First off, an apology to regular readers for the lack of posts in the past week or so. I have been working on new ways to present service reliability data together with information on bus crowding. This is now possible because the TTC includes crowding info in the data I receive from them.
Updated October 21, 2024 at 7:45am:
- The scheduled service levels for 35/935 Jane have been added.
- Charts showing the distribution of weekday headways by hour and location have been added.
TTC service metrics suffer from a lack of detail, and an inability to see what is happening to “my bus” or “my streetcar” as opposed to average service conditions over many hours, weeks and vehicles. Statistics purport to show that average loads and service lie within so-called Service Standards (about which more later) while riders wait glumly for buses that arrive in packs and have little room on board.
In past articles, I have presented charts showing the behaviour of many routes, but there are limitations of how many charts I can publish. With the advantage that I can review all of the data, patterns are more evident than might be the case with only excerpts.
One important pattern is the spacing of vehicles along a route. TTC standards assume that if service is “on time” (itself a rather loose concept) at terminals, the rest of the line will look after itself. Flatly, this is not true, but it is an assumption that lets managers collect gold stars they do not deserve.
Even on days when there is no adverse weather, traffic or special events, tracking data show that a reasonably spaced service might leave a terminal, but can degenerate into pairs (or worse) along the line. Instead of a steady “tick .. tick .. tick” of service promised by the schedule, riders experience “tick …… tick tick ….. tick .. tick ………. tick tick tick” like a drunken clock. All of the promised buses might eventually arrive, but unevenly. Of course, riders in the real world know that even at terminals, departures can be uneven, and this worsens across a route.
This contributes to crowding because the buses in wide gaps tend to have more riders, and the problem compounds as stop service times for these buses rise.
Although the TTC has released vehicle tracking data since 2007, crowding data are much more recent. Initially they showed up in the real-time data feed used by various apps, and now in the archival data I receive each month. This allows analysis of the relationship between vehicle spacing and crowding, as well as a better view of when and where routes are heavily used.
Buses have automatic passenger counters with infrared beams at doorways to keep track of entries and exits. Work to install them on the streetcar fleet is still in progress, and crowding data for streetcars is not yet available.
This article looks at bus tracking data showing crowding levels. This is a preliminary view of 35 Jane to show and explain the new chart formats. In future articles, I will dive into this and other routes in more detail.
If you have suggestions to improve these charts, please leave a comment.
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