Intelligent driving has become one of the most eye-catching core selling points for new energy vehicles. From the initial simple adaptive cruise control to today’s urban navigation-assisted driving, the pace of technological iteration has far exceeded expectations. Yet, beyond their amazement, consumers harbor doubts: Is it truly reliable?
Current State of Technology: The L2+ “Human-Machine Co-pilot” Era
Most intelligent driving systems in current models are still transitioning from Level 2 (Partial Automation) to Level 3 (Conditional Automation). Mainstream approaches fall into two camps:
Tesla’s Vision-Only Approach—Relying on cameras and powerful algorithms to perceive the world like human eyes. Low cost but questionable stability in extreme weather.
Chinese brands’ multi-sensor fusion approach—combining cameras, millimeter-wave radar, and lidar to create a “triple safeguard,” offering higher system redundancy but at a correspondingly higher cost.
Regardless of the approach, both explicitly require drivers to remain attentive and ready to take control at any moment—this is an “assist” system, not a “replacement” system.
User Experience: A World of Difference Between City and Highway
Highway scenarios have become the “comfort zone” for intelligent driving. On closed, structured roads, the system handles lane changes, overtaking, and on/off-ramps with remarkable smoothness, significantly reducing fatigue during long drives. Many users report, “Driving long distances without intelligent driving assistance feels unnatural now.”
Urban roads present a completely different challenge. Faced with disorderly non-motorized traffic, sudden pedestrian crossings, complex construction zones, and ambiguous traffic signs, the system still frequently exhibits “sudden braking” or “oversteering,” resulting in a high takeover rate. Using it during rush hour can sometimes increase mental stress.
Safety Hazards: Technical Bottlenecks and Human Risk
True danger often emerges at the system’s boundaries—when the vehicle encounters “extreme cases” not included in its training data. Examples include:
Irregularly shaped obstacles (e.g., fallen cargo)
Extreme weather (heavy rain, intense glare, dense fog)
Ambiguous road markings
Greater risks stem from driver overconfidence. When the system performs reliably, people may mistakenly assume “it can handle anything,” leading to distraction or even leaving the driver’s seat—a pattern linked to multiple severe accidents.
Regulatory Constraints: Legal Gaps and the Technology-Law Mismatch
Global regulations lag significantly behind technological advancement. Most countries and regions still mandate that drivers bear full responsibility for accidents, regardless of automation levels. This means legal liability remains with the “human” even when systems fail. Establishing true “driverless” liability frameworks and insurance systems remains a challenging endeavor.
Rational Recommendations: Be a Mindful User
Define Boundaries: Understand your vehicle’s capability limits and never force its use in hazardous situations.
Stay Focused: Keep hands on the wheel and eyes on the road, always ready to take control.
Adapt Gradually: Begin with simple road conditions to build understanding and trust in the system.
Stay Updated: Intelligent driving systems evolve through OTA updates; timely upgrades enhance performance
Intelligent driving is not “autonomous driving.” It functions more like an ever-learning co-pilot. While profoundly reshaping how we drive, it remains far from fully replacing human drivers—a journey requiring collective growth. In this technological revolution, maintaining reverence and rationality may be our most essential form of “intelligence.”
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