<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>frogblast</author><text>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.&lt;p&gt;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.  Every summer weekend the highway becomes highly congested.&lt;p&gt;Google quickly starts routing people down the back roads because of a 30 minute delay on the highway.  A sudden crush of cars hits these back roads, and they end up gridlocked for 3-4 &lt;i&gt;hours&lt;/i&gt;.  Google then realizes traffic is literally stopped on these roads, and stops sending new traffic down those routes.  But the people already on them are still stuck for hours.&lt;p&gt;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.&lt;p&gt;All because Google simultaneously made an ‘individually optimal’ decision for a whole bunch of individual drivers at once.&lt;p&gt;——&lt;p&gt;Another example in the same area actually causes a backup on the highway itself.  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.  Drivers dutifully followed directions by getting into the left turn lane.&lt;p&gt;The drain rate of the left turn rate is slow because oncoming traffic is also high.  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.   And suddenly the highway is now encountering 2-3 hour delays that don’t clear for most of the day.</text><parent_chain><item><author>paxys</author><text>When User 3982274 is on a busy road using the app, Google optimizes for that user&amp;#x27;s experience. If every user on that road is using the app at the same time, these algorithms should theoretically result in the optimal condition you described above.&lt;p&gt;For example, if there are two roads leading up to the destination, one at 100% capacity and the other at 0%. The app will start routing people from road 1 to road 2. When the two balance out and the app will stop the suggestion. Even though it helped only some individual users, the end result is a 50&amp;#x2F;50 split, so good for everyone.</text></item><item><author>2bitencryption</author><text>Google Map&amp;#x27;s traffic prediction has always led me to a very curious question:&lt;p&gt;Clearly Google Maps has the ability to turn into a feedback loop. Traffic exists -&amp;gt; people use Google Maps to find better routes -&amp;gt; traffic is modified due to people taking alternate routes -&amp;gt; new traffic emerges.&lt;p&gt;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?&lt;p&gt;Should Google Maps route several cars through a suboptimal route, if it results in traffic as a whole becoming better?&lt;p&gt;If Google Maps is &amp;quot;greedy&amp;quot; for every driver, can that make a traffic problem worse?&lt;p&gt;In reality, I guess this problem is more hypothetical than real, at least today.  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?&lt;p&gt;edit: there&amp;#x27;s also Braess&amp;#x27;s paradox. I&amp;#x27;m not sure if it applies here, but perhaps it does -- could &amp;quot;sending some users down a new route during heavy traffic&amp;quot; be identical to  &amp;quot;adding a road to a network&amp;quot;, which can therefore result in the paradox (worse network conditions for everyone)?&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Braess%27s_paradox&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Braess%27s_paradox&lt;/a&gt;</text></item></parent_chain></comment><story><title>Traffic Prediction with Advanced Graph Neural Networks</title><url>https://deepmind.com/blog/article/traffic-prediction-with-advanced-graph-neural-networks</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>layoutIfNeeded</author><text>That&amp;#x27;s definitely not how it works. Traffic is a nonlinear dynamical system with all sorts of non-intuitive coupling between various components.</text><parent_chain><item><author>paxys</author><text>When User 3982274 is on a busy road using the app, Google optimizes for that user&amp;#x27;s experience. If every user on that road is using the app at the same time, these algorithms should theoretically result in the optimal condition you described above.&lt;p&gt;For example, if there are two roads leading up to the destination, one at 100% capacity and the other at 0%. The app will start routing people from road 1 to road 2. When the two balance out and the app will stop the suggestion. Even though it helped only some individual users, the end result is a 50&amp;#x2F;50 split, so good for everyone.</text></item><item><author>2bitencryption</author><text>Google Map&amp;#x27;s traffic prediction has always led me to a very curious question:&lt;p&gt;Clearly Google Maps has the ability to turn into a feedback loop. Traffic exists -&amp;gt; people use Google Maps to find better routes -&amp;gt; traffic is modified due to people taking alternate routes -&amp;gt; new traffic emerges.&lt;p&gt;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?&lt;p&gt;Should Google Maps route several cars through a suboptimal route, if it results in traffic as a whole becoming better?&lt;p&gt;If Google Maps is &amp;quot;greedy&amp;quot; for every driver, can that make a traffic problem worse?&lt;p&gt;In reality, I guess this problem is more hypothetical than real, at least today.  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?&lt;p&gt;edit: there&amp;#x27;s also Braess&amp;#x27;s paradox. I&amp;#x27;m not sure if it applies here, but perhaps it does -- could &amp;quot;sending some users down a new route during heavy traffic&amp;quot; be identical to  &amp;quot;adding a road to a network&amp;quot;, which can therefore result in the paradox (worse network conditions for everyone)?&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Braess%27s_paradox&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Braess%27s_paradox&lt;/a&gt;</text></item></parent_chain></comment><story><title>Traffic Prediction with Advanced Graph Neural Networks</title><url>https://deepmind.com/blog/article/traffic-prediction-with-advanced-graph-neural-networks</url></story>