Well, you start with a rough sketch. It’s a lot of fun to go back and make it bigger and better. After several iterations, it becomes clear which route is most efficient.
What is the most efficient route that can take my bus?
In order to answer that question, you need a lot of good data. Bus routes are generally divided by two features: proximity to other nodes, and a minimum fare between nodes.
Here are two typical examples of two similar maps from the same study. The first is based on routes of New York City, the second on routes of the U.K., and the size of the blue and green markers is meant to indicate the average distance of the two cities. I will use this technique in more detail during the discussion of cost reduction.
In the U.K. map you can see that while distance between buses is slightly better than in the U.S. route the difference is minuscule and there is practically nothing to gain by moving from U.K. to U.S.
What you want is a way to map all the distance between nodes in your route from A to B. One way to do that is to make a map that splits each node into segments that are as far apart as possible. The method described below uses a grid of squares that are oriented in such a way that the distance from any node in a square between two points can be calculated.
This way is much cleaner than the routes in the U.S. map where you find many different routes that have one common element that is an “I” in green.
In an earlier tutorial, we saw that one method for calculating the average distance between two places (as shown in the lower right-hand part of the U.S. map) would lead to a map that looks quite similar to a standard route map. In this section you will see that the alternative route was faster.
The main benefit of using this method is that you don’t need a complete route to calculate the average distances between two places, as long as you have a map that is a subset of the route. In the U.S. and British maps most people have more than one city or town with which to connect their places.
A simple algorithm for calculating average distances between places is as follows:
Draw a map of all cities or towns that share a single place on the map. Find the average distance between the places. If the distances between the
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