I saw a good article on c/upliftingnews about AI improving traffic signal controllers. It’s good and all, I just can’t help but think of the “look at what they need to have a fraction of our power” meme while reading it

  • what is ahead? for that you need to find out which are the main routes people take. But you also cant just give the dominant route alle the passage, because the other routes are important too. With that you get a complex network you need to optimise, where a central control uses the sensor input from the individual lights, but local contral is not sufficent.

    And this is what the original comment stated, with his colleagues using reinforcement learning as one possible approach.

    • @max@feddit.nl
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      fedilink
      18 months ago

      For a big road/street, whatever the main flow of traffic is following. So for a north-south street that’s busier than the east-west street intersecting with it, optimise the flow for traffic going north-south, including the intersections ahead. A “green wave” or “groene golf” in Dutch would work wonders. Stick to the advised speed on the digital signs and you get a wave of green lights for x amount of upcoming intersections. I’ve had them for up to 9 in a row. For the streets crossing the main road, you get some sensors, probably inductive loops to check if there are cars waiting. If there are, periodically give them green and turn the main road to red. If there are no cars on the main road (e.g., at night), you could have an extra induction loop ahead of the crossing so that the light turns green for the crossing road whenever someone approaches, before even having to stop at the light.

      Sure, you could use reinforcement learning there. But you really don’t have to. Analyse the traffic for a while, and it’ll stay pretty much the same for a long, long time. Just optimise the cycles according to the time of day and day of the week and you should be good.