This morning on my way into the office I ran into a friend who lives in my building (downtown). She works in midtown and so I asked her how she gets into the office. She told me that she either takes the subway or an Uber, but that increasingly she has been taking Uber, particularly on the way home.

We then started talking costs and she told me that what she does is carpool with a friend from work using UberPOOL. They live nearby and so what they do is leave from the same place at night (the office) and then select a midpoint location between their homes for the drop-off. After splitting their portion of the fare, the ride costs her about $3.25.

As she was telling me this, I couldn’t help but think to myself: Wow, this is massively disruptive to transit. That is the same cost as taking the subway. So why take transit? With the subway, there may be a speed argument in certain instances, but that certainly wouldn’t be the case with some of Toronto’s streetcar lines (such as the King line). It’s faster to walk.

However, there are obviously geographic limits to how far you can go in an UberPOOL before your costs greatly exceed taking transit. But as Uber and other similar services continue to bring down the price of a ride (eventually the labor cost component will disappear), how big does that area get?

All of this – including my own mobility patterns – has got me thinking yet again about the role of transit in the city of tomorrow. 

One segment that continues to be underserved is the regional scale. Here in the Greater Toronto Area, we are working on that by transforming our commuter rail service into a two-way all-day Regional Express Rail service. Today that strikes me as being hugely valuable. And unless driverless vehicles somehow solve our traffic problem, it will likely remain that way.

I would love to get your thoughts in the comments below.

If you don’t follow the work of MIT’s Senseable City Lab, I highly recommend that you start. 

Earlier this year, researchers from the Massachusetts Institute of Technology, the Swiss Institute of Technology, and the Italian National Research Council developed something that they call “slot-based intersections.” In a world where cars have sensors and drive themselves, it is intended as a more efficient alternative to traditional intersections. Goodbye traffic lights.

Much like air-traffic control, the way the system works is by assigning individualized time slots to each car for when they may enter an intersection. For example, in the diagram below (Sequence 01) the car approaching from the bottom left (#10) has a “stop distance slot” in front of it reserved for 3 of the cars that are currently in the intersection. The two that are traveling perpendicular to it and the car currently turning left into the same lane as #10 (on the other side of the intersection). The car in the midst of turning right (#5) is exempt because there’s no possibility of collision. 

In Sequence 02 (below) you can see that car #10 is now turning left, which means it has its own time slot in the intersection. Other approaching cars now have a “stop distance slot” dependent on car #10.

In all cases, cars making a right turn are able to move freely, provided they will not interfere with any other cars.

The researchers estimate that real-time slot allocation might double the number of vehicles that a traditional traffic-light intersection can handle today and, in some cases, it might completely eliminate stop and go traffic.

Often when I write about self-driving vehicles I hear people tell me that cars are still cars. It doesn’t matter whether they are self-driving or not. The same inefficiencies apply. They are not the solution to urban gridlock. Elon Musk was also criticized (following his Master Plan) for not properly understanding urban geography.

But self-driving cars will create new efficiencies. I am not saying that they are a silver bullet, but I am saying that they will help a great deal. I don’t think that anyone truly understands the extent of these efficiencies, but there are a myriad of possibilities. This Senseable City Lab project is a perfect example.

What I am grappling with right now is the relationship between self-driving vehicles and traditional forms of public transit. Until we get a handle on the efficiencies and overall impact, it’s hard to ascertain how these different forms of mobility will work together. My gut tells me that the lines are bound to get blurry and that self-driving “cars” will feel less and less like the cars we know today.

Below is a video that was published along with the research. If you can’t see it, click here.

[youtube https://www.youtube.com/watch?v=4CZc3erc_l4?rel=0&w=560&h=315]

This morning on my way into the office I ran into a friend who lives in my building (downtown). She works in midtown and so I asked her how she gets into the office. She told me that she either takes the subway or an Uber, but that increasingly she has been taking Uber, particularly on the way home.

We then started talking costs and she told me that what she does is carpool with a friend from work using UberPOOL. They live nearby and so what they do is leave from the same place at night (the office) and then select a midpoint location between their homes for the drop-off. After splitting their portion of the fare, the ride costs her about $3.25.

As she was telling me this, I couldn’t help but think to myself: Wow, this is massively disruptive to transit. That is the same cost as taking the subway. So why take transit? With the subway, there may be a speed argument in certain instances, but that certainly wouldn’t be the case with some of Toronto’s streetcar lines (such as the King line). It’s faster to walk.

However, there are obviously geographic limits to how far you can go in an UberPOOL before your costs greatly exceed taking transit. But as Uber and other similar services continue to bring down the price of a ride (eventually the labor cost component will disappear), how big does that area get?

All of this – including my own mobility patterns – has got me thinking yet again about the role of transit in the city of tomorrow. 

One segment that continues to be underserved is the regional scale. Here in the Greater Toronto Area, we are working on that by transforming our commuter rail service into a two-way all-day Regional Express Rail service. Today that strikes me as being hugely valuable. And unless driverless vehicles somehow solve our traffic problem, it will likely remain that way.

I would love to get your thoughts in the comments below.

If you don’t follow the work of MIT’s Senseable City Lab, I highly recommend that you start. 

Earlier this year, researchers from the Massachusetts Institute of Technology, the Swiss Institute of Technology, and the Italian National Research Council developed something that they call “slot-based intersections.” In a world where cars have sensors and drive themselves, it is intended as a more efficient alternative to traditional intersections. Goodbye traffic lights.

Much like air-traffic control, the way the system works is by assigning individualized time slots to each car for when they may enter an intersection. For example, in the diagram below (Sequence 01) the car approaching from the bottom left (#10) has a “stop distance slot” in front of it reserved for 3 of the cars that are currently in the intersection. The two that are traveling perpendicular to it and the car currently turning left into the same lane as #10 (on the other side of the intersection). The car in the midst of turning right (#5) is exempt because there’s no possibility of collision. 

In Sequence 02 (below) you can see that car #10 is now turning left, which means it has its own time slot in the intersection. Other approaching cars now have a “stop distance slot” dependent on car #10.

In all cases, cars making a right turn are able to move freely, provided they will not interfere with any other cars.

The researchers estimate that real-time slot allocation might double the number of vehicles that a traditional traffic-light intersection can handle today and, in some cases, it might completely eliminate stop and go traffic.

Often when I write about self-driving vehicles I hear people tell me that cars are still cars. It doesn’t matter whether they are self-driving or not. The same inefficiencies apply. They are not the solution to urban gridlock. Elon Musk was also criticized (following his Master Plan) for not properly understanding urban geography.

But self-driving cars will create new efficiencies. I am not saying that they are a silver bullet, but I am saying that they will help a great deal. I don’t think that anyone truly understands the extent of these efficiencies, but there are a myriad of possibilities. This Senseable City Lab project is a perfect example.

What I am grappling with right now is the relationship between self-driving vehicles and traditional forms of public transit. Until we get a handle on the efficiencies and overall impact, it’s hard to ascertain how these different forms of mobility will work together. My gut tells me that the lines are bound to get blurry and that self-driving “cars” will feel less and less like the cars we know today.

Below is a video that was published along with the research. If you can’t see it, click here.

[youtube https://www.youtube.com/watch?v=4CZc3erc_l4?rel=0&w=560&h=315]