rfmcdonald | [URBAN NOTE] Chris Selley of the National Post on Toronto drivers and shortcut apps (Reply)

In "Apps promise to cut through gridlock, now if only Torontonians would learn how to drive", Chris Selley looks at Toronto drivers and how technology can help them improve, among other things.

Heading out of city hall on Wednesday afternoon shortly after five, the Swiftly transit app revealed that I had just missed a Bay Street bus. But as it turned out, I hadn’t: walking north at a leisurely pace, I soon caught up to it. And then passed it.

Then I stood on the corner of Dundas, for perhaps eight minutes, mouth agape, watching as eastbound motorists blocked the intersection over and over and over again. At one point not a single northbound vehicle made it through for three consecutive green lights. If you had been quick about it, you could have had a jolly picnic in the middle of Bay Street, anywhere between there and Gerrard.

There are many reasons for gridlock in this city. Some could be ameliorated if politicians had the courage to risk motorists’ irrational anger for the greater good: more restrictions on turns and parking; ending the ludicrous mixing of streetcars and cars; towing away illegal parkers even more mercilessly, and raising fines even more, than has been done under Mayor John Tory’s crackdown; a James Bond-style helicopter magnet that picks up intersection-blocking automobiles and drops them into a junkyard from a great height.

As such courage is not in overabundance, it is all the more satisfying to see private enterprise doing end runs around the problem. Using open data about transit vehicle locations, transit apps now compete to navigate you better through the gridlock. Some offer Toronto Transit Commission, Uber X, Car2Go and bike-share options on the same screen. Swiftly claims it can predict the next vehicle’s arrival better than its rivals, using its own algorithm.

And for motorists, there’s Waze — a free, advertising-supported GPS navigation app that routes and reroutes you, as necessary, based on other users’ speed (passively monitored as they go), and any reports of accidents, constructions or gridlock they enter into the app (hopefully not while driving). The more users there are, the more data there are to optimize your commute.