That's a great observation, and it’s worth emphasizing that current autonomous vehicles (AVs) are already designed to handle diverse weather conditions safely. Modern AVs use sensor fusion, integrating inputs from cameras, LiDAR, radar, and even weather data to detect and respond to changes in real time. This allows them to navigate safely through challenges like rain, fog, snow, or icy roads by adjusting speed, trajectory, and braking behavior dynamically.

What makes the peer-to-peer (P2P) approach proposed in the blog even more powerful is its ability to enhance this capability further. By enabling AVs to share real-time environmental insights like slippery road conditions, reduced visibility zones, or localized weather anomalies across the fleet, each vehicle benefits from the collective intelligence of the swarm.

While trains are inherently safer in constrained, predictable environments, AVs are already equipped to handle unpredictable, open environments. The P2P model takes this a step further, ensuring resilience and safety even as weather conditions change across seasons and locations.