An implementation of Uber’s "Fare Estimator" [CodeSignal]

CodeSignal put out a challenge by Uber that involves writing a "fare estimator" that involves a function dependent on cost per minute, cost per mile, ride time and ride distance.

The formula is along the lines of:

fare = (cost per minute) * (ride time) + (cost per mile) * (ride distance)

where ride time and ride distance are constant integers (or floats) and cost per minute and cost per mile are lists of integers and floats (as cost per minute and cost per mile depend on the car type).

This is my solution:

def fareEstimator(ride_time, ride_distance, cost_per_minute, cost_per_mile):
    y, f = (), lambda w, x, y, z: (w * x) + (y * z)
    for a, b in zip(cost_per_minute, cost_per_mile):
        y.append(f(a, ride_time, b, ride_distance))
    return y

I’m just looking for any kind of feedback on the code. Is there a better way to implement it? Can you recommend better coding styles? Is my algorithm good or is it a steaming pile of wank? Leave any feedback you want!

You can check out the full challenge here (but you might need to sign up): https://app.codesignal.com/company-challenges/uber/HNQwGHfKAoYsz9KX6