Broad question and I kind of froze for a second trying to figure out where to even start.
Start by giving a high-level overview of the autonomous vehicle system as a pipeline of perception, prediction, planning, and control, then dive into each component with technical depth. Emphasize the trade-offs and challenges in system design, such as sensor fusion, real-time constraints, and safety redundancy, to demonstrate engineering maturity.
Pro tip: Highlight how Cruise's specific approach (e.g., using a combination of LiDAR, radar, and cameras with redundancy) addresses edge cases and safety, showing you understand the company's technology and priorities.
Describe the autonomous vehicle as a perception-action loop: sensors collect data, perception interprets it, prediction forecasts other agents, planning decides the path, and control executes it. Mention the need for robust software infrastructure and safety mechanisms.
Explain how sensors like LiDAR, radar, cameras, and GPS provide complementary data, and how sensor fusion (e.g., Kalman filters, deep learning) creates a unified environment model. Discuss trade-offs like cost, range, and robustness in different conditions.
Cover how the system predicts the behavior of other actors (vehicles, pedestrians) using probabilistic models, and how planning algorithms (e.g., A*, RRT, optimization) generate safe and efficient trajectories. Mention real-time constraints and uncertainty handling.
Describe how control systems (e.g., PID, MPC) translate planned trajectories into steering, acceleration, and braking commands, ensuring smooth and safe vehicle operation. Highlight the importance of low-latency and fail-safe mechanisms.
Discuss how all components integrate into a reliable system, including redundancy, failover, and testing (simulation, closed-course, public roads). Emphasize safety standards and regulatory considerations.
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