An Exposure-Time-Aligned Primary-Path Architecture for Autonomous-Driving ECUs

Engineering notes

Key topics: autonomous driving, end-to-end, perception. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

While end-to-end (E2E) autonomous driving has become the dominant research direction, production vehicles continue to rely on modular multi-NN pipelines for a non-trivial transitional period. The subject of this paper is the design of an architecture that, during this phase, supports a modular pipeline and an E2E path side by side and embeds a path for staged migration. Transplanted to a production SoC, egalitarian late fusion is compute-inefficient and offers no natural unit for staged E2E substitution. As an alternative, we propose three design principles: (i) Primary-Path, which explicitly selects a primary perception chain and prioritizes its enclosure within a single SoC pair over the non-critical paths (ii) Exposure-Time-Aligned, which propagates the primary sensor's exposure time $τ_{\rm exp}$ as a tag along the chain and event-drives the fusion node on matched $τ_{\rm exp}$ rather than a fixed cycle and (iii) Co-Path Coexistence, which, building on (i) and (ii), lets an E2E output path co-run with the modular pipeline within the same $τ_{\rm exp}$ cycle. On a Dual-SoC production AD-ECU, the implementation closes camera-shutter to planner-output latency at a mean of 296 ms within the 350 ms design budget. Under (iii), the modular pipeline is primary at production launch and the E2E path runs as shadow on real vehicles, and the E2E scope is expanded as evaluation evidence accumulates.

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