Broadly speaking, cities tend to have better data on vehicular traffic than on pedestrian and bicycle traffic. This is because road design has traditionally prioritized the movement of cars, above all else. So it has felt right to bias traffic counts. But there are lots of places where pedestrians and cyclists greatly outnumber vehicles.

For example, I was on Queens Quay yesterday visiting my mom and, if you've ever been to Toronto's waterfront in the summer, you'll know that it has one of the busiest bike lanes/trails in the city — if not the busiest. But if you ask ChatGPT just how busy it is, it will more or less say, "I don't know. Really busy?" And that's because we don't have real-time usage data. We have estimates. And the same is true of pedestrian counts.

(If you're aware of a great dataset, please share it in the comment section below.)

But this is starting to change with the advent of AI traffic monitoring solutions that can handle multi-modal environments. Meaning they're capable of counting everything from pedestrians and scooters to cyclists and trucks. This is what cities need to make better decisions. And as this new tech becomes more widespread, I think it's going to show us just how much we've been missing.

Cover photo by Joshua Chua on Unsplash

Matt Elliott writes a newsletter called the City Hall Watcher. And one of his features is something called Intersection Inspection. It is where he does a deep dive into traffic counts and modal splits for intersections across Toronto. This week, he covered Yonge & St. Clair in midtown, and so I thought it would be interesting to share it on the blog. (Thanks to Canada Record for the tag on X.)

Here are traffic counts for the intersection going back to 1984:

What seems clear is that Yonge & St. Clair is fairly evenly divided between cars and pedestrians. And it has been this way going back many decades. At the same time, though, the volume of cars seems to be declining. According to the above data, cars haven't seen a count above 20,000 since 2014. There does also seem to be a slight spike in bike usage recently (this is broken out further in Matt's newsletter).

Data is crucial to good city building and I don't think it is leveraged nearly enough. For example, take the intersection of Baldwin St and Kensington Ave in Toronto's Kensington Market. If you look at the traffic counts (which can also be found in the above newsletter), you'll see that 88% of traffic tends to be from pedestrians (79%) and bikes (9%). Only 12% of traffic is from cars.

With this data in hand, you might, then, ask yourself: Should Kensington Market be mostly pedestrianized? And in my opinion, this is a lot easier to answer when you have numbers in front of you telling you how humans actually occupy the area.