this post was submitted on 21 Oct 2023
329 points (83.2% liked)

Fuck Cars

9824 readers
6 users here now

This community exists as a sister community/copycat community to the r/fuckcars subreddit.

This community exists for the following reasons:

You can find the Matrix chat room for this community here.

Rules

  1. Be nice to each other. Being aggressive or inflammatory towards other users will get you banned. Name calling or obvious trolling falls under that. Hate cars, hate the system, but not people. While some drivers definitely deserve some hate, most of them didn't choose car-centric life out of free will.

  2. No bigotry or hate. Racism, transphobia, misogyny, ableism, homophobia, chauvinism, fat-shaming, body-shaming, stigmatization of people experiencing homeless or substance users, etc. are not tolerated. Don't use slurs. You can laugh at someone's fragile masculinity without associating it with their body. The correlation between car-culture and body weight is not an excuse for fat-shaming.

  3. Stay on-topic. Submissions should be on-topic to the externalities of car culture in urban development and communities globally. Posting about alternatives to cars and car culture is fine. Don't post literal car fucking.

  4. No traffic violence. Do not post depictions of traffic violence. NSFW or NSFL posts are not allowed. Gawking at crashes is not allowed. Be respectful to people who are a victim of traffic violence or otherwise traumatized by it. News articles about crashes and statistics about traffic violence are allowed. Glorifying traffic violence will get you banned.

  5. No reposts. Before sharing, check if your post isn't a repost. Reposts that add something new are fine. Reposts that are sharing content from somewhere else are fine too.

  6. No misinformation. Masks and vaccines save lives during a pandemic, climate change is real and anthropogenic - and denial of these and other established facts will get you banned. False or highly speculative titles will get your post deleted.

  7. No harassment. Posts that (may) cause harassment, dogpiling or brigading, intentionally or not, will be removed. Please do not post screenshots containing uncensored usernames. Actual harassment, dogpiling or brigading is a bannable offence.

Please report posts and comments that violate our rules.

founded 3 years ago
MODERATORS
 

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

you are viewing a single comment's thread
view the rest of the comments
[–] [email protected] 2 points 1 year ago (1 children)

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.

[–] [email protected] 1 points 1 year 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.