SDPAD: A Fully Spike-Driven Pipeline for End-to-End Autonomous Driving

This paper introduces SDPAD, a fully spike-driven end-to-end planning pipeline for autonomous driving. It converts pre-trained ANN perception stacks into integer-spike form, lifts multi-view images into BEV space using Spike-3D-Lift, and plans through Spike-QFormer, a spiking query transformer. SDPAD achieves high accuracy and low energy consumption, outperforming previous SNN planners and matching mainstream ANN planners in energy efficiency.