What End-to-End AI Systems Mean for the Future of Automated Driving

Aptiv engineering VP Guillermo Pita explains how end-to-end AI differs from traditional modular ADAS by training a single model to learn driving behavior directly from data instead of chaining separate perception, tracking, planning and control modules. He cites more human-like driving as the main advantage, with explainability and debugging as the key challenges, and names data diversity rather than raw mileage as the central training problem.