what metrics would you use to evaluate waymo's self-driving technology?

Introduction

Evaluating Waymo's self-driving technology requires a comprehensive approach to product success metrics. To address this challenge effectively, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders. This approach will help us assess the technology's performance, safety, user experience, and business viability.

Step 1

Product Context

Waymo's self-driving technology is an advanced autonomous driving system that aims to revolutionize transportation by enabling vehicles to operate without human intervention. Key stakeholders include:

1. Users (passengers)
2. Regulators and policymakers
3. Waymo (as a company)
4. Investors
5. Other road users and pedestrians

The user flow typically involves:

1. Requesting a ride through an app
2. Waiting for the vehicle to arrive
3. Entering the vehicle
4. Traveling to the destination
5. Exiting the vehicle

This technology fits into Alphabet's broader strategy of leveraging AI and machine learning to solve complex real-world problems. Compared to competitors like Tesla and Cruise, Waymo has focused more on a geofenced approach, gradually expanding its operational domain.

In terms of product lifecycle, Waymo's self-driving technology is in the growth stage, having moved beyond initial testing to limited commercial deployment in select cities.

Hardware considerations:

• Sensor suite (LiDAR, cameras, radar)
• On-board computing systems
• Vehicle integration

Software considerations:

• AI and machine learning algorithms
• Real-time decision-making systems
• Cloud-based mapping and data processing