LEI·2025-12-17 13:01Autonomous Driving Technology & Strategies - Tesla adopts a pure vision approach, relying solely on cameras, aiming to reduce hardware costs by thousands of dollars per vehicle [1] - Rivian employs a multi-modal sensing approach, integrating vision, radar, and LiDAR for enhanced safety and reliability, especially in adverse conditions [1] - The integration of camera images, radar electromagnetic waves, and LiDAR point clouds within milliseconds poses significant algorithmic and computational challenges for multi-modal systems [1] Business Models in Autonomous Driving - Robotaxi (Mobility as a Service - MaaS) aims to eliminate driver costs, which account for 70%-80% of Uber's operating expenses [1] - Software as a Service (SaaS), exemplified by Tesla FSD and Rivian's future systems, transforms car manufacturers' revenue structure into a subscription-based model with gross profit margins exceeding 80% [1] Competitive Advantages & Industry Dynamics - Self-developed chips (like Tesla's FSD chip and Rivian's 5nm chip) are crucial for achieving a closed-loop autonomous driving business model [2] - Data flywheel effect, driven by vast amounts of data collected from vehicles, enhances AI capabilities and driving experience, creating a positive feedback loop [2] - Traditional automakers risk becoming hardware assemblers if they rely on third-party solutions like Nvidia or Mobileye, losing control over core value and profits [2] Market Outlook - The next two years are expected to be a period of rapid technological and business model advancements in autonomous driving [2]