During the last week of November, the first to see streetcars return to The Beach after almost three months’ absence for construction at Kingston Road, the line had a major disruption thanks to a broken rail near Roncesvalles. This rail damaged the track brakes on 22 Flexity cars, and while the TTC searched for the problem, the line was completely switched to bus operation.

Streetcars ran on Monday and Tuesday, November 25-26, and on Wednesday November 27 until midday. Buses ran from the afternoon of November 27 to the end of service on Friday,November 29 (actually Saturday morning).

There have been calls from certain quarters on City Council for a comparison of the operation of both modes. I published an analysis of route 505 Dundas in May 2018. Broadly speaking, it showed that buses outrun streetcars only when there is no traffic in the way and operators can drive as if they are on the suburban streets they are used to.

The substitution on 501 Queen gave an opportunity to compare the two modes over the entire route, not just over a segment running with buses due to construction. This article reviews the data from November 25-29 for 501 Queen.

Methodology

The TTC has two vehicle tracking system, CIS and VISION. The streetcar fleet (and a small number of buses that often run on streetcar lines) is tracked by CIS, while most of the bus fleet is tracked by VISION. The entire system will be on VISION probably in a few years, but for the moment there are two data sources.

Until quite recently, I was unable to obtain finely-grain information about vehicle locations from VISION, but this changed in October 2019. It is now possible to get comparable data tracking vehicles from both systems. This meant that comparable data were available for both the streetcar and bus operations on 501 Queen.

The process for converting data from snapshots with GPS co-ordinates to a format suitable for analysis is described at length in Methodology For Analysis of TTC’s Vehicle Tracking Data.

In this case, we are interested in three aspects of streetcar and bus behaviour:

• How long does each type of vehicle take to get from one point on the route to another?
• What are the speed profiles for each vehicle type along the route?
• What are the dwell times for each vehicle type along the route?

For the comparatively coarse measurement of travel times between points, the route is divided by screenlines. Tracking when each vehicle crosses a screenline gives both the headways at each line, and the travel times between them.

For fine measurement of vehicle speed, the tracking data are used to calculate each vehicle’s speed as it moved along a route. The route is subdivided into 10m segments, and the speeds of every vehicle passing through that segment in each hour are averaged. This reveals locations where vehicles spend a lot of time stopped or travelling slowly, and of course locations where they move much faster.

For dwell times, the points of interest are those where vehicles are stationary. The “tick” of the clock for tracking data is every 20 seconds, and so the length of a vehicle’s stay at a point can only be calculated to a multiple of that interval. This is a fairly coarse measurement relative to the length of time most vehicles take to serve stops, and the resulting data give only a broad outline of comparative dwell times. Note also that “dwell time” is not necessarily all “stop service time” because vehicles can be awaiting a green traffic signal, or be stuck in traffic at the stop.

The distance scale to which I convert GPS positions is measured in 10m increments. Given that vehicles will not necessarily stop at exactly the same place every time, the charts here give moving averages of dwell times over 30m.

All of the analyses presented here are subdivided into hourly intervals recognizing that a route’s behaviour at 6am is vary different from midday, the two peaks, and the evening. Far too much data presented by the TTC is summarized on an all-day basis, and even on an all-route basis. This masks variations in behaviour by location and time of day, and does not give a detailed picture of what is happening.

Summary

The data reveal various aspects of bus and streetcar operation on 501 Queen, and by extension, on other routes where a substitution might be contemplated. The results for 501 echo those seen in the 2018 article on the 505 Dundas route.

• Across the entire route, buses travel faster than streetcars, but their performance varies from place to place, hour to hour.
• On sections of the route where traffic is not free flowing, and where stops are busy, buses do no better than streetcars and during some periods they are worse.
• Where traffic is free flowing, some of the advantage buses have arises from driving at above the speed limit which is 40 kph within the old City of Toronto, and 50 kph on the Lake Shore section west of the Humber River.
• The effect of streetcar slow orders at numerous locations is clearly evident in the data.
• Dwell time for buses appears to be slightly longer than for streetcars. This could be due to loading delays, but in turn that could be caused by the bus service being overwhelmed by streetcar-level demand. (There were complaints about the quality and capacity of the replacement service.) Also, buses lose time getting to and from curbside stops, but this is not necessarily reflected in “dwell times” because they are merely slow, not stopped during these moves.
• I am unable to comment on service quality with buses because many vehicles were not logged on to VISION with the 501 route number. Therefore, their data do not appear in the extract I received. However, there were enough vehicles to get a sample of their behaviour and determine travel times.

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