这揭示了自动驾驶发展的基本规律：规模化应用必然面临各种极端场景的检验。真实道路环境的复杂程度远超实验室模拟，从特殊天气到突发事故，从信号故障到道路施工，每个特殊场景的发现与解决，都可能成为系统进阶的阶梯。
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The overall human driver crash rate is commonplace, and made possible due to the longstanding data reporting practices almost universally present throughout the United States and much of the world. There is a strong historical precedent for examining year-over-year trends and systemic challenges facing entire geographic driver populations. While crash data offers some insight into various performing subsets (e.g., factors like vehicle type or driver intoxication), the corresponding VMT data typically lacks such fine-grained granularity for detailed breakdown. For example, to be able to compare crash rates for factors like driver intoxication, you would need to know the VMT for drivers with intoxication or estimate it. Significantly less effort has been dedicated to isolating specific subsets of drivers for comprehensive crash risk analysis.
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