| I think you're not considering the full problem. You are describing a particular greedy algorithm wherein each individual car gets home as fast as they can.
1) Car #1 gets home as quick as they can by following closely.
2) Car #2 gets home as quick as they can by following closely, given #1.
3) Car #3 gets home as quick as they can by following closely, given #1+#2.
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Yes, given 1..N, the course of action which minimizes your own time is to follow closely. I agree. And people will probably act that way. But that doesn't make it an optimal solution.
Consider that car #1 introduces several seconds of delay due to braking and acceleration. Then car #2 does. Then car #3. By the end, you've got hours of delay built-in. Optimal is obviously hard to define. But most people would agree that it's not every driver maximizing their personal interests to a globally shitty end. Everyone following closely is the prisoner's dilemma where both betray each other. Consider the following alternate thought experiment.
Flow of traffic is very much non-linear. That's what stop and go does -- it introduces cascading delay where there was none. Suppose roads are just 10-15% over capacity, and it results in a global average commute time of 1h instead of 45 minutes. This is not unrealistic.
What if every day, 20% of drivers leave 1h later, thus preventing stop and go and keeping commutes to 45 minutes. Even if you counted their extra hour as commute time, the average is still less 1h. I'm not saying this is a good idea (though strategies like this have been used in some cities). I'm just saying that are ways to get everyone home faster than everyone maximizing self-interest [co-operative self-driving cars please!]. |