In the previous post I explored the impact of stop lights on driving different speeds. Another consideration is slower traffic, which we can model in our plot as lines with lesser slopes:
The gray lines represent cars driving slower than the faster (purple) driver, some of which are also slower than the blue driver. This plot shows the hypothetical scenario of a many-lane road in which slow cars don't impede faster cars, but in real life faster drivers frequently get stuck behind slower ones. Here's a plot that briefly slows a driver when they come upon a slower car:
Again, this is a loose simulation. Drivers are always stuck behind slower cars for the same amount of time, when in reality the time varies and may actually be shorter for drivers motivated to get around impediments (i.e., speeding drivers). Also, we wouldn't expect a uniform distribution of speeds around the speed limit, but probably more of a Gaussian distribution. Finally, I didn't compound traffic: gray cars don't get trapped behind slower cars the way the blue and purple cars do.
Despite those caveats, the above does illustrate how a speeding driver bumps up against slower traffic more than a driver going the average speed. The faster drivers race from one impediment to the next. In this simulation, the result is that the gains from driving faster are cut about in half.
Finally, we'll look at strategies for choosing a speed in the next post.