Self-Driving Cars on SoloSoft

Experts Say Self-Driving Cars Are the Elephant in the Room; We Still Have Time t

Mon, 01 Jan 0001 00:00:00 +0000

What “Problem” Does the “Solution” of Self-Driving Cars Actually Address?

Self-driving cars are presumed to be a panacea for traffic congestion, accidents, and pollution, but this premise itself needs serious scrutiny. The future envisioned by technological optimists often overlooks the complexity of transportation systems and their social costs. Do we really need another type of private vehicle to “optimize” already overburdened roads? Or is the real problem the urban structure overly reliant on private transport? The promotion of self-driving cars must first answer a fundamental question: Is it meant to perpetuate a “car-centric” development model, or serve as a transitional bridge toward a “human-centric” multimodal transportation system?

The Transparency Crisis in the Autonomous Driving Industry： Why It's the Next Fl

Mon, 01 Jan 0001 00:00:00 +0000

Is Remote Assistance a Technological “Safety Net” or a Business Model “Fig Leaf”?

The answer is clear: it is both. Remote assistance is essentially a transitional solution for autonomous systems when facing long-tail edge cases, but it has evolved from a temporary tool into an indispensable pillar of commercialization. The problem is that when the thickness and load-bearing capacity of this pillar become trade secrets, the public and regulators have no way to judge how “autonomous” the “self-driving” vehicles on the road truly are.

According to data from the California Department of Motor Vehicles (DMV), Waymo logged over 3 million miles of “fully driverless” travel in San Francisco in 2025, but the number of “remote assistance requests” during that period has never been disclosed. Industry experts estimate that in complex urban environments, there could be several to dozens of situations requiring human intervention per thousand miles. This information asymmetry creates a dangerous perception gap: a huge chasm exists between the public’s belief in “AI taking full responsibility” and the reality of “human-machine hybrid decision-making.”

Why L3 Autonomy Stalled — and Why China Still Forces Carmakers Ahead

Mon, 01 Jan 0001 00:00:00 +0000

Why is L3 Autonomy “Praised but Not Embraced”? The Dual Pressure of Market and Regulation

Simply put, L3 technology is trapped in a “death triangle” of high cost, low usage, and strict regulation. The retreat of BMW and Mercedes-Benz is not due to immature technology, but rather the inability to find a scalable and profitable business model at this stage. Consumers feel uneasy about the ambiguous liability of “hands-off but must be ready to take over,” leading to extremely low feature activation rates. Simultaneously, regulatory restrictions in various countries on operating conditions (such as geofencing, weather, speed) significantly diminish its practical value. For every L3 system sold, automakers bear high R&D amortization, sensor costs, and potential legal risks, yet cannot translate these into corresponding revenue or brand premium.