If I have learned one thing this summer, it’s that having a clean-cut way to evaluate anything is impossible. There are so many factors to consider. It’s also very easy to become separated from the context of your research subject. Public transit is not an isolated system. It is very much a living system that is constantly responding to the changes in its environment.
Because of this, I have had to rely on both static and dynamic metrics for assessing these light rail systems. By static, I mean looking at a single year, and creating a snapshot of all of the systems and compare them on one or more measures. The dynamic analysis comes into play when I look at trends for a single city. Both approaches are valuable in determining strong systems from weaker ones.
To begin, I’d like to first make observations, using 2014 as our reference year.
This graph shows annual passenger trips versus revenue vehicle miles (RVM). RVM is essentially the amount of service provided by the transit organization. One would expect that the more service you provide, the more people will ride. And we see that with the linear model. In a very over-simplified approach, we can say that cities above the line are doing better than cities below the line. Places such as Portland and Los Angeles are getting much more riders for the amount of service they’re providing in contrast with Dallas and Denver who are getting less riders.
Let’s look at another measure.
In this graph, we have annual passenger trips versus directional route miles (DRM) per service area. This is the amount of track over the boundaries of the transit provider. In other words, this is the coverage.
Again, one would expect that more coverage would lead to more ridership, and while in general, we can see this trend, it is not nearly as strong as with RVM. In a lot of ways, this makes sense. You can have the greatest coverage of any transit system, but to do so you may have a lot of routes that go places where few people live. Sometimes it is more effective to have a more localized coverage. We see this in Houston, LA, Seattle, Minneapolis, Denver and Salt Lake City.
Now let’s take a closer look at Los Angeles to try to have a better understanding.
Los Angeles is always an interesting city to look at. This chart shows the growth of ridership, DRM and RVM. I indexed each value using the equation y(i) = (x(i)/x(first))*100. This sets the first value at 100 and every proceeding value is expressed as a percent increase from the first value. So an index of 200 means that the value is double that of year one. This lets us look at all three metrics on the same scale and from the same starting place. It allows for a quick glance comparison of growth trends.
LA has increasing ridership and directly growing RVM. DRM grew in phases since that was how the light rail in LA was built. One could argue that causality of ridership and RVM goes both ways. Increasing RVM gives more riders, and more riders causes the transit operators to put out more service via RVM. Either way, there is definitely growth happening in LA, which is really good news.
Now I want to look at a city that appeared to not do so well, Denver. In the first graph, Denver is one of the cities giving out a lot of service with RVM, but not getting a lot of riders.
We can see that from 2006 to 2012, there was no increase in DRM. Basically, Denver was not looking to expand its tracks during this time. However, there was a jump in both ridership and RVM from 2006 to 2007. Ridership looks stable from 2007 to 2012, while RVM is jumping around. To me, I think one possible explanation for this is that Denver was trying to increase ridership by putting out more service, but perhaps increased RVM too much and was then adjusting it to meet the actual demand for the light rail. Of course, the issue of causality is up for debate. One could argue that ridership went up and Denver increased service to respond, but again overshot and had to readjust. The later is probably more realistic.
If we look at 2014, which is the year the first graph uses data from, we can see that the RVM is 16x what it was in 1999, but the ridership is only around 6x from where it was in 1997. It makes sense then that Denver fell below the line in the first plot. The amount of service provided has been increasing much faster than the demand for it has.
It is unclear if that is a bad thing or not. We are not sure what pushed the service increase. But this highlights why you cannot rely solely on a single year snapshot to make an assessment. Understanding light rail performance requires you to look at the story from different angles.