谷歌无人驾驶汽车又撞了

上周五，谷歌的一辆用于测试无人驾驶技术的雷克萨斯测试车在加州的山景城遭到了一辆闯红灯的汽车撞击。有目击者称，这起事故是谷歌无人驾驶汽车遭遇的几起事故中最严重的一起，好在据称现场并无人员伤亡。

从摄于事故现场的一张照片中可以看出（这张照片可以在9TO5Google网站上查看），撞击谷歌路试车的这辆州际电池公司（Interstate Batteries）的面包车明显应负全责。据谷歌公司的一份声明称：“在我们的测试车驶入十字路口之前，绿灯至少已经亮了6秒钟。”

目击者表示，在事故发生后，“几名晕头转向的谷歌员工”坐在路边等待拖车。

此次事故与特斯拉公司的无人驾驶技术的几起事故形成了鲜明对比。毕竟特斯拉的事故还造成了一起人员伤亡，这说明特斯拉的监测系统在态势感知和响应方面还存在一些不足。这次谷歌的路试车虽然也被撞得挺惨，但我们也不能责怪它，毕竟事故的责任方是那辆闯了红灯的面包车。

不过此次事故也指出了围绕着无人驾驶汽车的另一个问题——未来几十年里，无人驾驶汽车可能还得与不靠谱的人类司机们共享路权。高盛公司的最近一份报告就指出，以当前的车辆置换率和拥车模式来看，北美地区要想全面落地无人驾驶汽车，至少得等到2060年。

在这种情况下，又会有一种新的问题出现——一旦发生了交通事故，拥有预判和避免人类司机的驾驶错误能力的无人驾驶系统，又该在事故中承担多少责任呢？ （财富中文网）

译者：朴成奎

On Friday, a Lexus outfitted with Google autonomous driving technology was struck by a vehicle that ran a red light in Mountain View, California. Some observers say it is the worst crash that Google’s autonomous vehicles have been involved in. There were no reported injuries.

A photo of the aftermath (which you can see at 9TO5Google) shows the Interstate Batteries van apparently at fault. According to a statement from Google, the autonomous vehicle’s “light was green for at least six seconds before our car entered the intersection.”

Witnesses said that after the crash, “dazed Google employees” sat waiting for a tow truck.

The crash is in significant contrast to recent incidents involving Tesla vehicles driving in Autopilot mode. Those crashes, including one that was fatal, suggested at least some failure of the vehicles’ detection systems to properly read and respond to their environment. But it’s hard to lay much blame on Google’s system for being t-boned by a van running a red light.

Instead, the crash shows a much different problem for driverless cars—that they will continue to share the road with fallible human drivers for decades to come. A recent Goldman Sachs report points out that, at least using current replacement rates and ownership models, it could be 2060 before the North American auto fleet reaches full autonomy.

Under those circumstances, a new sort of question arises—how much responsibility will autonomous systems have for anticipating and avoiding the errors of old-fashioned human drivers?