Computation in series/parallel: Estimating the ideal throughput speed in uncertain traffic conditions
One of my favorite games to play when I drive is to try to estimate the ideal throughput speed — the speed at which you can go through traffic without having to change your speed. This involves a couple of behavioral changes: you have to allow more space than normal between you and the car in front, you have to be aware of upcoming red lights, etc. Over the years I have found that some drivers behind me get really annoyed over the amount of space in front of me. They race around and drive as fast as they can to the red light ahead whereupon they have to immediately brake. Sometimes I get to go past these drivers since I approach the green light moving while they have to race me again from a dead stop.
It occurred to me the other day that if the driver behind me noticed that I was doing this, they could, in turn, engage in the same estimation game. Their estimate, however, would be better than mine since I am already smoothing out the flow in front of them. This computational chain could continue behind them, each time getting easier and easier to estimate the ideal throughput speed no matter how uncertain the traffic was in front of us. Is this a computation in series or in parallel? We are doing it at the same time so it is in parallel, but each driver depends on the estimate in front of them so it is in series.
