观车 · 论势 || 平衡好智能网联汽车“创新速度”与“安全责任”

Core Viewpoint - The development of intelligent connected vehicles is at a critical juncture, facing challenges in safety and commercialization costs, with safety being the cornerstone of this evolution [1][4]. Group 1: Safety Challenges - Intelligent connected vehicles face three main safety challenges: insufficient capability to handle "long-tail scenarios," inherent limitations in perception and cognition, and uncontrollable risks due to the "black box" effect of deep learning systems [1][2]. - The transition from passive collision safety to a comprehensive safety system encompassing network security, data security, and driving safety reflects a fundamental shift in safety responsibilities [3][4]. Group 2: Technological Innovations - New technologies such as AI large models, vehicle-road-cloud integration, and low Earth orbit satellite communication are breaking through industry development bottlenecks [2][3]. - AI large models enhance decision-making logic in autonomous driving, enabling systems to respond to non-standard scenarios at millisecond speeds, thus continuously filling cognitive gaps [2]. - Vehicle-road-cloud integration is crucial for ensuring the safe operation of autonomous driving systems, leveraging intelligent roadside terminals and cloud computing capabilities [2]. Group 3: Policy and Industry Direction - The "14th Five-Year Plan" emphasizes the steady development of intelligent connected vehicles, with government reports highlighting the need to effectively prevent and mitigate safety risks [4]. - The integration of emerging technologies will lead to new paradigms for preventing network security risks in intelligent connected vehicles, with a focus on specialized, high-quality safety products and services [4]. - The balance between innovation speed and safety responsibility is essential for sustainable industry growth, with the goal of demonstrating that machine driving can be safer than human driving [4].