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Lingering on the patterns of transit reported in the National Transit Database a bit further, I thought I’d look at the modes differently than last week, in their patterns and their top performers.



These are the distributions of performance by decile. Dividing their average performance by their maximum value, and binning their distribution into 10 bin s provides a rough histogram of their distribution. Too often I use averages to show data because that’s all the data I can find, but these graphs show that rare world data rarely looks like the way we assume data should group about an average. I smoothed the lines that were the most “normal” in their distributions, and left the other ones jagged. I also only considered those with enough data to provide a regular distribution, throwing out those with less than ten examples in the US.

The first decile on the left shows how what percent of agencies operating each mode were less than 10% as efficient as the maximum.  The middle of the graph shows what percent are half as efficient as the maximum.

As promised, I also want to praise the top performers in some of the transit modes:

  • Best performer overall Trips/$ : City of Portland Aerial Tramway, even better than biking
  • Best Funicular Trips/BTU : Chattanooga Area Transit
  • Best Heavy Rail in trips/ BTU and $ : MTA New York City Transit
  • Best Light Rail in both Trips/BTU and $ : MTA Harris County, TX Houston
  • Best Commuter Rail Trips/BTU : SEPTA Philadelphia Transit
  • Best Commuter Rail in Trips/$ : Peninsula corridor joint powers board, San Francisco/San Jose, CA
  • Bus best Trips/$ : UGA Transit system, Athens, GA
  • Bus best in Trips/BTU : Ames, IA Transit agency (notably both college towns)
  • Best Bus Rapid Transit in Trips/$ Regional Transportation Commission, Southern Nevada, Las Vegas
  • Best Bus Rapid Transit in Trips/BTU Los Angeles MTA

For a much later post, I’d like to compare the performance of these modes from a decade ago, to see if they have consistently been this good. I’ll want to look at changes in these pattern over time, and other stats, like route extent, vehicles in service, vehicle miles, and firebox recovery, but a bit later. For now, look at the performance patterns from last week, Trips/BTU and Trips/Operational $.

By Friday, I’ll talk a bit more about population and jobs patterns, I’ve got a busy weekend coming up and that will be good practice for it.