As someone in Los Angeles who uses Waymo at least weekly, my experience is that pricing has become a bigger factor over the past few months. Rides that often used to cost me around $13-$17 before promotions are now regularly over $20. I enjoy using the service and would like to use it more, but at those prices I often choose to drive myself unless parking is difficult or I'm planning to drink.
If prices came back down, I could easily see myself using Waymo most days, potentially even for my daily commute. That makes me wonder how much pricing is affecting demand and ridership growth.
Coverage is another limitation. I would use Waymo more if it served destinations such as Woodland Hills, Pasadena, and LAX. If either my starting point or destination is outside the service area, the trip simply isn't an option.
The pickup and drop-off experience can also be frustrating at times. Waymo doesn't always allow the exact front entrance of a destination to be used, so pickups and drop-offs can end up down the street or even several blocks away. It's understandable that there are operational and safety reasons for some of these decisions, but it does add friction compared to driving yourself directly to the door.
Overall, I still like the service, but higher prices, service-area limitations, and pickup/drop-off constraints are the main reasons I don't use it more frequently.
Excellent point about pricing possibly shaping the demand curve and where supply/demand equilibrium falls. I also think the distance per trip piece is important because the per mile revenue profile looks different for a 10 trip compared to a 2 mile one. We don’t have public pricing data to my knowledge.
Interesting post! One clarification regarding the “waiting time” — I believe this actually refers to vehicle waiting time rather than passenger waiting time. So excessive vehicles on the road relative to demand would cause this number to increase and vice-versa. Here’s what found in the glossary for the “TotalWaiting” field:
“The total amount of time vehicles waited between ending one passenger trip and initiating the next passenger trip, expressed as a monthly total in hours
Waiting begins after end of previous trip's Period 3 (passenger drop off) to beginning of next trip's Period 2 (request accepted, vehicle en route to next passenger).“
My interpretation of the stable pattern since summer 2025 is that Waymo has reached an “optimal” policy with respect to dispatching cars into service vs leaving them at the depot so as not to accrue excessive deadheading mileage.
Yes that is correct, it's the 'waiting time' of the vehicle or essentially deadheading time (Period 1). The lower this number the better. Period 2 is a similar metric in that you want it to be as low as possible since that is also essentially unpaid time and the lower the number, the higher the overall efficiency.
Great topic. I can theorize a lot of reasons why the miles might flatten out. It will be interesting to see the statistics for the safety report thru the end of Q1 soon for Waymo (maybe two weeks from now). They were covering about 160,000 autonomous miles daily in the Bay Area in Q4 2025. and about 134,000 daily in Los Angeles. Matthew :: are you forecasting those miles will flatten or fall in the Waymo Safety Report?
I think they might fall but it’s something we could calculate from the CPUC data. It includes total revenue miles by quarter. Waymo is doing fewer rides but they are longer, so I would expect any fall off for miles traveled to look slightly attenuated compared to the trip curve.
As someone in Los Angeles who uses Waymo at least weekly, my experience is that pricing has become a bigger factor over the past few months. Rides that often used to cost me around $13-$17 before promotions are now regularly over $20. I enjoy using the service and would like to use it more, but at those prices I often choose to drive myself unless parking is difficult or I'm planning to drink.
If prices came back down, I could easily see myself using Waymo most days, potentially even for my daily commute. That makes me wonder how much pricing is affecting demand and ridership growth.
Coverage is another limitation. I would use Waymo more if it served destinations such as Woodland Hills, Pasadena, and LAX. If either my starting point or destination is outside the service area, the trip simply isn't an option.
The pickup and drop-off experience can also be frustrating at times. Waymo doesn't always allow the exact front entrance of a destination to be used, so pickups and drop-offs can end up down the street or even several blocks away. It's understandable that there are operational and safety reasons for some of these decisions, but it does add friction compared to driving yourself directly to the door.
Overall, I still like the service, but higher prices, service-area limitations, and pickup/drop-off constraints are the main reasons I don't use it more frequently.
Excellent point about pricing possibly shaping the demand curve and where supply/demand equilibrium falls. I also think the distance per trip piece is important because the per mile revenue profile looks different for a 10 trip compared to a 2 mile one. We don’t have public pricing data to my knowledge.
Waymo is definitely is more expensive during surge times since the only lever they have to temper demand is raising prices - https://x.com/TheRideshareGuy/status/2055842619482423558?s=20
Excellent post, Matt! Is it feasible to set up a self-updating database like Todd Schneider does for NYC ridehailing data: https://toddwschneider.com/dashboards/nyc-taxi-ridehailing-uber-lyft-data/
Love this idea. Let’s work on it!
Interesting post! One clarification regarding the “waiting time” — I believe this actually refers to vehicle waiting time rather than passenger waiting time. So excessive vehicles on the road relative to demand would cause this number to increase and vice-versa. Here’s what found in the glossary for the “TotalWaiting” field:
“The total amount of time vehicles waited between ending one passenger trip and initiating the next passenger trip, expressed as a monthly total in hours
Waiting begins after end of previous trip's Period 3 (passenger drop off) to beginning of next trip's Period 2 (request accepted, vehicle en route to next passenger).“
My interpretation of the stable pattern since summer 2025 is that Waymo has reached an “optimal” policy with respect to dispatching cars into service vs leaving them at the depot so as not to accrue excessive deadheading mileage.
Yes that is correct, it's the 'waiting time' of the vehicle or essentially deadheading time (Period 1). The lower this number the better. Period 2 is a similar metric in that you want it to be as low as possible since that is also essentially unpaid time and the lower the number, the higher the overall efficiency.
Illuminating. Thank you 🙏
Great topic. I can theorize a lot of reasons why the miles might flatten out. It will be interesting to see the statistics for the safety report thru the end of Q1 soon for Waymo (maybe two weeks from now). They were covering about 160,000 autonomous miles daily in the Bay Area in Q4 2025. and about 134,000 daily in Los Angeles. Matthew :: are you forecasting those miles will flatten or fall in the Waymo Safety Report?
I think they might fall but it’s something we could calculate from the CPUC data. It includes total revenue miles by quarter. Waymo is doing fewer rides but they are longer, so I would expect any fall off for miles traveled to look slightly attenuated compared to the trip curve.
Thanks for taking the time and a well fashioned answer.