## Round 1 - Coding ## Problem Implement a command processor for an autonomous vehicle. The vehicle has a position `(x, y)` and a heading direction (N/E/S/W). Process a sequence of commands: `F` (forward), `B` (backward), `L` (turn left 90 deg), `R` (turn right 90 deg). Return the final position and heading. ```python def process_commands(start_x: int, start_y: int, heading: str, commands: str) -> tuple[int, int, str]: # returns (x, y, heading) ... ``` ## Example ``` process_commands(0, 0, "N", "FFRFF") # F -> (0,1,N), F -> (0,2,N), R -> (0,2,E), F -> (1,2,E), F -> (2,2,E) # -> (2, 2, "E") process_commands(0, 0, "E", "FLF") # F -> (1,0,E), L -> (1,0,N), F -> (1,1,N) # -> (1, 1, "N") ``` ## Follow-ups 1. How would you add obstacles? The vehicle should stop before hitting one and report which command failed. 2. How do you handle commands to move by variable distances, like `F3` meaning move forward 3 units? 3. Extend to support a circular grid that wraps around at the edges. 4. How would you represent and process compound maneuvers like parallel parking as a named subroutine?

InterviewDB Question

Vehicle Command: Process and Execute Commands for an Autonomous Vehicle Controller

phone

Question Details

Round 1 - Coding Problem Implement a command processor for an autonomous vehicle. The vehicle has a position (x, y) and a heading direction (N/E/S/W). Process a sequence of commands: F (forward), B (backward), L (turn left 90 deg), R (turn right 90 deg). Return the final position and heading. Example Follow-ups How would you add obstacles? The vehicle should stop before hitting one and report which command failed. How do you handle commands to move by variable distances, like F3 meaning move for…

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About This Question

This is a reported interview question from a samsara interview during the phone round.

It covers the following topics: Coding, Phone, Onsite, Matrix .

Topics

Coding Phone Onsite Matrix

About Samsara Interview Reports

This question was reported by a candidate who interviewed at Samsara. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Samsara are the higher-signal extractions to take from this report.

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How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Samsara reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Samsara Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Samsara reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.