I went urban/rural split right away which felt right, but I fumbled the actual numbers mid-calculation.
Break the problem into a simple equation: total hours = (number of drivers) × (average hours stuck per driver per year). Segment the driving population by urban vs. rural, since traffic congestion is heavily concentrated in urban areas, and estimate each segment's average delay using reasonable assumptions about commute frequency and congestion levels.
Pro tip: State your assumptions clearly and round numbers to make mental math easy; the interviewer cares more about your structured thinking than the exact final number. Also, mention that you'd validate your estimate with real-world data sources like INRIX or TomTom traffic indices if available.
Confirm that 'drivers' includes all licensed drivers who drive regularly, and 'stuck in traffic' means time spent in congested conditions beyond free-flow travel time. Decide whether to include all trips or just commutes.
Split the U.S. population into drivers and non-drivers, then further divide drivers into urban, suburban, and rural based on where they live, as traffic exposure varies significantly by area type.
For each segment, estimate the number of days per year they drive in congested conditions, the average delay per congested trip, and the number of such trips per day. Multiply to get annual hours per driver.
Multiply the number of drivers in each segment by their average annual delay, sum across segments, and compare the result to known benchmarks (e.g., INRIX reports ~99 hours per driver in 2022 for the U.S.) to ensure plausibility.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.