  Perception algorithms in autonomous vehicles are vital for the vehicle to
understand the semantics of its surroundings, including detection and tracking
of objects in the environment. The outputs of these algorithms are in turn used
for decision-making in safety-critical scenarios like collision avoidance, and
automated emergency braking. Thus, it is crucial to monitor such perception
systems at runtime. However, due to the high-level, complex representations of
the outputs of perception systems, it is a challenge to test and verify these
systems, especially at runtime. In this paper, we present a runtime monitoring
tool, PerceMon that can monitor arbitrary specifications in Timed Quality
Temporal Logic (TQTL) and its extensions with spatial operators. We integrate
the tool with the CARLA autonomous vehicle simulation environment and the ROS
middleware platform while monitoring properties on state-of-the-art object
detection and tracking algorithms.
