2025-09-19

Application of Statistics in Urban Transit Systems

When designing and planning complex urban transit networks, statistics and use patterns are extremely helpful for planners, designers, and engineers that end up making decisions that can affect millions of commuters every year (sometimes even over a billion)

Example Data for Comparison

We will use the 2023 metrics from the Federal Transit Authority to compare heavy rail in the following cities:

##            city primary_uza_population
## 1      Brooklyn               19426449
## 15   Washington                5174759
## 23  Los Angeles               12237376
## 36       Boston                4382009
## 43      Chicago                8671746
## 47 Philadelphia                5696125

Plotly Plot

This plot compares cities’ populations with the number of people its heavy rail system moves every hour, as well as the financial component as well.

GGPlot

Filtering out the heavily-used New York Subway and the smaller heavy rail on islands, it becomes easier to compare cities’ heavy rail usage straight across.

GGPlot

ggplot(nonNY, aes(x=unlinked_passenger_trips,
                  y=total_operating_expenses, color=factor(city), 
                  label=city)) + geom_point() + plotLabels

Math Equations for Comparison

It is also sometimes easier to compare networks by assigning each city a score based on a common equation, and directly comparing the values. Some common equations include the farebox recovery and trips per capita:

\[Farebox Recovery = {Total Fare Revenues \over Total Operating Expenses}\] \[Trips Per Capita = {Unlinked Passenger Trips \over Metro Population}\] We can combine these metrics into a weighted score:

\[Transit Score = {0.5 * Farebox Recovery + 3 * Trips Per Capita}\]

Transit Scores for Comparison

Using these transit scores we can compare the following cities:

\[Los Angeles = 0.5 * {11,040,864 \over 192,351,180} + 3 * {26,854,945 \over 12,237,376} = 6.6\]

\[Chicago = 0.5 * {154,677,879 \over 725,296,800} + 3 * {117,447,140 \over 8,671,746} = 40.7\]

\[Philadelphia = 0.5 * {51,017,856 \over 240,404,145} + 3 * {57,976,426 \over 5,696,125} = 30.6\]

From these scores it is clear that Chicago does the best at providing its citizens with heavy rail, and Philadelphia is close behind. Despite Los Angeles being the largest city and metro of the three, it falls way behind in terms of its heavy rail.