SORTA’s topological years

SORTA's transit system map from 1977

And we wonder why people might be desperate for the relative simplicity of a limited rail system?

I’ve been digging around a bit more in those documents I got from Dave Walters a while back. There’s a whole directory of system maps! 64 of them…dear Zeus! What a gold mine.

I think the one above, from 1977, is actually my favourite even if it does have a somewhat jarring effect. SORTA seems to have produced strongly topological maps like this one from the 1970’s through to the late-1990’s. A topological map is one that emphasizes connections over the realistic placement of all elements. Connections are of course critical in any transit system, so emphasizing them makes a lot of sense if it doesn’t produce otherwise harmful distortions. Also, since time spent on transit is often not-very-strongly related to the distance travelled, there may be relatively little value to spatial accuracy for many users.

The 1977 map is actually moderately legible on closer examination:

1977 system map sceenshot

Pre-70’s maps had been mostly geographically accurate, though they often distinguished poorly between different lines.  From 1954:

1954 Cincinnati transit map

The system map of 1999 was the first to reject the topological perspective of the 1970’s. This map favours spatial accuracy and loses  much in topological clarity. Consider closely for example, the 17 through Northside in both maps.

SORTA's 1999 transit system map of cincinnati

This map also begins to include the lines of non-stop express routes which tend to add a lot of clutter but are of little use for most of their length. SORTA and TANK have since been producing only slight variations on this 1999 map as far as I can tell, and it’s these types of maps I was reacting against when I produced my own (topological) map in 2011.

a portion of the cincinnati frequent transit map

The current system map, which SORTA just released about nine months late, clearly continues the recent pattern of showing locations accurately at the cost of clarity about topology and connections.

2014 transit system map screenshot

I really do suspect this recent topological ambiguity has something to do with the continuing demand for simpler new routes which tend to be mapped in isolation. Can we ever expect a return to topological system mapping techniques?

Here, by the way, are some fuller versions of all of these maps:

 

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An approximation of service frequency

Here is a rather crude, though I think useful, visualization of service frequency at the stop level. Basically, I used the GTFS data from SORTA and TANK to calculate the number of times a bus stops at each stop every week. Since a week is the basic cycle period of transit(service is bad on Sunday, better on monday), this should give us a an idea of basic average frequency with the huge caveat that there’s enormous variation within each week.

map of the approximate frequency of greater cincinnati transit system

Click the image to get a bigger version. There’s lot’s of interesting detail in there!

You may notice that frequency can appear vary in a single line where it doesn’t seem like it probably should:

Map of Ludlow Avenue in Clifton, Cincinnati

Ludlow Avenue

In most cases, this is simply an artifact of the way I grouped stops that were next to each other and had exactly the same name. At least 2-3,000 stops of the 6,000 stops in the dataset can reasonably be thought of as pairs with one serving each direction of travel.

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Posted in: Analysis | Data | Maps
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TANK service plan proposals

Surprise! TANK has prepared a lucid, well thought out and even decently mapped explanation of what exactly they might like to do with their routes in the future.

TANK service plan map

Provided by TANK

The description is even all tangled up with a survey to get your thoughts on the plan right as you’re having them! Go take it!

I’ve got a few of my own relatively minor critiques of the plan but I think by and large this is all very sensible and will constitute an overall improvement. Really, I just see a couple missed opportunities like the Southbank Shuttle alignment and the lack of consideration given to possible short Covington-to-Newport-and-back trips that would need higher (combined) frequencies to make them work. I’m particularly excited by the idea of a high-frequency(every 15 mins) corridor between Downtown Cincinnati and Latonia.

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Posted in: Plans
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Updated Frequencies

Below is a visualization of weekly frequency for each of SORTA’s routes, derived from the just-released GTFS data. The area of each square is directly proportional to the number of trips a route will make each week after the August 18th, 2013 service changes. The #1 at the top will make a total  of 232 weekly trips. The m+ at the bottom will make 595. The route with the most weekly trips is the 43 with 1,289.1 I’ll let them talk for themselves now:

Visualisation of weekly frequency for SORTA's 2013 service changes

I’ve been meaning to write a really simple little graph-generating script for a while. I’ve been unhappily living with Excel and OpenOffice forever as has everyone, and their ability to make visualisations is just NOTHING compared to the simplicity of SVG combined with a language like PHP. Just a couple hours coding and a little time tweaking in Inkscape and boom! Coloured squares. Oh yeah.

*does a little dance*

I didn’t choose the colours by the way. Those were in the data in a field marked simply ‘route_colors’. Someone at SORTA picked them. Any colour theorists in the audience want to offer a psychoanalysis?

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  1. A trip here is somewhat loosely defined. In almost every case, it’s the journey from the far end of a route’s path to the other. The journey back to the starting point is another trip. I’m being a touch lazy and not looking at the actual shapes though. I know there have been instances in the past, though I can’t say for sure if there are any cases of it in this data, where for some technical reason a trip as just defined is split into two or more trips for the purpose of encoding it neatly in the data. If that’s happening here, it will distort the visualization and I won’t know any better. I simply haven’t looked. I’m tired and it’s my bed time. Plus, a quick glance over and it seems to pass the smell test. No huge outliers that I immediately notice.
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