許多消費者期待自動駕駛能盡快普及化，讓移動過程更為輕鬆，然而近日美國的自動駕駛監管再度升溫，美國國家公路交通安全管理局(NHTSA)日前正式升級對Tesla Full Self-Driving (FSD)駕駛輔助系統的調查層級，從初步評估(Preliminary Evaluation)進入工程分析(Engineering Analysis)，涵蓋約320萬輛車。此舉不僅代表調查進入更關鍵階段，也代表未來啟動強制召回的可能性大幅提高，對Tesla當前與未來的技術戰略形成實質壓力。

在自動駕駛技術持續推進的浪潮下，Nvidia 正試圖從單一晶片供應商，進一步躍升為整個產業的核心平台提供者。近日在GTC 2026上，執行長黃仁勳宣布最新進展，顯示其Drive Hyperion自動駕駛平台正快速獲得全球車廠與移動服務業者採用，並逐步建立一個涵蓋硬體、軟體與AI模型的完整生態系。

Against the backdrop of the rapid evolution of intelligent driving technologies in mainland China, Huawei is expanding the penetration of its driver assistance systems across the broader automotive market with a clear and increasingly aggressive pace. According to recently disclosed plans, Huawei aims to deploy its Qiankun ADS driver assistance system in more than 80 vehicle models within this year. This represents a significant increase from approximately 30 models as of November 2024, underscoring that Huawei’s strategic focus in automotive technology is steadily taking shape.

In an era when autonomous driving is highly dependent on digital and electrical infrastructure, Waymo’s recent experience during a large-scale power outage in San Francisco unexpectedly became a real-world test of how driverless systems respond to extreme scenarios. The outage, triggered by a fire at a power substation, disrupted the daily lives of up to 130,000 customers and directly impacted Waymo’s autonomous ride-hailing service. Multiple vehicles came to a halt mid-journey at intersections or in the middle of roadways, causing tangible disruptions to urban traffic and the passenger experience.

Level 4 autonomous driving has already been achieved by some automakers and activated on specific routes, but mass-market personal adoption is still some distance away. Tensor’s Robocar, promoted as the world’s first personally owned Level 4 autonomous vehicle, raises the question of whether it can redefine the future of the automotive industry in terms of technology, business models, and market positioning.

Chinese electric vehicle manufacturer Xpeng recently unveiled a series of new technologies at its Tech Day, including a self-driving taxi, plans for a flying car business, and a next-generation robot. However, the centerpiece of the event was undoubtedly the upgraded semi-autonomous driving platform “VLA 2.0,” which has drawn significant attention across the automotive industry. The system will not only be rolled out across mainland China but will also be made available for other automakers to adopt. German automotive giant Volkswagen will be the first partner to collaborate on this technology. Xpeng made it clear that the goal of VLA 2.0 is to surpass Tesla’s Full Self-Driving (FSD) system.

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.