譯/莊蕙嘉
期待雖高 自駕車仍處於遙遠未來
A year ago, Detroit and Silicon Valley had visions of putting thousands of self-driving taxis on the road in 2019, ushering in an age of driverless cars.
一年前，底特律和矽谷曾有2019年讓數千輛自動駕駛計程車上路的願景，要開啟無人駕駛車的時代。
Most of those cars have yet to arrive — and it is likely to be years before they do. Several carmakers and technology companies have concluded that making autonomous vehicles is going to be harder, slower and costlier than they thought.
這些車大多數還沒上路－而且很可能還要等好多年才會上路。數家汽車製造商和科技公司已作出如下結論：製造自動駕駛車將比他們以為的更困難、更緩慢且更花錢。
"We overestimated the arrival of autonomous vehicles," Ford's chief executive, Jim Hackett, said at the Detroit Economic Club in April.
「我們對自駕車問世的評估過於樂觀。」福特汽車執行長吉姆．哈克特今年4月在底特律經濟俱樂部這麼說。
In the most recent sign of the scramble to regroup, Ford and Volkswagen said Friday that they were teaming up to tackle the self-driving challenge.
福特和福斯周五(12日)宣布要合組團隊以迎接自駕車的挑戰。這也是業界忙著重新組合、再次出發的最新跡象。
The two automakers plan to use autonomous-vehicle technology from a Pittsburgh startup, Argo AI, in ride-sharing services in a few urban zones as early as 2021. But Argo's chief executive, Bryan Salesky, said the industry's bigger promise of creating driverless cars that could go anywhere was "way in the future."
這兩家汽車製造商計畫使用匹茲堡新創公司「亞果人工智慧」的自駕車技術，最快於2021年在一些都會區提供共乘服務。但是亞果的執行長布萊恩．薩勒斯基說，這個產業更大的承諾，也就是創造可去到任何地方的自駕車，「還在遙遠的未來」。
He and others attribute the delay to something as obvious as it is stubborn: human behavior.
他和另一些人將這個延誤歸咎於顯而易見且難以應付的一項因素：人類行為。
Researchers at Argo say the cars they are testing in Pittsburgh and Miami have to navigate unexpected situations every day. Recently, one of the company's cars encountered a bicyclist riding the wrong way down a busy street between other vehicles.
亞果研究人員說，他們在匹茲堡和邁阿密測試的車輛，每天都須經歷無法預期的狀況。最近，這家公司一輛車遇到一名自行車騎士，在一條車多的街道上逆向行駛在車輛間。
Another Argo test car came across a street sweeper that suddenly turned a giant circle in an intersection, touching all four corners and crossing lanes of traffic that had the green light.
另一輛亞果的測試車遇到一輛掃街車，在一個十字路口突如其來大轉彎，碰到四個街角，而且橫越已經轉為綠燈的車道。
"You see all kinds of crazy things on the road, and it turns out they're not all that infrequent, but you have to be able to handle all of them," Salesky said. "With radar and high-resolution cameras and all the computing power we have, we can detect and identify the objects on a street. The hard part is anticipating what they're going to do next."
「你在路上見到所有瘋狂的事，而且發現它們並非那麼不常見，但你必須有能力處理所有狀況。」薩勒斯基說。「我們擁有雷達、高解析度鏡頭和所有電算能力，可偵測並識別街道上的物體。困難的部分是預測它們下一步會做什麼。」
Salesky said Argo and many competitors had developed about 80% of the technology needed to put self-driving cars into routine use — the radar, cameras and other sensors that can identify objects far down roads and highways.
薩勒斯基說，自駕車進入日常使用所需技術，亞果和許多競爭對手約已開發成功80%－雷達、攝影鏡頭及其他可在一般道路和高速公路識別遠方物體的感應器。
But the remaining 20%, including developing software that can reliably anticipate what other drivers, pedestrians and cyclists are going to do, will be much more difficult, he said.
但是剩下的20%，包括開發能夠可靠預測其他駕駛人、行人和自行車騎士下一步行動的軟體，會難得多。
A year ago, many industry executives exuded much greater certainty. They thought that their engineers had solved the most vexing technical problems and promised that self-driving cars would be shuttling people around town in at least several cities by sometime this year.
一年前，許多業界高管還展現出遠比當下更有把握的態度。當時他們認為，他們的工程師已解決最困難的技術問題，且承諾自駕車今年之內，至少可在幾個城市輸運民眾。
說文解字看新聞
結合汽車製造與最新科技的自動駕駛車是近年焦點。本文在前三段就使用了自駕車常見的三個英文同義詞：autonomous/self-driving/driverless cars，autonomous意為maneuvered by computers without human intervention，字首的auto即有「自動」之意。
Sensors, GPS and high-resolution cameras都是自駕車的基本技術，這些配備由汽車電腦指揮控制，將捕捉的數據和影像轉換成行車所需資訊。
不過文中也提到，開發挑戰在於人為因素。即使設備可以識別出行人、其他駕駛或自行車騎士，但難以預期他們的行為，也可說是unpredictable。換句話說，It is difficult to determine the intentions of pedestrians, cyclists or other drivers.
包括福斯、福特、Google、Uber在內的諸多汽車及科技業者都在研發自駕車技術，但道路測試時仍須有人坐在駕駛座緊急應變。
