Honda Invests in U.S. AI Startup, Adopting E2E Architecture to Challenge Traditional Sensor-Based Autonomous Driving Technologies
Most mainstream autonomous driving and ADAS (Advanced Driver Assistance Systems) architectures today rely on a “modular sensor fusion” approach, in which multiple cameras, radars, and LiDAR sensors collect data that are processed through several algorithmic layers for object recognition and environmental modeling, followed by decision-making and control. While this structure offers high controllability, it also entails lengthy development processes, high labeling costs, and accumulated errors between modules that often lead to less natural and consistent driving responses. Honda Motor Co., Ltd. recently announced an additional investment in California-based AI startup Helm.ai, aiming to shift its autonomous driving and ADAS development strategy from “sensor-oriented” to a new era of “AI End-to-End (E2E)” learning architecture.