Estimate Lifetime Hours a Person Spends Waiting at Intersections and Traffic Lights

Quick Overview

An estimation question for product manager interviews that asks how much total time an average person spends at traffic intersections over a lifetime. It tests defining the quantity, breaking it into trips, intersections and waiting time across life stages, doing clean arithmetic with clear units, and sanity-checking the result.

Estimate Lifetime Hours a Person Spends Waiting at Intersections and Traffic Lights

Company: Google

Role: Product Manager

Category: Product / Decision Making

Difficulty: medium

Interview Round: Other

Estimate how much time, in total, a typical person spends at traffic intersections across their whole life. ```hint Make one trip the unit Work out what a single trip loses at intersections first, then think about how the number of trips changes from childhood to old age. ``` ### Clarifying Questions - Does "an intersection" mean every intersection the person passes through, or one specific intersection, such as the one nearest their home? - Should I count time spent as a pedestrian and as a passenger, or only time spent driving? - Should I count only time spent stopped at red lights and stop signs, or also the seconds spent moving through the intersection? - Should I model a typical resident of a car-dependent US metro area, or a global average person? ### What a Strong Answer Covers - A precise definition of what counts as time at an intersection and which travel modes are included - A clear equation that breaks the total into trips, intersections per trip and average delay per intersection, segmented by life stage - Labeled, defensible assumptions with clean arithmetic and correct unit conversions - A sanity check against total daily travel time, and a range showing which assumption moves the answer most ### Follow-up Questions - How would your estimate change for someone in a dense city who mostly walks, compared with a rural driver? - Which single assumption is your answer most sensitive to, and what data would you use to pin it down? - How could a navigation product such as Google Maps use an estimate like this, for example in routing or arrival-time predictions?

Overview: An estimation question for product manager interviews that asks how much total time an average person spends at traffic intersections over a lifetime. It tests defining the quantity, breaking it into trips, intersections and waiting time across life stages, doing clean arithmetic with clear units, and sanity-checking the result.

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Google
Oct 5, 2024
mediumProduct ManagerOtherProduct / Decision Making
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Estimate how much time, in total, a typical person spends at traffic intersections across their whole life.

Clarifying Questions Guidance

  • Does "an intersection" mean every intersection the person passes through, or one specific intersection, such as the one nearest their home?
  • Should I count time spent as a pedestrian and as a passenger, or only time spent driving?
  • Should I count only time spent stopped at red lights and stop signs, or also the seconds spent moving through the intersection?
  • Should I model a typical resident of a car-dependent US metro area, or a global average person?

What a Strong Answer Covers Guidance

  • A precise definition of what counts as time at an intersection and which travel modes are included
  • A clear equation that breaks the total into trips, intersections per trip and average delay per intersection, segmented by life stage
  • Labeled, defensible assumptions with clean arithmetic and correct unit conversions
  • A sanity check against total daily travel time, and a range showing which assumption moves the answer most

Follow-up Questions Guidance

  • How would your estimate change for someone in a dense city who mostly walks, compared with a rural driver?
  • Which single assumption is your answer most sensitive to, and what data would you use to pin it down?
  • How could a navigation product such as Google Maps use an estimate like this, for example in routing or arrival-time predictions?