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NuTonomy公司的自动驾驶出租车(图)

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客

  供图:埃德蒙德·哈罗

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客

2016年传统出租车的价位是每公里0.93美元;到2030年自动驾驶出租车的价位将是每公里0.31美元。资料来源:摩根士丹利 

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客

 不要付小费:nuTonomy公司的测试车遍布传感器,总是礼貌行车,而且从原则上来讲,费用更低。供图:埃文·阿克曼

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客

 应急按钮:nuTonomy公司的汽车配有三个并排按钮——“手动”、“暂停”和“自动”,并且在不远处,还有一个鲜红色的“紧急停车”按钮。供图:埃文·阿克曼

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客
像欧洲里斯本这样的中型城市,通过自动驾驶车辆的拼车策略能够把街道清空:自动驾驶出租车外加地铁系统会将90%的汽车淘汰,会将100%的街道停车位空出来。资料来源:经合组织国际运输论坛

 After Mastering Singapore’s Streets, NuTonomy’s Robo-taxis Are Poised to Take on New Cities

NuTonomy公司的自动驾驶出租车

An AI alternative to deep learning makes it easier to debug the startup’s self-driving cars
替代深度学习的人工智能可以更加轻松地测试这家新兴公司的自动驾驶车辆。
胡德良   译

Take a short walk through Singapore’s city center and you’ll cross ahelical bridge modeled on the structure of DNA, pass a science museum shaped like a lotus flower, and end up in a towering grove of artificial Supertrees that pulse with light and sound. It’s no surprise, then, that this is the first city to host a fleet of autonomous taxis. 

 在新加坡市中心散步,走出不远,就会跨越一座模仿了DNA结构的螺旋形桥梁,穿过一个形状像莲花的科学博物馆,最终来到一片高耸的人造超级树林中,其中的树木有节律地闪烁光芒并发出声音。这是不足为奇的,新加坡市是第一个拥有自动驾驶出租车车队的城市。

 Since last April, robo-taxis have been exploring the 6 kilometers of roads that make up Singapore’s One-North technology business district, and people here have become used to hailing them through a ride-sharing app. Maybe that’s why I’m the only person who seems curious when one of the vehicles—a slightly modified Renault Zoe electric car—pulls up outside of a Starbucks. Seated inside the car are an engineer, a safety driver, and Doug Parker, chief operating officer of nuTonomy, the MIT spinout that’s behind the project.

 自从去年4月,机器人出租车就开始在这段六公里的道路上探索起来,这段公路两旁就是新加坡纬壹科技城商业区,这里的人们已经习惯于通过一款拼车应用软件来打出租车了。因此,当一辆出租车——一款稍加改装的雷诺Zoe电动车停在一家星巴克连锁店外面的时候,似乎唯有我对其感兴趣。车上坐着一位工程师、一位安全驾驶员和nuTonomy公司的首席运营官道格·帕克nuTonomy公司是从麻省理工学院分离出来的一家公司,负责该项目的开发。

 The car comes equipped with the standard sensor suite for cars with pretensions to urban autonomy: lidars on the roof and around the front bumper, and radar and cameras just about everywhere else. Inside, the car looks normal, with the exception of three large buttons on the dashboard labeled Manual, Pause, and Autonomous, as well as a red emergency stop button. With an okay from the engineer, the safety driver pushes the Autonomous button, and the car sets off toward the R&D complex known as Fusionopolis.

 这辆汽车配备了标准的传感器套件,适合于具有城市自治权的市区汽车:车顶上以及前保险杠周围装有激光雷达,雷达和摄像头几乎遍布汽车的各个部位。这款车的内部看起来一切正常,只是在仪表板上拥有三个大大的按钮,分别标着“手动”、“暂停”和“自动”,此外还有一个红色的紧急停车按钮。工程师发出了一声“开车”的指令,安全驾驶员按动了“自动”按钮,这辆车就朝着被称为“启汇园”的研发中心驶去。

 By the end of this year, nuTonomy expects to expand its fleet in Singapore from six cars to dozens, as well as adding a handful of test cars on public roads in the Boston area, near its Cambridge headquarters, and one or two other places.

 nuTonomy公司预计,到今年年底把新加坡的车队从6辆车扩大到数十辆,并在波士顿地区的公共道路、公司在剑桥的总部附近以及一两个其他地方增加一些测试车辆。

 Robo-taxis Come Cheap

 车费便宜

 We think Singapore is the best place to test autonomous vehicles in the world,” Parker tells me as the car deftly avoids hitting a double-parked taxi.

 该出租车灵巧地绕过了一辆并排停放的出租车,这时帕克告诉我说:“我们认为,新加坡是世界上自动驾驶车辆的最佳测试地。”

 One-North offers a challenging but not impossible level of complexity, with lots of pedestrians, a steady but rarely crushing flow of vehicle traffic, and enough variability to give the autonomous cars what they need to learn and improve.

 纬壹科技城提供了一定的挑战性,但是其复杂性并未到达不可能攻破的地步:行人很多,但车流量稳定,很少出现拥挤的情况,而且也有足够的变化,能够满足自动驾驶汽车学习与提高的需求。

 Riding in an autonomous car makes you acutely aware of just how many potentially dangerous behaviors we ignore when we’re behind the wheel. Human drivers know from experience what not to worry about, but nuTonomy’s car doesn’t yet, so it reacts to almost everything, with frequent (and occasionally aggressive) attempts at safety. If the car has even a vague suspicion that a pedestrian might suddenly decide to cross the road in front of it, it will slow to a crawl.

 乘坐自动驾驶汽车能够使你强烈地意识到,我们在驾驶车辆时忽略掉了多少潜在的危险行为。人类驾驶者从经验中可以获知不用担心什么样的情况,但是nuTonomy公司的汽车还不能做到这一点,因此它对几乎所有的情况都会做出反应,会频繁地(有时会积极地)做出安全尝试。如果该车稍稍怀疑某个行人可能会突然在其前面横穿马路,它就会缓慢前行。

 This mistrust of pedestrians as well as other drivers was designed into the software. “Humans are by far our biggest challenge,” Parker says.

 对行人以及对其他司机的这种怀疑都设计在软件之中。帕克说:“人类是我们最大的挑战。”

 Over the course of 15 minutes, our car has to deal with people walking in the gutter, cars drifting across the centerline, workers repairing the road, taxis cutting across lanes, and buses releasing a swarm of small children. Even a human driver would have to concentrate, and it’s unsurprising that the safety driver sometimes has to take over and reassure the car that it’s safe to move.

 在这15分钟的行程中,我们的汽车不得不应对沿着路边排水沟行走的人们、超越中线行驶的车辆、维修道路的工人、抄近路横穿车道的出租车、有一大群小孩正在下车的公交车……甚至人类驾驶员都不得不集中精力应对,难怪安全驾驶员有时必须要接过驾驶的任务,确保车辆安全前行。

 To handle these complex situations, nuTonomy uses formal logic, which is based on a hierarchy of rules similar to Asimov’s famous Three Laws of Robotics. Priority is given to rules like “don’t hit pedestrians,” followed by “don’t hit other vehicles,” and “don’t hit objects.” Less weight is assigned to rules like “maintain speed when safe” and “don’t cross the centerline,” and less still to rules like “give a comfortable ride.”

 为了处理这些复杂的情况,nuTonomy公司利用了形式逻辑,这种逻辑运用一种规则等级,类似于阿西莫夫著名的“机器人三定律”。优先等级安排给像“不要撞到行人”等规则,接着是“不要撞到其他车辆”和“不要撞到物体”等规则。较为次要的规则有“安全时保持行驶速度”和“不要超越中线”等,更加次要的规则有“提供乘车舒适性”等。

 The car tries to follow all of the rules all the time, but it breaks the less important ones first: If there’s a car idling at the side of the road and partially blocking the lane, nuTonomy’s car can break the centerline rule in order to maintain its speed, swerving around the stopped car just as any driver would. The car uses a planning algorithm called RRT*—pronounced “r-r-t-star”—to evaluate many potential paths based on data from the cameras and other sensors. (The algorithm is a variant of RRT, or rapidly exploring random tree.) A single piece of decision-making software evaluates each of those paths and selects the path that best conforms to the rule hierarchy.

 该车一直企图遵循所有的规则,但是它会首先打破不太重要的规则:如果有一辆车怠速停在路边,挡住了部分车道,那么nuTonomy公司的汽车就会跟任何人类司机一样,打破中线规则,保持车速,绕过停止的车辆。该汽车利用了一种计划运算程序,这种程序被称为“RRT*”, 是“快速随机搜索树(RRT)”的一种变体,通过摄像头和其他传感器获取的数据来评估许多潜在的路径。“RRT*”由单一的决策软件来评估每条路径,选择那条最符合规则等级的路径。

 By contrast, most other autonomous car companies rely on some flavor ofmachine learning. The idea is that if you show a machine-learning algorithm enough driving scenarios—using either real or simulated data—it will be able to figure out the underlying rules of good driving, then apply those rules to scenarios that it hasn’t seen before. This approach has been generally successful for many self-driving cars, and in fact nuTonomy is using machine learning to help with the much different problem of interpreting sensor data—just not with decision making. That’s because it’s very hard to figure out why machine-learning systems make the choices they do.

 相对来说,多数其他自动驾驶汽车公司依靠具有某种特点的机器学习。这种理念就是,如果你为汽车的机器学习运算程序展示足够的驾驶场景,不管是利用真实数据还是模拟数据,它都能够找出潜在的良好驾驶规则,然后将这种规则运用到以前未曾见过的驾驶场景中。对于许多自动驾驶汽车来说,这个方法通常是成功的。事实上,nuTonomy公司正在利用机器学习来帮助处理十分困难的传感器数据解析问题,不仅仅用来处理决策问题。原因是,要想弄清机器学习系统为何会做出自己的选择,毕竟是非常困难的。

 “Machine learning is like a black box,” Parker says. “You’re never quite sure what’s going on.”

 “机器学习就像一个黑盒子。”帕克说,“你永远都不能确定其中到底发生了什么。”

 Formal logic, on the other hand, gives you provable guarantees that the car will obey the rules required to stay safe even in situations that it’s otherwise completely unprepared for, using code that a human can read and understand. “It’s a rigorous algorithmic process that’s translating specifications on how the car should behave into verifiable software,” explains nuTonomy CEO and cofounder Karl Iganemma. “That’s something that’s really been lacking in the industry.”

 另一方面,形式逻辑可以为你提供可靠的保证,使汽车遵守规则,按照要求保持安全,即使在完全没有准备的其他情况下也是如此,同时可以利用人们能够读得懂的代码来显示各种情况。nuTonomy公司执行总裁兼联合创始人卡尔·伊格奈玛解释说:“这是一个严格的运算过程,把有关汽车应该如何运行的规范转化为可以验证的软件……这是该行业真正缺少的方面。”

 Gill Pratt, CEO of the Toyota Research Institute, agrees that “the promise of formal methods is provable correctness,” while cautioning that it’s “more challenging to apply formal methods to a heterogeneous environment of human-driven and autonomous cars.”

 丰田研究所执行总裁吉尔·普拉特同意上述观点,他表示:“形式化方法的承诺就是可以证实的正确性。”同时,他还警告说:“将形式化方法运用在人类驾驶和自动驾驶的混杂车辆环境中,这是更具挑战性的。”

 nuTonomy is quickly gaining experience in these environments, but it recognizes that these things take time. “We’re strong believers that this is going to make roads much, much safer, but there are still going to be accidents,” says Parker. Indeed, one of nuTonomy’s test vehicles got into a minor accident in October. “What you want is to be able to go back and say, ‘Did our car do the right thing in that situation, and if it didn’t, why didn’t it make the right decision?’ With formal logic, it’s very easy.”

 在这样的环境中,nuTonomy公司正在快速获得经验,但是该公司认识到处理这些方面的事情需要时间。帕克说:“我们坚信,这将会使行车安全得多,但是仍然会出事故。”的确,10月份,nuTonomy公司的一辆测试车发生了一个小事故。帕克说:“你想做的是,退一步询问‘我们的车在那种情况下能够做出正确选择吗?如果不能,为什么它就不能做出正确的抉择呢?’利用形式逻辑,这是很简单的事情。”

 The ability to explain what’s happened will help significantly with regulators. So will the ability to show them just what fix you’ve made so that the same problem doesn’t happen again. Effective regulation is critical to the success of autonomous cars, and it’s a challenging obstacle in many of the larger auto markets. In the United States, for example, federal, state, and local governments have created a hodgepodge of regulations related to traffic, vehicles, and driving. And in many areas, technology is moving too fast for government to keep up.

 能够解释发生了什么,会为监管机构提供大力帮助;能够向监管机构展示你做过什么样的修复,也会对这些机构提供大力支持,以便不会再次发生同样的问题。有效监管对于自动驾驶车辆的成功运行是很关键的,在许多大型汽车市场中有效监管成为一个具有挑战性的障碍。例如:在美国,联邦政府、州政府和地方政府针对交通、车辆和驾驶出台的规章制度五花八门。在很多领域,技术发展太快,政府的规章制度难以跟上。

 A handful of other companies are testing autonomous taxis and delivery vehicles on public roads, including Uber in Pittsburgh. The motive is obvious: When robotic systems render human drivers redundant, it will eliminate labor costs, which in most places far exceed what fleet operators will pay for their autonomous vehicles. The economic potential of autonomous vehicles may be clear. But what’s less clear is whether regulators will approve commercial operations anytime soon.

 几家其他公司也正在公共道路上测试自动驾驶出租车和自动驾驶货运车,其中包括匹兹堡的优步公司。这些公司的动机很明显:当机器人系统使人类司机变得多余时,就会消除劳动力成本;在许多地方,劳动力成本远远超过了车队运营商将要为自动驾驶车辆支付的费用。或许,自动驾驶车辆的经济潜力是显而易见的。但是,监管机构是否会在短期内批准自动驾驶车辆的商业运营,这一点尚不明朗。

 In Singapore, the city-state’s government is both more unified and more aggressive in its pursuit of a self-driving future. “We’re starting with a different philosophy,” explains Lee Chuan Teck, deputy secretary of Singapore’s Ministry of Transport. “We think that our regulations will have to be ready when the technology is ready.” Historically, Singapore has looked to the United States and Europe for guidance on regulations like these, but now it’s on its own. “When it came to autonomous vehicles, we found that no one was ready with the regulations, and no one really knows how to test and certify them,” says Tan Kong Hwee, the director for transport engineering of the Singapore Economic Development Board.

 在新加坡,政府更加统一、更加积极地追求未来的自动驾驶技术。新加坡交通部副部长李川德解释说:“我们开始于不同的理念,我们认为一旦技术成熟,我们的规章制度就必须要准备就绪。”从历史上来讲,像这样的规章制度,新加坡都是向美国和欧洲寻求指导;但是,现在新加坡靠自己了。新加坡经济开发委员会运输工程总监谭康惠(Tan Kong Hwee)说:“提到自动驾驶车辆,我们发现没有哪个国家拥有准备就绪的规章制度,也没有人真正知道该如何测试和认证这些制度。”

 Singapore’s solution is to collaborate with local universities and research institutions, as well as the companies themselves, to move regulations forward in tandem with the technology. Parker says that these unusually close ties between government, academia, and industry are another reason nuTonomy is testing here.

 新加坡的解决方案是:除了跟公司本身合作之外,还跟当地大学和研究机构合作,与技术同步,推进法规建设。帕克称:政府、学术界和产业界之间建立了非常密切的联系,这是nuTonomy公司正在测试车辆的另外一个原因。

 Clearing Lisbon

 清空街道

 Singapore has good reason to be proactive: Its 5.6 million people are packed into just over 700 square kilometers, resulting in the third most densely populated country in the world. Roads take up 12 percent of the land, nearly as much as is dedicated to housing, and as the population increases, building more roads is not an option. The government has decided to make better use of the infrastructure it has by shifting from private cars (now used for nearly 40 percent of trips) to public transit and car shares. Rather than spending 95 percent of their time parked, as the average car does today, autonomous cars could operate almost continuously, reducing the number of cars on Singapore’s roads by two-thirds. And that’s with each car just taking one person at a time: Shared trips could accommodate a lot more people.

 新加坡积极主动是有充分理由的:该国拥有560万人,生活在700平方公里多一点的土地上,使其在人口密度方面成为世界上第三大国。道路占去了该国土地的12%,用于住房的土地跟道路几乎一样多。随着人口的增加,建设更多的道路不是首选的好办法。政府决定要更加有效地利用目前拥有的基础设施,从私人汽车转变到公共交通和汽车共享上来。现在私人汽车用于将近40%的行程,当今的普通车辆有95%的时间都处于停放状态。为了取代这一状况,自动驾驶车辆几乎可以连续运行,可以将新加坡道路上的汽车减少三分之二。通常,一辆车一次只是承载一个人;相比之下,同路共乘策略可以容纳更多的乘客。

 Over the next three to five years, Singapore plans to run a range of trials of autonomous cars, autonomous buses, autonomous freight trucks, and even autonomous utility vehicles. The goal will be to understand how residents use autonomous vehicle technology in their daily lives. Beyond that, Lee says, Singapore is “about to embark on a real town that we’re developing in about 10 to 15 years’ time, and we’re working with the developers from scratch on how we can incorporate autonomous vehicle technology into their plans.” Building new communities from scratch, such as One-North, is a Singaporean specialty.

 在接下来的三至五年中,新加坡计划对自动驾驶汽车、自动驾驶公交车、自动驾驶货运车、甚至对自动驾驶多功能车进行一系列的试验。这么做的目的是,要了解居民在日常生活中如何使用自动驾驶技术。除此之外,李川德说:“新加坡即将开始建设一个真正的商业中心,我们准备在大约1015年的时间内开发出来,我们正在从头开始跟开发商合作,要把自动驾驶车辆技术融入开发计划中。”从头开始建立像纬壹科技城这样的新社区,是新加坡的特色。

 In this new town, most roads will be replaced with paths just big enough for small autonomous shuttles. For longer trips, on-demand autonomous cars and buses will travel mostly underground, waiting in depots outside the city center until they’re summoned. It’s a spacious, quiet vision, full of plazas, playgrounds, and parks—and practically no parking spaces.

 在这个新商业中心,绝大多数道路将被小路替代,这些小路刚好能够容得下往返穿梭的小型自动驾驶汽车。对于较长的旅程,根据需要安排的自动驾驶汽车和公交车主要在地下运行,在市中心外部的公共汽车站等候,一召唤即开。这是一番宽敞而宁静的景象,遍布广场、游乐场和公园,几乎没有停车位。

 To begin to meet this challenge, nuTonomy has partnered with Grab, an Asian ride-sharing company, making autonomous taxi services available to a small group of commuters (chosen from thousands of applicants) around One-North. Testing the taxis in a real application like this is important, but equally important is understanding how users interact with the cars once they stop being a novelty and start being a useful way to get around. “People very quickly start to trust the car,” says Parker. “It’s amazing how quickly it becomes normal.”

 为了迎接这一挑战,nuTonomy公司已经开始跟亚洲拼车企业 Grab公司合作,使从纬壹科技城周围数千名申请者中挑选出来的小群体乘客都能够享受到自动驾驶出租车的服务。像这样在实际运用中测试出租车是很重要的,但同样重要的是:要搞清楚,一旦自动驾驶出租车不再新奇,开始成为一种有用的出行方式,用户跟汽车之间该如何进行信息互换。帕克说:“人们很快开始信任这种车了,该事件成为常态的速度之快,令人惊奇。”

 If all goes well, Parker adds, the company should be ready to offer commercial service through Grab—to all customers, not just preapproved ones—around the One-North area in 2018. At first, each taxi will have a safety driver, but nuTonomy is working on a way to allow a human to remotely supervise the otherwise autonomous car when necessary. Eventually, nuTonomy will transition to full autonomy with the option for teleoperation.

 帕克补充说道:如果一切顺利,到2018年,nuTonomy公司应该能够准备就绪,通过Grab公司向纬壹科技城周围区域的所有乘客提供商业服务,不仅仅局限于获得预先审批的乘客。首先,每辆出租车都将配备一名安全驾驶员,但是nuTonomy公司正在研究一种方法,必要的时候允许由一个人远程监督没有配备安全驾驶员的自动驾驶出租车。最终,nuTonomy公司将过渡到完全自动驾驶,同时可以选择远程操作。

 “The whole structure of cities is going to change,” Parker predicts. “I think it’s going to be the biggest thing since the beginning of the automobile age.”

 帕克根据预测说:“城市的整体结构将会发生改变,我认为这将是汽车时代开始以来最为重大的事件。”

   

译自:http://spectrum.ieee.org/29 Dec 2016 | 13:30 GMT

原著:EVAN ACKERMAN(埃文·阿克曼)

 

NuTonomy公司的自动驾驶出租车(图) - 月亮飞船 - 欢迎光临月亮飞船的博客

EVAN ACKERMAN(埃文·阿克曼)  

作者简介:

 Evan Ackerman is the senior writer for IEEE Spectrum’s award-winning robotics blog, Automaton. Since 2007, he has written over 6,000 articles on robotics and emerging technology, covering conferences and events on every single continent except Africa, Antarctica, Australia, and South America (although he remains optimistic). In addition to Spectrum, Evan’s work has appeared in a variety of other online publications including Gizmodo and Slate, and you may have heard him on NPR’s Science Friday or the BBC World Service if you were listening at just the right time. Evan has an undergraduate degree in Martian geology, which he almost never gets to use, and still wants to be an astronaut when he grows up. In his spare time, he enjoys scuba diving, rehabilitating injured raptors, and playing bagpipes excellently.

 EVAN ACKERMAN(埃文·阿克曼)是IEEE Spectrum杂志旗下获奖机器人博客Automaton的资深写手。自从2007年以来,他撰写了6,000多篇关于机器人和新兴技术的文章,涵盖的会议和事件涉及除非洲、南极洲、澳大利亚和南美洲之外的每个大陆,然而他对尚未涉及的这几个大陆一直抱有乐观的态度。除了为IEEE Spectrum杂志撰写文章,埃文的作品还发表在各种其他在线出版物上,包括科技博客Gizmodo和杂志Slate。如果你曾经在合适的时间收听,你可能在国内公用无线电台(NPR)“科学星期五”频道或英国广播公司(BBC)“国际广播频道”听到过埃文的声音。埃文拥有一个火星地质学的本科学历,但是他几乎从未用到过这个专业,然而日后他仍想当一名航天员。在业余时间,埃文喜欢水肺潜水,喜欢使受伤的猛禽恢复健康,而且他的风笛吹奏得很棒。

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