Unit 5 — the metered meter, demand-based surge, and stable pricing

Fare Estimation & Pricing

The rider sees one number before they tap Confirm: the price. Get it right and they ride; get it wrong — quote $12, charge$ 19 — and you lose them. That number is built directly on the distance and ETA from Units 1 and 4, then bent by the live balance of supply and demand.

This unit builds upfront pricing piece by piece — the metered meter, the surge multiplier that clears the market, the smoothing and hysteresis that keep it from flickering — and you implement each one, check it with python test.py, and unlock the next with a deterministic checkpoint.

Preview — Sub-unit 1

The problem: a reliable upfront fare

Quote a reliable upfront fare before the trip and keep pricing responsive to demand, without whiplash for riders or arbitrary swings.

Functional

Estimate the fare from route distance and duration before the trip.
Apply demand-based surge per pricing zone.
Return a transparent breakdown: base, distance, time, surge, fees.
Honor the quoted upfront price unless the route materially changes.

Non-functional

Sub-millisecond fare computation on the request path.
Surge that tracks demand without oscillating.
Respect regulatory caps and transparency rules.
An immutable audit trail for every quote.

Constraints

Distance and ETA inputs are themselves estimates (Units 1, 4).
Demand and supply shift minute to minute per zone.
Surge events are noisy — most last under five minutes.
Cached multipliers can go stale between refreshes.

Uber's own framing: surge pricing is a market-clearing mechanism. When requests outnumber drivers in an area, a higher price does two things at once — it rations scarce cars by pricing out some demand, and it pulls more drivers toward the shortage. The multiplier is the actuator of a supply/demand control loop, not an arbitrary markup.

Pro content

Fare Estimation & Pricing

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