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Waymo Common Problems

Elevator System Design

System DesigneasyLast reported April 2026
By AceOffer · Updated April 2026 · Reported 1× across 190+ candidate reports

Understanding the Problem

Design the operation logic for an elevator system. Start with basic scheduling for a single building: how do you handle up/down call requests from floors, how does the elevator decide its direction and stops? Then extend to multi-elevator allocation — how do you assign a request to one of N elevators efficiently? Follow-up: the building has many floors (high-rise scenario). How do you partition floors across elevators? Discuss the sky lobby concept (express elevators to a mid-level transfer floor, then local elevators for upper zones) and its tradeoffs.

Functional Requirements

Structured requirements coming soon. For now, see the full problem statement above and the deep-dive prompts below.

Non-Functional Requirements

Latency, throughput, availability, consistency targets — being authored.

The Set Up

Defining the Core Entities

Core entities (Request, Batch, Worker, Cache, etc.) — being authored.

The API

POST /endpoint → describe request shape GET /endpoint → describe response shape (API spec being authored)

High-Level Design

Component diagram + walkthrough mapping each functional requirement to a system flow — being authored.

Potential Deep Dives

These are the directions the interviewer is likely to push you. Each one has multiple valid solutions at different quality tiers.

1)The building has 100+ floors. How do you partition floors across elevator banks? What is a sky lobby and when would you use it? (when: Candidate handles basic single/multi elevator well)

Bad
Naive approach with serious trade-off — being authored.
Good
Solid baseline with reasonable trade-offs — being authored.
Great
Production-grade approach with explicit trade-off rationale — being authored.

2)How do you handle an elevator going out of service? How does the system adapt? (when: After zone partitioning discussion)

Bad
Naive approach with serious trade-off — being authored.
Good
Solid baseline with reasonable trade-offs — being authored.
Great
Production-grade approach with explicit trade-off rationale — being authored.

What is Expected at Each Level?

L4 / Mid-level
Cover happy path. Clarify scope. Identify the obvious bottleneck. Pick a reasonable storage and reasonable scaling approach.
L5 / SeniorTarget
All of the above plus: explicit failure handling, durability vs latency trade-offs, choose the right batching/caching strategy, articulate why.
L6 / Staff+
All of the above plus: organizational concerns (rollout, migration, on-call), quantitative analysis, multi-region considerations, what could go wrong with the proposed solution at 10x scale.

Insider Notes

**Common mistakes:** High-rise partitioning answer becoming disorganized/scattered without a clear framework; Not defining a concrete cost function for multi-elevator assignment; Forgetting direction compatibility when assigning requests to moving elevators **What passers do:** Progressively structured answer: single elevator → multi elevator → high-rise; Articulating a concrete scheduling algorithm (LOOK/scan) with reasoning; Proactively mentioning sky lobby and zone tradeoffs before being prompted **Why people fail:** High-rise section answered in a scattered, unstructured way with no clear framework; Staying only at a conceptual level without concrete data structures or algorithm choices **Edge cases probed:** High-rise with very many floors requiring zone partitioning; Sky lobby design and transfer floor placement; Multiple elevators — how to avoid all elevators clustering at same floor **Alternative approaches:** FCFS (First-Come-First-Served) (Simple to implement but leads to high average wait times and erratic elevator movement; not realistic for production.); Destination Dispatch (Group Control) (Passengers enter destination floor at lobby; system groups passengers going to same/nearby floors into one car. Reduces stops and travel time but requires special input hardware and more complex allocation logic.); Predictive / ML-based scheduling (Uses historical demand patterns (rush hours, lunch peaks) to pre-position elevators. Higher throughput at scale but complex to build and validate.)
Waymo · System Design · Last reported April 2026