One of the great features of the so-called gig economy is that many of its businesses operate with an asset-light model. Uber, for instance, relies on drivers showing up with their own cars. This is the opposite of, say, the real estate industry, which, for a lot of business models, is both capital-intensive and asset-heavy.

But there is one problem with the asset-light model, and it's that it may not work forever. The Financial Times just reported that Uber has committed to spending $10 billion over the next few years on actual cars and on equity investments in various strategic companies.

For instance, earlier this month, electric vehicle company Lucid announced that Uber will be investing $500 million in the company and buying at least 35,000 of its cars.

This is gig-economy blasphemy, but it's very obviously an existential concern for the company. Uber needs to be in the AV race, or else asset-light could be an asset-liability. The thing that helped Uber become successful in the past now seems to be what they need to overcome in this new mobility race.

On a loosely related note, I find it somewhat amusing that cities are now starting to push back against robotaxis out of fear that they will displace Uber drivers. If you were following Uber in its early days, you'll know that cities fought the company vehemently because of the taxi lobby. Now they're trying to protect it.

Cover photo by Erik Mclean on Unsplash

One of the least understood aspects of self-driving cars is the extent and capacity to which they rely on remote assistance operators (RAOs).

When a self-driving car finds itself confused in an uncertain or tricky situation (like when one rolled into an active shootout), there are typically two safety valves. The first is a manual override, where someone like a first responder might jump into the front seat and take control of the steering wheel. And the second is assistance from a remote operator.

If the car gets confused, a human can tell it, "Hey, you, follow this path." But how often is remote assistance being called upon? And who is actually responding on the other end? Apparently, the answer is, "I don't know."

According to a recent report from Senator Ed Markey, every major AV company refuses to disclose how often they rely on an RAO. And in the case of Waymo, they rely on overseas operators in places like the Philippines.

This has led to new proposed legislation that would, among other things, limit the number of vehicles that a single RAO can oversee, mandate that the RAO be located in the US, and require the humans to hold a local driver's license. You know, so they're sure to know the rules of the road.

There's a lot to figure out, and it seems a bit messy. But that's what it takes. As one would expect, this is par for the course when you're trying to rewrite urban mobility.

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We’ve been talking about the merits of congestion pricing for as long as I’ve been writing this blog. But it remains politically unpopular, despite the overwhelming evidence that it consistently does what it’s supposed to do: it reduces congestion, shortens commute times, improves air quality, and raises money for alternative modes of transport, among other things. 

The status quo bias is strong, but right now we have an opportunity. Self-driving cars are in the midst of shifting the mobility landscape, and there’s a growing belief that (1) roads are going to need to be more accurately priced to deal with the surge in demand, and (2) this is a moment in time that grants us the opportunity to do it. Here’s a recent tweet by Chris Spoke of Toronto Standard that makes this point and that I agree with.

The basic idea behind point number two is that many voters don’t like the idea of a congestion charge for themselves, but will probably mind a charge on robot cars a lot less — both because they are robot cars and because there are relatively few of them on the road today. However, at some point, robot cars will form the majority of vehicles on the road, so now would be a good time to establish new practices.

What do you think?

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