This model is overlooking some aspects of traffic flow. The most important one is that flow does not increase and decrease smoothly. As density increases there starts to be shock waves that bounce longitundinally[0].
It would also makes sense to also distribute some autonomous vehicles along the train to minimize these shock waves. A much simplier solution is to autonomously centre between the vehicle in front and rear[1]. Doing so smoothly is simple local logic which may improve flow rates dramatically but I don't know if it's been implemented anywhere.
On my commute all of the possible routes are congested. I can be as selfish as I like, but I won't get home any faster. I think we need more roads and more pubic transport and more work-from-home schemes. Autonomous cars may may allow me to chill a bit more in the gridlock I suppose...
Funny what apparently simple differences in mathematical models can imply.
I studied an old-school "Wardrop model" of traffic flow in one class in school. In that model, your speed along a road segment is a function of the flow (vehicles per hour), and it's usually assumed to be monotonic (or at least non-decreasing.) In the article, the images never show increased throughput coinciding with longer travel times.
In the Wardrop model, equilibrium traffic levels are unique, and in TFA's model they aren't. (The diagrams make this clear in a really nice way, I like them a lot.)
I wonder whether/when each model is a better description of reality. It's hard to imagine the road in that Office Space clip demonstrating especially veh/hr flow...
In my reading, this says that autonomous cars, if they all behave cooperatively, can be more efficient road users than manual cars driven by individuals acting selfishly.
While it works out in the Nash equilibria they describe, I don't see it working at any sort of scale. It's too easy to defect from the better equilibrium: drive the car yourself, or buy that aftermarket app which disables the cooperative driving mode.
It is already working at scale. If you are using google maps' navigation, you are driving like this today. The only difference - instead of doing altruistic thing by your own volition, you are likely being misled by nav system to take the route that, while being somewhat sub-optimal at this particular moment, will not cause massive congestion the moment you will get there.
If there were safety advantages with cooperative driving and ultimately efficiencies I bet a public relations campaign could convince people. Or having dedicated lanes for cooperative driving. I would certainly turn this on for interstate driving.
I think the PR campaign makes people aware there is a problem, but when people are intoxicated, the access to good [nondestructive] decision making is inhibited.
I would wonder if ALL vehicles should have some sort of breathalyzer interlock that could also prevent junior from "fixing" mommys car so the little green light comes on again.
I drove to work for a while and it was awful. I wished that there was some way to tell everyone what the average speed of the road currently was and limit their speed to that. Instead I found that people moved their cars forward to the next place to stop as quickly as they could every single time. It was infuriating.
What actually happens with human drivers is this: everyone wants to get home/work so the distance between the cars will decrease below safe levels when more cars are added to the road.
So the breaking latency of the autonomous cars must be better than this to fit more cars onto roads.
> ...when a modest portion of the autonomous cars are altruistic, it is possible for majority of the cars to use the shortest route without causing congestion. This can significantly (in fact, unboundedly) decrease the total latency.
how could it decrease the total latency unboundedly? I mean, doesn't the lower bound have to be zero?
They're probably talking about a division style of 'unbounded' (dividing by your 0). But they're still bounded by the speed of light in that case. Trash article is trash.
It would also makes sense to also distribute some autonomous vehicles along the train to minimize these shock waves. A much simplier solution is to autonomously centre between the vehicle in front and rear[1]. Doing so smoothly is simple local logic which may improve flow rates dramatically but I don't know if it's been implemented anywhere.
I studied an old-school "Wardrop model" of traffic flow in one class in school. In that model, your speed along a road segment is a function of the flow (vehicles per hour), and it's usually assumed to be monotonic (or at least non-decreasing.) In the article, the images never show increased throughput coinciding with longer travel times.
In the Wardrop model, equilibrium traffic levels are unique, and in TFA's model they aren't. (The diagrams make this clear in a really nice way, I like them a lot.)
I wonder whether/when each model is a better description of reality. It's hard to imagine the road in that Office Space clip demonstrating especially veh/hr flow...
While it works out in the Nash equilibria they describe, I don't see it working at any sort of scale. It's too easy to defect from the better equilibrium: drive the car yourself, or buy that aftermarket app which disables the cooperative driving mode.
What's affected those is laws, vigorously enforced.
So the breaking latency of the autonomous cars must be better than this to fit more cars onto roads.
how could it decrease the total latency unboundedly? I mean, doesn't the lower bound have to be zero?