When it comes to autonomous vehicle economics, I think we may be focusing on the wrong number.
Vehicle cost is not the biggest variable. Utilization is.
A robotaxi spends far more of its life generating revenue than sitting in a driveway, so how often that vehicle is actually carrying passengers can completely change the economics.
Here’s the simple example from my model 👇
🚗 $70K vehicle
→ 30 rides per day
vs.
🚙 $30K vehicle
→ 25 rides per day
The more expensive vehicle can still generate better economics because it is being utilized more heavily.
That’s why trying to win the market simply by making the vehicle cheaper can backfire. If lower pricing reduces the number of rides or revenue generated per vehicle, the cost advantage starts getting overwhelmed by utilization.
And this is where the network becomes extremely important.
The fleet with access to the most consistent demand can keep its vehicles moving, maximize revenue hours and spread fixed costs across more rides.
That puts $Uber(UBER)$ in a very interesting position. 👀
Uber already has a massive rider network and can connect that demand with multiple types of vehicles and service levels. $Tesla Motors(TSLA)$ may have a major advantage in vehicle cost, but a robotaxi sitting idle is still an idle asset.
Even if Uber’s vehicles ended up costing 2x Tesla’s, higher utilization could potentially outweigh that difference.
📊 Lower vehicle cost matters.
🔥 But utilization can dominate the model.
And if that’s true, the biggest question in autonomous transportation may not be who builds the cheapest robotaxi.
It may be who can keep the most vehicles busy.
That’s the metric I’ll be watching. 👀🚗
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