解决实际问题:Waymo 和 Waze 如何应对旧金山的路坑
An Actual Smart Fix: How Waymo And Waze Are Tackling Potholes In San Francisco

原始链接: https://www.zerohedge.com/markets/actual-smart-fix-how-waymo-and-waze-are-tackling-potholes-san-francisco

## 旧金山利用科技应对坑洼路面 旧金山通过Waymo和Waze之间的合作,正在改进其道路维修系统。Waymo的自动驾驶汽车将自动检测并报告坑洼和路况不佳的情况,直接发送到Waze应用程序。 这些数据将输入Waze的“Waze for Cities”项目,为地方机构提供超越传统311报告的实时信息。虽然不会取代现有系统,但它为优先维修和确保所有社区都能得到公平关注提供了宝贵的信息补充。 Waze已经利用驾驶员报告和车辆行为(如突然刹车)来识别道路危险。Waymo的贡献使这一过程自动化,有望实现更快、更全面的道路维护——这种模式对像新泽西州和纽约州面临类似基础设施挑战的城市可能大有裨益。

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原文

A smart new approach to fixing road issues is taking shape in San Francisco—and honestly, it’s finally a good idea. 

Waymo, known for putting driverless cars on city streets, is now teaming up with Waze to help identify potholes. Using data from its self-driving vehicles, Waymo can detect rough road conditions and automatically flag them in the Waze app, according to a new report from NBC

Drivers using Waze can already see these reported potholes, but the bigger impact comes from Waze’s “Waze for Cities” program. Thousands of cities use it to collect real-time road hazard data, giving local agencies a clearer picture of where repairs are needed.

The report notes that San Francisco officials say this won’t replace existing systems like 311 reports, but it adds another valuable layer of information. Crews still aim to fix major issues within a few days, while also making sure all neighborhoods—not just high-traffic areas—get equal attention.

This kind of tech-driven system actually makes a lot of sense. Bringing something like this to places like New Jersey or New York could seriously improve how quickly and fairly road repairs get handled.

Before partnering with Waymo, Waze had already developed a crowd-sourced approach to identifying road hazards like potholes. Drivers using the app could manually report issues in real time, tagging exact GPS locations of potholes, debris, or rough road conditions, which were then shared with other users to improve routing and safety.

Over time, Waze also leveraged passive data—such as repeated sudden decelerations or erratic vehicle movement patterns—to infer the presence of road irregularities without explicit reports. This combination of active user input and behavioral data allowed Waze to build a dynamic, continuously updated map of road quality, laying the groundwork for more automated detection methods later explored in collaborations with autonomous driving systems.

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