
trajectories. We use the term trajectory checker to refer to the trajectory
safety assessment component. The trajectory checker must evaluate planned
trajectories against various safety rules, taking into account a large number
of possibilities, including the worst-case behavior of other traffic
participants. This must be done while guaranteeing hard real-time performance
since the safety assessment is carried out while the vehicle is moving and in
constant interaction with the environment.
  In this paper, we present a prototype of the trajectory checker we have
developed at IVEX. We show how our approach works smoothly and accomplish
real-time constraints embedded in an Infineon Aurix TC397B automotive platform.
Finally, we measure the performance of our trajectory checker prototype against
a set of NCAPS-inspired scenarios.
