Maybe you’ve muttered it to yourself, in a moment frustration, as you tap the steering wheel and stare at a persistent red.
在失望的时候，你或许会这样自言自语，一边用指头敲着方向盘，一边盯着一直不变的红灯。

As Dr. Steven Smith points out, it’s literally true.
按照史蒂夫•史密斯博士所说，这种想法确实没错。

“The way conventional systems work, you preprogram those timing systems in advance,” he explains. “But as soon as you install them, they start to age. Patterns and flows are continually evolving.”
他解释说：“常规交通管理系统的工作方式，需要提前对定时系统进行预编程。系统安装好之后便已经开始老化。但交通模式与流量一直在持续变化。”

Reprogramming a single intersection as population and geography shifts costs thousands of dollars—so some municipalities rarely get around to it. The signal patterns keeping you stuck in traffic may be three to five years out of date, if not more.
随着人口与地形的变化，对一个十字路口进行重新编程的成本可能需要数千美元，因此，许多城市根本没有考虑这样做。那些令你陷入交通堵塞的信号模式，可能在三五年前便早已过时。

The resulting inefficiencies multiply into the broader economy. The Texas A&M Transportation Institute’s Urban Mobility Report found that in 2011, congestion cost the U.S. an aggregate $121 billion dollars, up from just $24 billion in 1982.
由此产生的低效会扩展到整体经济。德州农工大学交通研究所（Texas A&M Transportation Institute）的《城市交通报告》发现，2011年，美国的交通拥堵成本总计为1,210亿美元，而在1982年仅为240亿美元。

Smith is hoping to change that. On top of his position as a research professor at Carnegie Mellon, he’s the head of Surtrac, a startup that’s applying cutting-edge artificial intelligence and planning to traffic management. Surtrac’s smart traffic signals rely on advanced sensors and powerful processing to update their patterns, not every few years, but every few seconds, in response to shifting traffic volumes and unexpected events like accidents or road closures. They’ve been deployed in a growing pilot study in Pittsburgh’s East Liberty neighborhood since 2012.
史密斯希望改变这种状况。他不仅是卡耐基梅隆大学（Carnegie Mellon）的研究教授，也是初创公司Surtrac的负责人，这家公司将先进的人工智能技术与规划应用于交通管理。Surtrac的智能交通信号依靠先进的传感器和强大的处理技术，每隔几秒钟就更新一次信号模式，而非几年时间，以此响应交通流量的变化和意外事件，如交通事故或道路封闭等。自2012年以来，该公司在匹兹堡的东利伯蒂社区进行了初步研究。