Austin Robotaxi Launch: Size Demand and Fleet, Plan Peaks, Choose Operate or License
Company: Perplexity
Role: Product Manager
Category: Product / Decision Making
Difficulty: medium
Interview Round: Other
You are launching a self-driving ride service (a robotaxi) in Austin, Texas. Size the opportunity, work out the fleet you need, plan for busy and quiet periods, and recommend a business model.
### Clarifying Questions
- Do we own the self-driving technology, so that licensing it to others is a real option?
- Does the service cover the whole Austin metro area from day one, or a smaller launch zone such as downtown and nearby neighborhoods?
- Is the service passenger rides only, or can idle vehicles carry deliveries too?
- Should the estimates describe the first year after launch or a mature steady state?
### Part 1 — Market size and demand
Estimate how large the market for this service is in Austin and how many rides per day it could serve in its first year.
```hint Build up from trips
Start from how many trips people in the Austin area take each day, then narrow down to the trips a launch-stage robotaxi could actually serve.
```
#### What This Part Should Cover
- A clear equation with every input labeled as an assumption, in round numbers.
- The difference between the total market and the share reachable in a limited launch zone.
- A sanity check on the result.
### Part 2 — Fleet size
From your demand estimate, decide how many vehicles the fleet needs, and explain what "optimal" means for this decision.
```hint What one vehicle can do
Work out how many rides one vehicle can complete in an hour, counting the drive to the rider and the time before it is ready again, and compare that with demand in the busiest hour.
```
#### What This Part Should Cover
- Rides per vehicle per hour, built from trip time, pickup time and turnaround.
- Busiest-hour demand, target utilization and the share of the fleet unavailable at any moment.
- The cost of an extra vehicle compared with the value of the rides it adds.
### Part 3 — Peak and off-peak plan
Describe how you would run the service through peak and off-peak periods.
```hint Use the quiet hours
Think about what the vehicles not needed at 4 a.m. should be doing, and which levers can shift or absorb demand when it exceeds what the fleet can serve.
```
#### What This Part Should Cover
- When Austin's peaks happen, including large events, and what drives them.
- Levers for peaks that do not require a larger fleet.
- Productive uses of off-peak time, such as charging, cleaning and maintenance.
### Part 4 — Operate the fleet or license the technology
Compare running your own fleet with licensing the driving technology to another company, and recommend an approach for Austin.
```hint Follow the money and the risk
For each model, ask who buys the vehicles, who keeps the fare, and who carries the safety and brand risk if something goes wrong.
```
#### What This Part Should Cover
- Revenue per ride and capital required in each model.
- Control over safety, rider experience and operating data.
- A recommendation, plus the conditions that would change it.
### What a Strong Answer Covers
- One consistent set of assumptions carried through all four parts.
- Arithmetic shown step by step, with sanity checks.
- Austin-specific demand drivers and constraints rather than a generic city.
- Autonomy-specific factors such as a geofenced service area, remote assistance and regulation.
- A recommendation that names the assumptions it is most sensitive to.
### Follow-up Questions
- Which assumption is your estimate most sensitive to, and how would you test it before buying vehicles?
- A major festival pushes downtown demand far above your normal peak for a week. How do you serve it without permanently growing the fleet?
- How would the operate-or-license choice change if you planned to expand to many more cities over the next two years?
Overview: A multi-part estimation and strategy case about launching a robotaxi service in Austin. It tests sizing the market and daily demand, deriving fleet size from busiest-hour demand, planning operations for busy and quiet periods, and weighing running the fleet against licensing the driving technology.