AI RESEARCH

Latency Analysis and Optimization of Alpamayo 1 via Efficient Trajectory Generation

arXiv CS.AI

ArXi:2605.08975v1 Announce Type: new Reasoning-based end-to-end (E2E) autonomous driving has recently emerged as a promising approach to improving the interpretability of driving decisions as it can generate human-readable reasoning together with predicted trajectories. Such approaches commonly generate multiple trajectories to capture diverse future behaviors, and they fall into two categories: (1) multi-reasoning, where one reasoning sequence is generated per trajectory, and (2) single-reasoning, where a single reasoning is shared across all trajectories.