csdn無人駕駛汽車

The first self-driving vehicles were ships. After centuries of wrestling with wind and waves, ancient sailors devised contraptions that harnessed these forces of nature to fill in for man. They were simple but ingenious solutions, like the sheet-to-tiller system, which is still used today.

噸他第一次自駕車車輛是船舶。 經(jīng)過數(shù)個世紀的風(fēng)浪搏斗，古老的水手們設(shè)計出了各種裝置，利用這些自然力量來為人類填充。 它們是簡單但巧妙的解決方案，例如如今仍在使用的單頁紙耕機系統(tǒng)。

To rig it, you simply take the jib sheet (the rope that controls the smaller sail up front) and run it around a pulley and back across the deck. Finish by tying the bitter end to the tiller (the stick that steers the boat). Now, when a gust hits and the boat starts to round up into the wind, the jib will pull the rope around the pulley and yank the tiller, steering the vessel back the opposite way.

鉆機它，只需采取懸臂片(是c ontrols較小帆前面的繩)并運行它圍繞滑輪和橫跨甲板背面。 通過將苦味的一端綁到分till(操縱船的棍棒)上來完成。 現(xiàn)在，當(dāng)陣風(fēng)襲來，船開始向風(fēng)轉(zhuǎn)彎時，副臂將拉動滑輪周圍的繩索并拉起分till，使船向相反方向行駛。

Tricks like this helped clever mariners relieve the fatigue of long shifts at the helm during the Age of Sail. You can use it to crack open a cold one and enjoy the spray as your yacht plows through the whitecaps like a train on rails. And while tillers were repurposed to steer the first automobiles, this old technique didn’t make the leap from sea to land — though we can imagine some frightful, fruitless attempts to make it do so. By 1891, the introduction of the steering wheel, by Benz, put the matter to rest.

這樣的技巧幫助聰明的水手減輕了航海時代掌舵時長班輪的疲勞。 您可以使用它來裂開寒冷的空氣，并在游艇像鐵軌上的火車一樣駛過白帽時享受噴霧。 盡管將耕作機重新用于駕駛第一批汽車，但這項古老的技術(shù)并沒有實現(xiàn)從海上到陸地的飛躍，盡管我們可以想象到一些可怕而徒勞的嘗試。 到1891年，奔馳引入了方向盤，此事才得以解決。

On land, self-steering actually got harder when machines replaced animals. Motorization was a vast improvement over draft animals’ muscle power, but the gain came at the expense of brain power. It had long been common for riders on horseback, and even cart drivers, to fall asleep at the reins. Their dutiful animals would simply keep following the road or stop dead in their tracks.

在陸地上，當(dāng)機器代替動物時，自我指導(dǎo)實際上變得更加困難。 機動化是對牲畜的肌肉力量的巨大改進，但是獲得卻是以腦力為代價的。 長期以來，騎馬者甚至手推車司機都在at繩上入睡。 他們盡職盡責(zé)的動物只會繼續(xù)走這條路，或者死在他們的足跡上。

Cars and trucks, however, needed drivers to guide them second by second. Their soaring popularity, combined with the growing risks posed by their weight and speed, birthed a variety of experimental self-steering schemes. One 1925 demonstration of a remotely controlled vehicle in New York City offered a glimpse of driverless autos to come, simultaneously tantalizing and terrifying the public. Cruising down Broadway before thousands of onlookers, the optimistically named American Wonder drove “as if a phantom hand were at the wheel,” reported the New York Times.

但是，汽車和卡車需要駕駛員一秒鐘地引導(dǎo)他們。 他們的聲望飆升，再加上體重和速度帶來的風(fēng)險不斷增加，催生了各種實驗性的自我指導(dǎo)方案。 1925年在紐約市進行的一次遙控車輛演示展示了即將到來的無人駕駛汽車，同時也激怒了公眾并使他們感到恐懼。 據(jù)《紐約時報 》報道，樂觀地命名為《美國奇跡》的美國人在百老匯前向百老匯巡游，開車“就像幻影般的手在操縱方向” 。

In the 1920s, motor vehicles claimed tens of thousands of lives annually — a death rate 18 times higher than today. This new technology promised to render city streets safe once again. But those hopes were soon dashed when the futuristic vehicle’s operators lost control — first at Sixty-Second Street and again moments later at Columbus Circle — before finally crashing the would-be wonder into another vehicle.

在1920年代，機動車輛每年奪走數(shù)萬人的生命，死亡率比今天高18倍。 這項新技術(shù)有望再次使城市街道安全。 但是，當(dāng)這輛未來派汽車的操作員失去控制時，這些希望很快破滅了-首先在第六十二街，然后在哥倫布圓環(huán)(Columbus Circle)失去了時機-最終使可能的奇跡撞上了另一輛車。

Despite this early misstep, the auto industry continued to daydream about remote-controlled cars. At the 1939 World’s Fair, the Futurama exhibit by General Motors featured an enormous motorized diorama of an American city. Free-flowing highways plied by self-driving cars, trucks, and buses crisscrossed bustling districts of slender skyscrapers. There was even a “traffic control tower” where, the future city’s designers imagined, dispatchers would direct the movements of tens of thousands of vehicles by radio. By the 1950s, guide wires embedded in the road surface had replaced radio as the preferred technology for remote-controlled vehicles. Ironically, it was RCA, the Radio Corporation of America, that staged the first successful demonstration of this approach in the 1950s.

盡管出現(xiàn)了這些早期失誤，但汽車行業(yè)仍在幻想著遙控汽車。 在1939年的世界博覽會上，通用汽車的Futurama展品展示了美國城市巨大的電動立體模型。 無人駕駛的汽車，卡車和公共汽車在通行的高速公路上縱橫交錯，遍布繁華的細長摩天大樓。 甚至有一座“交通管制塔”，在這座未來城市的設(shè)計師想象中，調(diào)度員將通過無線電指揮成千上萬輛汽車的行駛。 到1950年代，嵌入在路面中的導(dǎo)絲已取代無線電，成為遙控車輛的首選技術(shù)。 具有諷刺意味的是，美國無線電公司RCA在1950年代首次成功演示了這種方法。

These early prototypes showed the technical feasibility of automated driving, but their high cost and the lackluster demand for such features meant that neither radio-controlled nor wire-guided cars caught on. The price tag for guided-vehicle highways was thought to be as high as $200,000 per lane-mile. If fully built out, this road upgrade might have added more than 40 percent to the cost of building the Interstate Highway System, already the largest public works project in American history. Meanwhile, despite the dangers and drudgery of long or late-night drives, automakers were still riding a wave of consumer excitement about driving. They focused on producing powerful new cars that were exhilarating to drive.

這些早期的原型展示了自動駕駛的技術(shù)可行性，但是它們的高成本和對此類功能的低迷需求意味著無線電控制和有線引導(dǎo)汽車都不會流行。 有人認為，引導(dǎo)車輛的高速公路的價格高達每車道英里20萬美元。 如果完全修好，道路升級可能會增加州際公路系統(tǒng)建設(shè)成本的40％以上，該系統(tǒng)已經(jīng)是美國歷史上最大的公共工程項目。 同時，盡管長途或深夜駕駛有危險和煩惱，但汽車制造商仍然在消費者對駕駛的興趣激增的浪潮中。 他們致力于生產(chǎn)令人振奮的強大新車。

These early dreams imagined a self-driving future based on external guidance. But by the 1960s, the focus had shifted to harnessing the new technology of computers to design vehicles that could truly, independently drive themselves autonomously, without outside help. At Stanford University, for the first time anywhere, researchers built robots that used cameras to see and computers to navigate. In highly controlled experiments, these early droids followed white lines and avoided obstacles placed in their path.

這些早期的夢想設(shè)想了基于外部指導(dǎo)的自動駕駛未來。 但是到了1960年代，重點已經(jīng)轉(zhuǎn)移到利用計算機的新技術(shù)來設(shè)計能夠真正獨立地自動駕駛而無需外界幫助的車輛。 在斯坦福大學(xué)，研究人員首次在任何地方建造了機器人，這些機器人使用相機進行查看，并使用計算機進行導(dǎo)航。 在高度受控的實驗中，這些早期機器人沿白線行駛，并避免在其路徑上放置障礙物。

Self-driving wasn’t confined to the laboratory for long. CPUs and image-processing techniques improved, so that by the late 1970s engineers at the University of Tsukuba’s Mechanical Engineering Lab were able to test the world’s first self-driving passenger vehicle, on Japanese roads. Traveling at speeds up to 20 miles per hour, these first AVs used two video cameras to visually detect street markings. In the 1980s the action moved to Europe, where Ernst Dickmanns, a professor at West Germany’s Armed Forces University, retrofitted a Mercedes-Benz van with self-driving gadgets of his own design, launching a decade-long collaboration with auto giant Daimler.

自動駕駛并沒有長期局限于實驗室。 CPU和圖像處理技術(shù)得到了改進，因此到1970年代末，筑波大學(xué)機械工程實驗室的工程師已經(jīng)能夠在日本的道路上測試世界上第一輛自動駕駛乘用車。 這些首批自動駕駛汽車以最高時速20英里的時速行駛，使用兩個攝像機來視覺檢測街道標記。 在1980年代，行動轉(zhuǎn)移到了歐洲，在那里，西德武裝大學(xué)的教授恩斯特·迪克曼斯(Ernst Dickmanns)用自己設(shè)計的自動駕駛小工具改裝了梅賽德斯-奔馳面包車，與汽車巨頭戴姆勒展開了長達十年的合作。

Finally, it was the Americans’ turn, as Carnegie Mellon University took the lead in the 1990s. As the competition to build self-driving machines spread worldwide, the software improved quickly and computers got ever faster, unlocking new possibilities. By the decade’s end, the first cross-country trips under automated control — in the U.S., Germany, and Japan — were in the record books.

最終，輪到美國人了，卡內(nèi)基梅隆大學(xué)在1990年代率先。 隨著制造自動駕駛機器的競爭遍及全球，軟件Swift改進，計算機變得越來越快，從而開辟了新的可能性。 到本世紀末，在美國，德國和日本的自動控制下的首次越野旅行已記錄在案。

The most intense period of AV development was still to come. In the early 2000s, the Pentagon took a growing interest in this emerging technology. To focus the efforts of scattered research groups and catalyze stronger ties with the defense and auto industries, the Defense Advanced Research Projects Agency — the U.S. military’s most independent research-funding arm — organized a series of open competitions in 2004, 2005, and 2007. These “Grand Challenges,” as they were called, offered millions of dollars in prize money and priceless prestige, and attracted dozens of teams from academia and industry.

視聽技術(shù)發(fā)展最緊張的時期仍將到來。 在2000年代初期，五角大樓對這項新興技術(shù)的興趣日益濃厚。 為了集中分散的研究小組的努力并促進與國防和汽車工業(yè)的更緊密聯(lián)系，美國國防部最高級的研究資助機構(gòu)美國國防高級研究計劃局(Defense Advanced Research Projects Agency)在2004年，2005年和2007年組織了一系列公開比賽。這些被稱為“大挑??戰(zhàn)”的比賽提供了數(shù)百萬美元的獎金和無價的聲望，并吸引了來自學(xué)術(shù)界和工業(yè)界的數(shù)十支團隊。

Putting their best hardware and software to the test, the competitors watched from afar as their AVs tried to traverse both open country and more suburban settings on an abandoned military base. The 2004 race ended without a winner — none of the entrants reached the finish line. But a year later, Stanford University’s winning vehicle claimed the $2 million prize.

測試人員測試了他們最好的硬件和軟件后，遠遠地觀看了他們的AV試圖穿越一個廢棄的軍事基地穿越空曠國家和郊區(qū)的情況。 2004年的比賽在沒有獲勝者的情況下結(jié)束-沒有參賽者到達終點。 但是一年后，斯坦福大學(xué)的獲獎車輛獲得了200萬美元的獎金。

The DARPA contests accelerated the development of driverless vehicles. Stanford’s first-place finish in 2005 was the result of its pioneering use of machine learning, an A.I. programming technique, in processing road imagery. But more important, the contests focused attention on the emerging technology’s possibilities. No one was shocked by the military’s rising interest in AVs. But it was the potential civilian applications that set off a sudden wave of speculation. For the first time, the practical commercial use of self-driving technology seemed within reach.

DARPA競賽加快了無人駕駛汽車的發(fā)展。 斯坦福大學(xué)在2005年獲得第一名的成績是它在處理道路圖像中率先使用了AI學(xué)習(xí)技術(shù)即機器學(xué)習(xí)技術(shù)的結(jié)果。 但更重要的是，比賽將注意力集中在新興技術(shù)的可能性上。 軍方對自動駕駛汽車的興趣日益濃厚，沒有人感到震驚。 但是，潛在的民用應(yīng)用引發(fā)了突然的猜測。 第一次，自動駕駛技術(shù)在商業(yè)上的實際應(yīng)用似乎觸手可及。

It was a wake-up call for the auto industry. But not everyone heard it. Most companies were preoccupied with the financial crisis of 2007–2008 and the global recession that followed. U.S. automakers in particular were hamstrung when it came to capitalizing on the opportunity of AVs, which would require substantial further investment for the journey from lab to market. The automakers were going bankrupt or getting bailed out by the federal government. Instead, Silicon Valley moved forward. By 2009, the head of the winning Stanford University team, Sebastian Thrun, was leading a new self-driving-car project at Google. The search giant had bet big on Android, its highly successful operating system for mobile phones. Cars could become the next big computing platform, it seemed. Could Google stake a claim on the future of automotive software? It appeared to be a smart bet, bolstered by CEO and cofounder Larry Page’s lifelong interest in AVs.

這是汽車行業(yè)的警鐘。 但并非所有人都聽到了。 大多數(shù)公司全神貫注于2007-2008年的金融危機以及隨之而來的全球衰退。 在利用自動駕駛汽車的機會方面，尤其是美國汽車制造商受到了阻礙，這需要大量的進一步投資才能從實驗室到市場。 汽車制造商已經(jīng)破產(chǎn)或被聯(lián)邦政府紓困。 相反，硅谷前進了。 到2009年，斯坦福大學(xué)獲獎團隊的負責(zé)人塞巴斯蒂安·特倫(Sebastian Thrun)領(lǐng)導(dǎo)了Google的新自動駕駛汽車項目。 這家搜索巨頭在Android上押注了很大的錢，它的手機操作系統(tǒng)非常成功。 看起來，汽車可能會成為下一個大型計算平臺。 Google可以對汽車軟件的未來提出主張嗎？ 首席執(zhí)行官兼聯(lián)合創(chuàng)始人拉里·佩奇(Larry Page)對視聽設(shè)備的終生興趣增強了這筆賭注。

A new Google self-driving car is on display at Google X in Mountain View, California on May 13, 2015. Photo: Kim Kulish/Getty Images2015年5月13日，一輛新的Google自動駕駛汽車將在加利福尼亞山景城的Google X上展出。照片：Kim Kulish / Getty Images

Google’s move took a few years to sink in, but once it did, all hell broke loose — not only in the car business, but in the computer and cab industries as well. Suddenly, every major automaker, every ride-hail company, and competing cloudware giants like Apple hastily mobilized efforts to develop self-driving vehicles, too. When in-house projects failed to produce convincing results, many companies simply acquired promising startups to get hold of the needed technology instead. In a two-year period during 2016 and 2017 alone, some $80 billion surged into self-driving vehicle technologies.

Google的舉動花了幾年時間，但一旦成功，一切就徹底崩潰了–不僅在汽車行業(yè)，而且在計算機和駕駛室行業(yè)。 突然，每個主要的汽車制造商，每個叫車服務(wù)的公司，以及像蘋果公司這樣的競爭云軟件巨頭都匆忙動員起來，開發(fā)自動駕駛汽車。 當(dāng)內(nèi)部項目無法產(chǎn)生令人信服的結(jié)果時，許多公司只是簡單地收購了有前途的初創(chuàng)公司來掌握所需的技術(shù)。 僅在2016年和2017年的兩年中，自動駕駛汽車技術(shù)就激增了約800億美元。

The biggest deal, Intel’s panicked 2017 acquisition of computer-vision pioneer Mobileye, an Israel-based maker of computer-vision systems, was valued at an eye-watering $15 billion. As this flurry of mergers and acquisitions unfolded, the web of partnerships and cross holdings linking automakers and the tech sector grew ever more tangled. Two of the world’s biggest consumer industries — computers and cars — had seen their future in each other. But they couldn’t decide whether they wanted to get together or gobble each other up.

最大的一筆交易是英特爾在2017年驚慌失措地收購了計算機視覺先驅(qū)Mobileye，后者是以色列計算機視覺系統(tǒng)制造商，其估值達到了驚人的150億美元。 隨著一連串的并購活動的展開，將汽車制造商與科技行業(yè)聯(lián)系起來的伙伴關(guān)系和交叉持股網(wǎng)絡(luò)變得越來越糾結(jié)。 世界上最大的兩個消費行業(yè)-計算機和汽車-彼此見證了他們的未來。 但是他們無法決定他們是否想聚在一起或互相吞噬。

By 2018 the hard work and high finance had paid off. In December, Google spin-off Waymo quietly unwrapped the world’s first truly self-driving taxi service, in Chandler, Arizona. More than 40 years after the first AV test-drive at Tsukuba, and nearly a decade after recruiting Thrun, the company started taking requests for driverless rides through the Phoenix suburbs. Reports said the tech giant had set aside more than $10 billion to build out its self-driving empire. At last, it seemed, the long and painful birthing of the AV was finally over.

到2018年，辛勤的工作和高昂的財務(wù)狀況得到了回報。 去年12月，谷歌的分拆Waymo在亞利桑那州的錢德勒悄悄地推出了世界上第一個真正的自動駕駛出租車服務(wù)。 在筑波市進行首次AV試駕40多年后，以及招募Thrun的將近十年之后，該公司開始接受在鳳凰城郊區(qū)進行無人駕駛的請求。 報道稱，這家科技巨頭已經(jīng)撥出超過100億美元來建立自己的自動駕駛帝國。 終于，AV的漫長而痛苦的誕生終于結(jié)束了。

“There is hardly a task that horse-drawn vehicles can do which cannot be done as well, and possibly better, with automobiles,” reported the New York Times on January 12, 1903, as one of the world’s first big auto shows opened its doors inside Madison Square Garden, then located at Twenty-Sixth Street and Madison Avenue. The Times was still at it a century later, this time hawking the engineering marvels of the self-driving age with a similar enthusiasm. “On my fourth day in a semi-driverless car,” wrote columnist David Leonhardt in 2018, “I was ready to make a leap into the future.”

1903年1月12日， 《紐約時報 》報道說： “在這里，用馬拉的車輛幾乎不可能完成汽車所能完成的任務(wù)，甚至可能做得更好。”這是世界上最早的大型車展之一它的門位于麥迪遜廣場花園內(nèi)，然后位于第二十六街和麥迪遜大街。 一個世紀后，《 泰晤士報》仍處在這個時代 ，這次以類似的熱情勾銷了自動駕駛時代的工程奇跡。 專欄作家戴維·萊昂哈特(David Leonhardt)在2018年寫道：“在我開著半自動駕駛汽車的第四天，我已經(jīng)準備好邁向未來。”

The paper of record isn’t alone. Much like the automobile, AVs have unleashed bold speculation about the new technology’s benefits to individuals and society. But what does that future promise?

記錄紙并不孤單。 就像汽車一樣，自動駕駛汽車對新技術(shù)對個人和社會的好處進行了大膽的猜測。 但是，未來的前景如何？

First, self-driving technology can eliminate nearly all of the deaths caused by automobiles, say its champions. An estimated 60 million people were killed in motor vehicle crashes in the 20th century. That’s more than all of the military and civilian deaths during World War II. But even as cars have become much safer, the killing continues, as motor vehicles spread to new countries where skilled drivers and traffic regulations are in short supply. As auto use booms in China and India, more than 1.4 million road deaths occur worldwide every single year — stealing enough souls to fill a city the size of Dallas, Texas; Birmingham, England; or Kobe, Japan. The vast majority of these crashes would have been prevented with self-driving technology, advocates claim.

首先，自動駕駛技術(shù)可以消除幾乎所有由汽車造成的死亡。 在20世紀，估計有6000萬人死于汽車撞車事故。 這超過了第二次世界大戰(zhàn)期間所有軍事和平民死亡人數(shù)。 但是，即使汽車變得更加安全，殺人仍在繼續(xù)，因為汽車傳播到了缺乏熟練駕駛員和交通法規(guī)的新國家。 隨著中國和印度汽車使用量的激增，全球每年有140萬以上的道路交通事故死亡-偷走了足夠多的人，以填滿德克薩斯州達拉斯市的整個城市。 英國伯明翰； 或日本神戶。 提倡者聲稱，這些碰撞中的絕大多數(shù)將通過自動駕駛技術(shù)避免。

Second, AV boosters boast, traffic congestion as we know it will disappear. The economic toll of overcrowded roads is enormous, and is easier to measure than ever, thanks to location-tracking devices embedded in ubiquitous mobile phones. Using the vast troves of travel records these phones leave behind, telematics firm Inrix estimated that in the U.S. alone, the cost of drivers’ time wasted in traffic was over $305 billion a year, or nearly $1,500 per driver. The argument for AVs is that software-piloted cars can safely pack more cars closer together at highway speeds, thanks to faster braking reflexes. But AVs might also reduce some bottlenecks by simply spreading human populations farther apart, splaying settlements out over a wider expanse of land. When passengers in AVs can use travel time for work or leisure instead of keeping eyes on the road, the thinking goes, longer rides to less-congested areas won’t be a bother.

其次，視音頻增強器自吹自traffic，因為我們知道交通擁堵將消失。 由于嵌入在無處不在的移動電話中的位置跟蹤設(shè)備，擁擠的道路造成的經(jīng)濟損失是巨大的，而且比以往任何時候都更容易衡量。 使用這些手機留下的大量旅行記錄，遠程信息處理公司Inrix估計，僅在美國，駕駛員浪費在交通上的時間的成本每年就超過3050億美元，或每位駕駛員近1500美元。 對于自動駕駛汽車的觀點是，由于更快的制動React，軟件駕駛的汽車可以安全地將更多的汽車以高速公路速度更近地打包在一起。 但是，AV可能還會通過簡單地將人口分散到更遠的地方，在更廣闊的土地上擴大定居點來減少某些瓶頸。 當(dāng)自動駕駛汽車的乘客可以將旅行時間用于工作或休閑而不是盯著道路行駛時，人們就會想到，長時間乘車去較不擁擠的區(qū)域?qū)⒉粫斐陕闊?

Third, no one will be left behind by AVs, advocates hope. Cars expanded mobility for hundreds of millions of people in the 20th century, but when the automobile’s success dispersed the population and siphoned funds from mass transit, many found themselves facing new barriers to freely getting around. In the U.S. alone, more than 25 million people have disabilities that limit travel — nearly one-sixth of the workforce. Not only will AVs bring automobile travel to those physically unable to drive, it is believed, they will open up new travel options for the very old, the very young, and those who can’t afford cars of their own. As disabled people come off the sidelines and enter the workforce, as senior citizens get easier access to medical care, and as children enjoy access to a wider range of educational and enrichment opportunities, the social and economic benefits could be enormous.

第三，倡導(dǎo)者希望，AV不會留下任何人。 汽車在20世紀為成千上萬人提供了出行便利，但是當(dāng)汽車的成功驅(qū)散了人口并從公共交通中抽走了資金時，許多人發(fā)現(xiàn)自己面臨著自由出行的新障礙。 僅在美國，就有超過2500萬的殘疾人限制出行，幾乎占勞動力的六分之一。 人們相信，自動駕駛汽車不僅會給身體無法駕駛的人帶來汽車旅行，而且還將為年紀大，年幼的人和無力負擔(dān)自己的汽車的人開辟新的旅行選擇。 隨著殘疾人離開場外進入勞動力市場，隨著老年人更容易獲得醫(yī)療服務(wù)，以及隨著兒童獲得更多的教育和致富機會，社會和經(jīng)濟利益將是巨大的。

When will this utopia arrive, you ask? Today AVs are still a novelty. Despite all the hassles, dangers, and drudgery of driving, we remain the most cost-effective “technology” suited to the task. By the time you read this, in the early 2020s, even if the wildest predictions come to pass, there will still be fewer than one million truly self-driving vehicles plying the world’s highways, streets, and sidewalks. But AVs’ numbers are destined to grow quickly as the decade rolls on. By 2030 the global headcount of smart cars, trucks, and buses could creep into the tens of millions. They’ll share the road with some two billion human-driven cars and trucks (give or take a few hundred million). Even then, it seems, AVs will be but a rounding error in the global population of automobiles. But the revolution will strike with surprise, surgical precision, and overwhelming force. As cyberpunk novelist William Gibson once famously said, “The future is already here — it’s just not very evenly distributed.”

您會問這個烏托邦何時到達？ 如今，AV仍然是新事物。 盡管有種種麻煩，危險和駕駛煩惱，但我們?nèi)匀皇亲钸m合該任務(wù)的具有成本效益的“技術(shù)”。 到您讀這篇文章時，在2020年代初，即使做出最瘋狂的預(yù)測，在全球的高速公路，街道和人行道上行駛的真正無人駕駛汽車仍將少于一百萬。 但是隨著十年的到來，自動駕駛汽車的數(shù)量注定會Swift增長。 到2030年，智能汽車，卡車和公共汽車的全球人數(shù)可能攀升至數(shù)千萬。 他們將與大約20億輛人力驅(qū)動的汽車和卡車共享道路(付出或花費幾億美元)。 看來，即使到那時，AV仍將是全球汽車總數(shù)中的四舍五入錯誤。 但是革命將以驚人的速度，精確的手術(shù)和壓倒性的力量進行打擊。 正如賽博朋克小說家威廉·吉布森(William Gibson)曾說過的那樣：“未來已經(jīng)來臨-分布不均勻。”

Pilot models of the Uber self-driving car are displayed at the Uber Advanced Technologies Center on September 13, 2016 in Pittsburgh, Pennsylvania. Photo: AFP/Stringer/Getty Images2016年9月13日在賓夕法尼亞州匹茲堡的Uber先進技術(shù)中心展示了Uber自動駕駛汽車的飛行員模型。 照片：法新社/斯特林格/蓋蒂圖片社

The first changes we notice will occur in taxis. Most market analysts agree that all taxis in the industrialized nations will be automated by 2030. In the U.S., that’s 300,000 vehicles. Add in all the Ubers and Lyfts and the total is closer to 1,000,000 in all. Swarming from our airports and resorts through our most beloved downtowns, driverless cabs could become the face of automation for a generation, and the gateway drug to driverless mobility for billions of passengers every year. The arrival of driverless cabs could radically change consumers’ perception of cars. When computerized chauffeurs are a tap and a swipe away, and robotaxi rides are dirt cheap, people may opt out of auto ownership altogether. If we make the shift en masse, far fewer vehicles will be needed to move the same number of people that private cars do today.

我們注意到的第一個變化將發(fā)生在出租車上。 大多數(shù)市場分析家都同意，到2030年，工業(yè)化國家的所有出租車都將實現(xiàn)自動化。在美國，這是30萬輛汽車。 將所有Uber和Lyfts加起來，總數(shù)總計接近1,000,000。 無人駕駛室從我們的機場和度假勝地到我們最受人歡迎的市中心涌現(xiàn)，無人駕駛出租車可能會成為一代人自動化的代名詞，每年都有數(shù)十億乘客通向無人駕駛的門戶藥物。 無人駕駛出租車的到來可能從根本上改變消費者對汽車的看法。 當(dāng)輕便的輕便司機和輕便的機器人司機一去不復(fù)返時，人們可能會完全放棄使用汽車所有權(quán)。 如果我們進行大規(guī)模轉(zhuǎn)移，那么與如今的私家車一樣，移動相同數(shù)量的人所需的車輛將更少。

But this silver lining may not come to be. Automation will also make private automobiles more useful, and software will radically reduce the hassles of ownership. Think about it for a moment. Automated cars will do more than drive for you — they’ll also park themselves, take themselves to the garage for fuel and repairs, and pay their own insurance bills (with your money, of course). It’s entirely likely that we’ll simply swap our stupid cars for smart ones, and go on cruising around as we have.

但這種一線希望可能不會成為現(xiàn)實。 自動化也將使私家車更加有用，而軟件將從根本上減少所有權(quán)的麻煩。 考慮一下。 自動駕駛汽車為您提供的不僅僅是開車服務(wù)，它們還將自己停車，帶自己去車庫加油和維修，并支付自己的保險費(當(dāng)然是用您的錢)。 我們完全有可能只是將愚蠢的汽車換成智能汽車，然后繼續(xù)四處行駛。

In the long run we’ll likely see a mix of both worlds. By 2040, even if shared AVs take over and new-car sales fall by 50 percent — a sea change, indeed — automakers will still be churning out some 30 million self-driving cars worldwide every year. Half will end up in China, another quarter in America, and the rest scattered across the EU, Japan, and emerging markets. Yet even as the business of making cars shrinks, the business of using cars — and vans, and scooters, and everything else that goes — will grow. What’s left of today’s $2 trillion global auto manufacturing industry will be subsumed into a much larger market for “personal transportation services” that’s projected to reach $7 to $10 trillion a year by mid-century, roughly the size of the entire EU economy today. Waymo alone wants to capture a $1.7 trillion annual share by 2030. But Uber, Amazon, and Alibaba — not to mention Ford, GM, and VW, among others — aren’t ceding this new frontier without a fight. They have their own designs on the service businesses of the self-driving future, too.

從長遠來看，我們可能會看到兩個世界的混合。 到2040年，即使共享的自動駕駛汽車接手，新車銷量下降50％(的確是天翻地覆的變化)，汽車制造商每年仍將在全球范圍內(nèi)生產(chǎn)約3000萬輛自動駕駛汽車。 一半將在中國結(jié)束，另一半在美國結(jié)束，其余將分散在歐盟，日本和新興市場。 然而，即使隨著汽車制造業(yè)務(wù)的萎縮，使用汽車(面包車，踏板車以及其他所有東西)的業(yè)務(wù)也會增長。 當(dāng)今全球2萬億美元的汽車制造業(yè)中，剩下的將被歸入“個人運輸服務(wù)”更大的市場，到本世紀中葉，這一市場預(yù)計每年將達到7至10萬億美元，大致相當(dāng)于當(dāng)今整個歐盟經(jīng)濟的規(guī)模。 僅Waymo一家就希望在2030年之前奪取每年1.7萬億美元的份額。但是，Uber，亞馬遜和阿里巴巴(更不用說福特，通用汽車和大眾汽車等公司)也不會在不戰(zhàn)而退的新領(lǐng)域。 他們在自動駕駛未來的服務(wù)業(yè)務(wù)上也有自己的設(shè)計。

So while the driverless revolution starts with a trickle, before long that slow drip will become a torrent. By 2050 or thereabouts, most human-driven cars will be gone. A smaller, smarter fleet of self-driving vehicles of many shapes and sizes will have replaced them. Some will be private, some will be shared. Some will move a single person, some will haul a hundred or more. Many won’t carry anyone at all, and instead will busy themselves with shuttling around an unceasing flood of goods unleashed by the triumph of online shopping. Some will help us by simply watching over our urban world or directing traffic. All told, our diverse fleet of AVs will log vastly more miles than our cars do today.

因此，盡管無人駕駛的革命始于a細流，但不久之后，緩慢的滴灌將成為洪流。 到2050年左右，大多數(shù)人類駕駛的汽車都將消失。 規(guī)模更小，更智能的多種形狀和尺寸的自動駕駛汽車將取代它們。 一些將是私有的，一些將被共享。 有些會移動一個人，有些會拖一百或更多。 許多人根本不會帶任何人，而是忙于穿梭于在線購物的勝利所釋放出的不斷涌入的大量商品中。 有些人將僅通過監(jiān)視我們的城市世界或指揮交通來為我們提供幫助。 總而言之，我們多樣化的AV車隊行駛的里程數(shù)比今天的汽車要遠得多。

It’s tempting to see the driverless revolution as a repeat of our 20th-century experience with cars, only on a larger, computer-choreographed scale. But nothing in our past can prepare us for what lies ahead. At full tilt, the pace of change will bewilder us. In the U.S., full motorization took about 60 years — from roughly 1920, when cars started arriving in cities in large numbers, to 1980, when metro areas everywhere started to choke on their vast numbers. The next 40 years, from 1980 to 2020, was a period of saturation.

誘人的是，無人駕駛革命是我們20世紀汽車體驗的重演，只是在更大的計算機編排規(guī)模上。 但是，過去的一切都無法使我們?yōu)榧磳⒌絹淼氖虑樽龊脺蕚洹?全面傾斜，變化的步伐將使我們感到困惑。 在美國，完全的機動化花費了大約60年的時間-從大約1920年開始，當(dāng)時汽車開始大量進入城市，到1980年，當(dāng)時世界各地的都會區(qū)開始大量擁擠。 從1980年到2020年，接下來的40年是一個飽和期。

The average number of hours spent in traffic by commuters nearly tripled, and the economic cost of traffic congestion grew tenfold, to $166 billion annually. We have spent much of this time seeking ways to curb auto use and invest in alternatives.

通勤者平均在交通上花費的時間增加了三倍，交通擁堵的經(jīng)濟成本增長了十倍，達到每年1,660億美元。 我們花了很多時間來尋找抑制汽車使用和投資替代品的方法。

But automation could play out in as little as 20 to 30 years — the span of a single generation. If our history with the automobile does teach us anything — it is that the future we find in the driverless revolution won’t be the one we expected.

但是自動化可以在短短20到30年內(nèi)發(fā)揮作用-一代人的時間跨度。 如果我們的汽車歷史確實能教給我們?nèi)魏螙|西，那就是我們在無人駕駛革命中發(fā)現(xiàn)的未來不會是我們所期望的。

From Ghost Road: Beyond the Driverless Car published by W. W. Norton & Company. ? 2020 by Anthony M. Townsend由《 幽靈路：超越無人駕駛汽車 》由WW Norton＆Company發(fā)布。 ?2020年，安東尼·湯森(Anthony M. Townsend)

翻譯自: https://onezero.medium.com/the-100-year-history-of-self-driving-vehicles-10b8546a3318

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