Updated May 12, 2025 at 3:40pm: The text of the summary explaining the motion has been changed.

A motion before the TTC Board meeting on May 14 seeks to have staff examine ways to make service more reliable:

TTC4.9 – Optimizing Scheduling Efficiency and Enhancing Service Planning Using Technology – by Chair Jamaal Myers, seconded by Commissioner Dianne Saxe

Recommendations

Chair Jamaal Myers, seconded by Commissioner Dianne Saxe, recommends that the TTC Board:

1. Direct TTC staff to conduct an analysis of surface corridor TTC routes where multiple TTC routes operate on the same corridor to optimize scheduling efficiency, improve blended headways and customers wait times and identify opportunities and implications for scheduling and operational adjustments that minimize bunching and gapping and enhance coordination between routes serving the same corridor.

2. Direct TTC staff to explore opportunities to use artificial intelligence (AI) and predictive analytics to enhance our service planning and scheduling and management of gapping and bunching, and report back through the Strategic Planning Committee on best practices and priority actions to be integrated in the 2026 Operating and Capital Budgets.

Summary

Original version: This motion directs staff to review bunching and gapping on all routes where multiple TTC routes use the same corridor to explore how scheduling can be optimized to improve headways and reduce bunching and gapping of vehicles. This motion also directs staff to explore how Al and predictive analytics can be used to enhance service planning and the management of gapping and bunches on all routes and make recommendations for priority actions that could be integrated into the 2026 Operating and Capital budgets.

Revised version: Currently, TTC vehicles are not considered “bunched” for purposes of route planning, if multiple buses are traveling together so long as they are representing different bus routes. This motion directs staff to review bunching and gapping on all routes where multiple TTC routes use the same corridor to explore how scheduling can be optimized to improve headways and reduce bunching and gapping of vehicles. This motion also directs staff to explore how Al and predictive analytics can be used to enhance service planning and the management of gapping and bunching on all routes and make recommendations for priority actions that could be integrated into the 2026 Operating and Capital budgets.

There are several problems with this motion, but a few are key.

• The idea of a “scheduled” time simply does not work especially when service is fairly frequent. Riders care about regularity, not that each bus or streetcar is spot on its assigned time. Yes, of course, if the service were “on time”, it might also be regular, but forcing this to occur is counter-productive. The question is how to ensure reliably even spacing between vehicles.
• The TTC’s Service Standards and the rules operators are supposed to follow are based on the schedule, but this is not a workable guide to running service under typical conditions found on busy routes. If the TTC really wants evenly spaced service, then this should be the standard the organization aims for.
• There will always be some variation between ideal and actual vehicle locations whether this is measured by a schedule or by a target headway spacing. That’s the nature of transit even on a completely protected route like the subway. The goal is to control and minimize this variation before small problems become very large ones.
• Many streets are served by a single route with no branches or overlaid service, and headways are not reliable. This problem shows up throughout the day, not just in periods where external forces such as surge loads, traffic congestion and plagues of frogs can be blamed. The TTC should learn how to run “simple” routes reliably, and then we can talk about more complex route structures.
• “Artificial Intelligence” does not learn out of thin air, but from a combination of examples and goals. If we train bots on the collected works of Donald Trump, don’t expect Shakespearean verse. So it is with Toronto’s transit. The current system is hardly an example to learn from, and even with input from other cities, the basic question of goals must be answered. If we tell the bot to optimise for general traffic and transit will benefit oh-by-the-way, the bot will quickly say “look at all those cars” and move them as quickly as possible.

I have written many articles reviewing service behaviour on routes, and the problem of irregular service has, if anything, grown worse over the years. In “the old days” there were issues with the adequacy of scheduled travel times combined with growing traffic congestion, and this led to lengthened trips. Even where operators get adequate time for terminal breaks, this does not guarantee reliable service, although it does reduce the need for short turns.

Those short turns are a valid response to service problems. For a time, a simplistic embargo on this service management technique actually worsened bunching because gaps could not be filled by a judicious turnback. Vehicles stayed in bunches.

TTC management, with the tacit approval of the Board if only through their ignorance, produced reports showing that on average the service wasn’t too bad. “TTC’s goal is to have 60% of all trips meet the on-time performance standard.” [Service Standards at p. 15] This is an all-day average and individual periods could vary without affecting the overall metric.

Every rider knows that the “average” service is not what pulls up (or not) to their stop every day.

Quality is measured only from the terminal, and two closely-spaced cars will run nose-to-tail fairly quickly because the first one does all of the work. They will stay together for an entire trip, and possibly the return.

Service standards allow vehicles to be up to five minutes late, but on a frequent route that can mean long gaps are followed by a pair of vehicles. Oddly enough, the standards actual recognize that riders care more about vehicle spacing for frequent services (10 minutes or better) than if buses are on time, and yet the metric routinely used by the TTC is schedule based, not headway based.

This not a scheduling problem, but a policy and management that aim low. It’s easy to get a gold star on an exam where you can be almost correct, and then only 60% of the time.

Traffic congestion, construction delays and special events generating surge loads are predictable to a point, although traffic accidents are not. The question is how the TTC deals with these events. Either all schedules are padded on spec in case of delays, an expensive way to deal with an issue that does not affect most routes at most times, or there has to be a recognition that scheduling alone will not solve the problem.

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