![]() The left turn lane fills up, and one driver with directions to turn then stops in the traffic lanes to wait for room to get into the turn lane. The drain rate of the left turn rate is slow because oncoming traffic is also high. Drivers dutifully followed directions by getting into the left turn lane. Google started suggesting one back road that required an unprotected left turn across oncoming traffic on the highway, to avoid a 10-15 minute delay further on the highway. It gets smelly when a bunch of drivers take a shit on the side of the road because they can’t go anywhere else, and leave it there.Īll because Google simultaneously made an ‘individually optimal’ decision for a whole bunch of individual drivers at once.Īnother example in the same area actually causes a backup on the highway itself. But the people already on them are still stuck for hours. Google then realizes traffic is literally stopped on these roads, and stops sending new traffic down those routes. A sudden crush of cars hits these back roads, and they end up gridlocked for 3-4 hours. Google quickly starts routing people down the back roads because of a 30 minute delay on the highway. Every summer weekend the highway becomes highly congested. I live in a rural area, between a major population center and a major resort area, with one major highway and a few small back roads that provide alternate paths for part of the highways route. I live in an area strongly impacted by Google making ‘individually optimal’ decisions for each driver, and actually leaving those drivers in a dramatically worse situation. Wow, such naivety, and that's when you even have perfect information! Such a cool domain, tons of respect for the work that's being done here, even if there are some tricky/ethical aspects that are going to come into play eventually, inevitably. I had no idea cooperative path-planning was so damn difficult - I remember estimating it as a 1-week mini-project initially. That made people happy - aircraft no longer did seemingly stupid things like "oscillate", or get "temp. ![]() We eventually implemented a relatively simple "AStar-3D", essentially just A* against a space-time graph, and it's greedy/FIFO - meaning it's optimal for each aircraft at the time the aircraft runs it's path. WHCA* turned out to be a bit too suboptimal for our use-case, people generally expected "perfectly optimal" routes to be used for aircraft, and they weren't even overly happy with most-optimal "for-all" paths either. In a game my company created, we implemented cooperative realtime pathfinding using WHCA* - an algorithm that David Silver published (he's now working at DeepMind last I looked). It's a good question, even if it's likely not applicable practically yet. I'm not sure if it applies here, but perhaps it does - could "sending some users down a new route during heavy traffic" be identical to "adding a road to a network", which can therefore result in the paradox (worse network conditions for everyone)? But imagine this: in 30 years, if all cars are self-driving and self-navigating via systems like Google Maps, what is the system optimizing for?Įdit: there's also Braess's paradox. In reality, I guess this problem is more hypothetical than real, at least today. If Google Maps is "greedy" for every driver, can that make a traffic problem worse? Should Google Maps route several cars through a suboptimal route, if it results in traffic as a whole becoming better? So my question is: what is Google Maps traffic optimizing for? The best traffic experience for User 3982274, or the best traffic experience for the conglomerate of all cars on the road? Traffic exists -> people use Google Maps to find better routes -> traffic is modified due to people taking alternate routes -> new traffic emerges. Google Map's traffic prediction has always led me to a very curious question:Ĭlearly Google Maps has the ability to turn into a feedback loop.
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