AI predicts accident hot-spots from satellite imagery and GPS data
unite.ai
unite.ai
- Speed Limit > 30mph and < 60 mph
- lots of driveways and left turns
- moderately heavy traffic at some times of day but not constant gridlock
Just picture the commercial drag strip and the collector roads that wind between huge garden apartment complexes or gated subdivision.
Accidents are especially likely where two such streets cross.
Why?
These are the futon of transportation. They’re designed first for high speed and volume of traffic, but also high direct access to the surrounding businesses. These objectives are horribly in conflict and not safe to combine. People want to drive FAST on these, and they do, but they are frustrated by the stop and go nature and there is a constant stream of “surprises” when other drivers take a chance on a turn through a tight gap or run a light that just turned red because they’re sick of waiting. One moment of distraction for either party and BAM, a crash.
Good streets for local access are small and slow moving (high volume can be accommodated by a parallel network of such streets, ie “a grid” but it doesn’t have to be perfect squares). Good roads for high speed are wide, clear, and simple, with lots of extra room to cushion mistakes (medians, shoulders, etc.)
All this model has really done is learned to recognize new “stroads” that don’t have a crash history yet, but will soon.
The result of the simulation was both interesting but also unrealistic.
In order to improve intake from the feeder streets the simulation recommended something no normal drivers would do in rush hour: IIRC it wanted drivers to obediently and predictably do alternate lane merges as well as some intricate braided flow pattern. It was great if you were working with logical components but utterly impractical in reality. I don’t think any semblance of that system was ever implemented as it was obvious it would fail worse than the current bad design.
Whenever traffic is slow, I make a point of always driving up exactly towards the merge and just sliding into the flow of traffic. Many many times, someone will be pissed at that, either on the way there because my lane is free, sometimes for a very very long stretch and they try to cut me off because I'm 'bypassing' the line or even at the merge, where I just let someone through but then it's my turn but they cut me off.
What do these people think? The 2 lane highway is supposed to become a 1 lane highway just because there's a merge ahead (say because of an accident)? How far back is it supposed to become 1 lane? 100 meters? 500 meters? 10 kilometers? I've seen some crazy long lineups with nobody on the second lane for multiple kilometers. The line could easily have been half as long if everyone just stayed on their lane until the merge point and zippered.
I remember seeing an experiment on TV (Germany) like 20 years ago, where they had a large truck adhere to the zipper rule, merging exactly where they're supposed to and filming it (doing it over and over) and there were many many cases of the truck having to brake hard as people tried to 'slip by'. This was a 'soft zipper' i.e. lots of space to the front with just lines marked out where the truck could come to a standstill/slow down and go on, so it was a safe experiment.
Which ultimately is one of those cases that demonstrate that some ideas are good and 'correct' but "not implementable with humans."
The only problem with zipper merging (much like roundabouts) is a lack of education around how they work and WHY they work. Adjust the education we give new drivers and over time our roads will become more efficient.
https://www.youtube.com/watch?v=iHzzSao6ypE
The real simple solution to traffic is no more monkeys driving cars. Also, implicitly, fully isolate cars from human powered forms of transportation.
Meanwhile self-driving cars can learn of them from the scheduling coordination services and distribute the load among working routes without rubbernecking.
Not getting the futon analogy?
1) they will use individual responsibility arguments on drivers to blame them
2) blame pedestrians or cyclists or whoever for failing to defer to cars
It’s not a legality problem it’s a philosophy one.
This is not a dichotomy. The legal aspect comes from the "philosophical" one that comes for lobby money.
They cause congestion and are much slower than actual roads, while still being unfriendly to pedestrians and bikers. They're bad for drivers and bad for pedestrians.
https://www.strongtowns.org/journal/2018/2/5/the-true-cost-o...
The pramaterizarion is largely around the dynamics of the cars not human behavior. It’s the over algorithmization of decision making. It’s like YouTube radicalizing people by showing them videos that increase engagement. It’s not intentional in a strict sense, it’s just mindless adherence to a process without thinking.
But then later, because the bypass road is usually built on cheap land outside of the city center, all that property gets bought up and developed as well, and the property owners will demand ingress/egress to their properties. Since the environment is nicer than the snarled up city center, people will start to favor businesses and housing in this area. Over the next 10-20 years the bypass will simply turn into another stroad. To make matters worse, the bypass and the original road will often have the same road numbers, differentiated by either "business" or "bypass", making navigation confusing.
Where I live I often see multi-million dollar homes being built right next to high-speed roads, and instead of a feeder street system taking cars to a more limited number of ingress/egress points, they simply dump the driveways out into the 60mph traffic. Total insanity.
It really does all come down to poor planning, and a lack of desire to make street planned city center grids with mixed-zone housing and municipal managed central parking areas. Instead each business sits in an island in a sea of their own giant parking lots, which often sit mostly unused which makes urban centralization impossible.
One can assume from this requirement that fighting fires is impossible in Europe, and residential buildings are constantly burning to the ground with firefighters standing around, helpless to intervene.
In Europe a street as wide as that would be a main thoroughfare. I seemed to see them all over in the US, like every road in a grid would be super wide, but also have shops.
These roads aren't ideal but they're everywhere because they're cheap. Unless you can wave a magic wand and make municipalities rich enough to carpet bomb everything with traffic lights, dedicated turn lanes and sidewalks there are going to be tradeoffs.
I'm sure all sorts of wonderful pedestrian friendly moves get pulled by people trying to get ahead in that game.
I live in one of the poorest neighborhoods on the outskirts of my US city. There are a few major roads headed toward the more affluent neighborhoods and downtown. What I see when I run along/across or drive along those roads is mostly through-traffic. There aren't a lot of "shops" in my neighborhood, but one or two strip-malls and a few gas-stations and fast-food "restaurants".
Anecdata: In my experience, the areas with less through-traffic (and thus high-danger traffic) are areas with destinations, whether they're shops for goods and/or services or restaurants (that don't involve cars). The reason I think it's economic is because it's not just about the customers/consumers visiting these areas, but the workers. I'd bet that a not-insignificant number of workers in my neighborhood drive to another neighborhood for work, but the inverse is probably not true (that a lot of folks from other neighborhoods drive here for work).
I think part of the solution is to make communities smaller and more friendly to their inhabitants. There should be opportunities for work in these poorer neighborhoods, and that means the services to support them.
It doesn't matter what number is on the speed limit sign on these major roads, people will drive 50 anyway (I have been passed in the turn lane several times because I drive the speed limit on a 2-lane (one each direction) + turn-lane road).
Perfect application of AI/ML. The reasoning behind AI/ML does not need to be mysterious for it to be an appropriate solution. "All it has done is <Something I understand> " is not a valid criticism of the solution.
"All it has done is add these values and subtract these values" would not be a valid criticism of a banking application, for example.
Also, the rest of the prediction appears to just be the density of the road segmentation. Look at the parking lot (?) top left of the purple box (or all the road-rich neighborhoods in the right half):
https://ml8ygptwlcsq.i.optimole.com/fMKjlhs-dkVIYmPS/w:700/h...
Plenty high estimated risk, zero actual collisions.
You could get the same predictive quality with a simple gaussian blur of the "historical accidents" plots (road segmentation included), it seems.
I worked on a project like this for an insurance-oriented hackathon
We created a heatmap from readily available historical data adjusted for traffic density, and played a sound on a mobile device when approaching "hotspots".
For extra "wow" points we actually had someone drive out in my car and tracked them live as they drove around the location of the event, with hotspots showing up at places like where a blind entrance to the parking garage intersected with the road
I hope they are misquoted here.
The main takeaway from this work is that better data equals better models. The data fusion approach taken by the authors is the most interesting thing about it. The comparisons to baselines is the weakest part of the article. The effort to sell this as a highly significant result is just sad, but is mostly a reflection of the state of academic publishing.
If I am an accident oracle -- say I know with certainty where, say, 50% of accidents will occur (the other 50% are truly stochastic with no structural component at all) -- and the city believes me, then surely when I tell them an accident will occur at Intersection X, they will take measures that prevent accidents at Intersection X.
But this also means any measure of my ability to predict accidents is confounded, because the equilibrium behaviour would be that I never predict an accident and plenty of other accidents occur. Moreover, because of all the other confounders, it's actually unclear whether we should expect accidents to go down or up or stay the same or what, and to the extent year to year variability was already quite high the problem will be even larger, so even high level numbers before and after hiring my services aren't easily interpretable.
Which is fine, you just need to convince decision makers of this particular inferential fallacy and then hopefully they keep listening even though the KPI is wrong. Except what if the type of accidents change and I'm no longer an accident oracle? Then the mitigation efforts are wasted, and also the money they pay me.
One solution would be to basically engage in some kind of RCT where some of my predictions are held out for assessing my model while others are acted on and where the strength of the prior about my effect decays. Good luck telling voters and lawyers that justification, though.
Fun stuff.
The Dutch took the approach of treating car crashes similarly to how the FAA treats plane crashes: do a deep analysis of what occurred, what the root structural issues were (for instance, is it difficult for a car turning left to see oncoming traffic?) and then change the environment to improve the structural issues.
Knowing where incident hot spots are likely to be should help you redesign the areas most likely to cause issues.
There’s a reason the Netherlands has around 1/3 as many traffic fatalities per capita as the US: in the US, it seems like we throw up our hands at problems like road crashes, whereas with problems like plane safety we take an incremental and root-cause analysis approach to improve safety over time.
If you make an oracle that simply points that some necessary geometries accumulate the risks, don't be surprised when every authority not only ignores you, but also becomes very annoyed if you insist on it.
Hmmm....
A bit like autonomous driving, sounds like the sort of thing that probably works beautifully well in places like the US and elsewhere with wide roads and predictable grid patterns.
I imagine this sort of thing would mark large swathes of Europe,Africa, Japan, India and all sorts of other places as "accident hot-spots" though.
I learned to swing my upper body sideways to have a look behind the pillar. As a cyclist I learned to look for the face of the driver and to stop if I don't see the eyes.
Because I both hit a cyclist and got hit as a cyclist by a car.
Which is probably good and bad -- municipalities can use the data to improve dangerous roads/intersections, online map providers could use the information to route around dangerous roads. But also insurance companies can use it to set rates "We've analyzed your driving over the past month and based on our predicted danger level, we're going to need to increase your rates 20%
Car insurance telematics [1] seems largely positive in that it financially discourages dangerous behaviors and it means people who actually drive dangerously (as opposed to people who are simply young) will foot a greater fraction of insurance costs. (Though there are definitely implementation issues and privacy concerns.)
[1] https://www.consumerreports.org/car-insurance/how-car-insura...