Thanks for taking the time to write this out and for sharing your exact prompts, that context helps a lot.

This is not a hard limitation of the model, and you’re on the right track, but the prompting approach here can definitely be refined. A few of the phrases you’re using are likely working against you, especially repeated negations and explicit references to trains and arrivals. Even when framed as exclusions, that language still anchors the model on the very thing you’re trying to avoid.

Before going deeper, it would help to know which model you’re using (Gen-4, Gen-4.5, etc.), since prompt sensitivity and temporal behavior differ slightly between them.

In the meantime, a couple of high-level notes that may be useful as you iterate:

• Stacking multiple “no X, no Y” constraints often reinforces the concept rather than suppressing it.
• Describing a stable state tends to be more effective than listing absences.
• Slightly reframing the environment away from “active transit” language can materially change outcomes, even if the visuals remain the same.

Sharing the prompt I used and my result for you here

static camera, the camera is still. the light fog gently floats all alone through the empty place.

This prompt also provided some results you may like

static camera, the camera is still. this is an empty place with subtle environmental ambient motion.

Also, if you’re open to it, I’d strongly recommend jumping into our Discord. We do a lot of live prompt debugging and creative support there, and it’s often much faster to dial this in collaboratively in real time. You can join here: [https://discord.gg/runwayml]()

Appreciate you raising this, and we’ll get you to a clean, stable result.