what metrics would you use to evaluate aurora's autonomous vehicle software?

Introduction

Evaluating Aurora's autonomous vehicle software requires a comprehensive approach to product success metrics. To address this challenge effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders. This approach will help us assess the software's performance, safety, and user experience, as well as its business impact and technological advancement.

Step 1

Product Context

Aurora's autonomous vehicle software is a complex system designed to enable vehicles to operate without human intervention. Key stakeholders include:

1. End-users (passengers)
2. Fleet operators
3. Regulatory bodies
4. Aurora's engineering team
5. Investors and partners

The user flow typically involves:

1. Requesting a ride
2. Vehicle arrival and passenger boarding
3. Autonomous journey
4. Arrival at destination and passenger disembarking

This software is crucial to Aurora's strategy of becoming a leader in the autonomous transportation industry. Compared to competitors like Waymo and Cruise, Aurora's focus on trucking and ride-hailing provides a unique positioning.

In terms of product lifecycle, Aurora's software is in the growth stage, with ongoing refinement and expansion of capabilities.

Software-specific context:

• Platform: Likely a combination of proprietary software and open-source components
• Integration points: Vehicle control systems, sensors, mapping data, and cloud infrastructure
• Deployment model: Over-the-air updates for continuous improvement