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Product Management Root Cause Analysis Question: Investigating autonomous truck disengagements during left turns
Image of author vinay

Vinay

Updated Dec 2, 2024

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Asked at Waymo

15 mins

What's causing the sudden increase in disengagements during left turns for Waymo's autonomous trucks on highway routes?

Problem Solving Data Analysis Technical Understanding Autonomous Vehicles Transportation Artificial Intelligence
Data Analysis Root Cause Analysis Autonomous Vehicles Product Troubleshooting Safety Metrics

Introduction

The sudden increase in disengagements during left turns for Waymo's autonomous trucks on highway routes presents a critical challenge for the safety and efficiency of our self-driving technology. This issue not only impacts our operational performance but also has significant implications for user trust and regulatory compliance. In addressing this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both immediate fixes and long-term strategic improvements.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development, ensuring a comprehensive examination of all potential factors contributing to the increased disengagements.

Step 1

Clarifying Questions (3 minutes)

  • Given the specificity of left turns, I'm thinking this might be related to a recent software update. Has there been any recent changes to the left-turn decision-making algorithms?

Why it matters: Software updates often introduce unintended consequences, and pinpointing a recent change could fast-track our solution. Expected answer: Yes, a minor update was pushed last week. Impact on approach: If confirmed, we'd prioritize code review and rollback considerations.

  • Considering the highway context, I'm curious about the traffic patterns. Have there been any significant changes in traffic density or speed on these routes recently?

Why it matters: External factors like increased traffic could strain the system's capabilities. Expected answer: Traffic patterns have remained relatively consistent. Impact on approach: If traffic isn't the issue, we'd focus more on internal system factors.

  • Thinking about environmental factors, has there been any unusual weather conditions or road work on these highway routes?

Why it matters: Adverse conditions could challenge the sensors and decision-making systems. Expected answer: No significant environmental changes noted. Impact on approach: This would lead us to investigate system-specific issues more closely.

  • Regarding system performance, have we observed any changes in sensor data quality or processing speeds preceding the left turn maneuvers?

Why it matters: Degraded sensor performance could directly impact decision-making capabilities. Expected answer: Some intermittent sensor lag has been reported. Impact on approach: This would prompt a deep dive into sensor hardware and data processing pipelines.

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