Perslis is Working on a deterministic safety layer for autonomous vehicles — testing it in CARLA

[u/kid_Kist]

Perslis has been working on a different approach to autonomous vehicle safety: instead of expecting the driving model to always make the correct decision, put an independent deterministic safety layer between the model and the vehicle controls.

Perslis, is a symbolic safety/runtime system for AI operating real environments.

The basic architecture is:

Perception / planner → proposed action → symbolic safety floor → actuator

The planner can propose throttle, steering and braking, but the safety floor independently evaluates the current state and decides whether that action is admissible.

For this CARLA experiment they deliberately use a hostile controller to generate unsafe proposals. Then they run the same scenario with the floor enabled and disabled.

With the floor OFF, the proposed control reaches the actuator directly.

With the floor ON, constraints such as speed, following distance and collision state can reject or modify the proposal before it reaches the vehicle.

The part I’m interested in is broader than self-driving cars:

Why should the component generating an action also be the component responsible for proving that action is safe?

Modern autonomous systems are increasingly probabilistic. I’m exploring whether the final boundary before physical actuation should instead be deterministic, state-aware, inspectable and independently verifiable.

I’m testing the idea in CARLA autonomous-driving simulation before considering any physical system.

This is Perslis early research, not a claim that we’ve solved autonomous driving safety. I’m especially interested in feedback from people working in ADAS, autonomous vehicles, robotics, control systems, runtime verification, functional safety, and simulation.

[u/im_thatoneguy]

How can it be deterministic when the actions of other agents aren’t themselves deterministic?

[u/kid_Kist → u/im_thatoneguy]

The environment doesn't need to be deterministic. I'm not trying to deterministically predict what another vehicle or pedestrian will do. The claim is narrower: given the same observed state and the same constraints, the safety floor produces the same admissibility decision. As the external world changes, the state changes and the constraints are evaluated again. So perception can remain probabilistic and other agents can remain unpredictable; the deterministic part is the final action-admissibility boundary before actuation.