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(感谢公路新势力的视频翻译,强烈推荐大家阅读经济学人首个无人驾驶特别报告: 你能获得自由, 但要付出代价---机器之能公众号)
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Who is behind the wheel?
谁在掌舵?
本文英文部分选自经济学人Leaders版块
Transit deserts
交通沙漠(公共交通服务不足的地区)
Self-driving cars offer huge benefits—but have a dark side
无人驾驶汽车带来了巨大的好处- 但也存在负面影响
Policymakers must apply the lessons of the horseless carriage to the driverless car
决策者必须将传统汽车的经验应用于无人驾驶汽车
A NEW kind of vehicle is taking to the roads, and people are not sure what to make of it. Is it safe? How will it get along with other road users? Will it really shake up the way we travel? These questions are being asked today about autonomous vehicles (AVs). Exactly the same questions were posed when the first motor cars rumbled onto the roads. By granting drivers unprecedented freedom, automobiles changed the world. They also led to unforeseen harm, from strip malls and urban sprawl to road rage and climate change. Now AVs are poised to rewrite the rules of transport—and there is a danger that the same mistake will be made all over again.
一种新型车辆正在上路,人们却不清楚该怎么面对。 它安全吗? 它是如何与其他道路使用者相处的? 它真的会改变我们出行方式吗? 今天被问到的这些问题都是关于自动驾驶汽车的。当第一辆汽车轰鸣着上路时,人们也有同样的疑问。通过给司机前所未有的自由,汽车改变了世界。 同时也导致了无法预料的危害,如购物中心、城市扩张、路怒症、气候变化。现在自动驾驶汽车正准备重写交通规则,而且同样的错误将会再次发生。
AVs are on the threshold of being able to drive, without human supervision, within limited and carefully mapped areas (see special report). Waymo, the self-driving-car unit of Google’s parent company, hopes to launch an autonomous “robotaxi” service in the suburbs of Phoenix, Arizona later this year. General Motors, America’s biggest carmaker, plans its own robotaxi service for 2019. On February 26th California said it would abolish the rule that experimental AVs must always have a safety driver on board ready to assume control.
在人们精心绘制的有限区域内(见特别报道),自动驾驶汽车能在无人监督下行驶。作为谷歌母公司的无人驾驶汽车部门,Waymo希望今年晚些时候,在亚利桑那州的凤凰城郊区推出一项自动“机器人出租车”服务。 通用汽车公司是美国最大的汽车制造商,计划于2019年开始自己的“机器人出租车”服务。2月26日,加利福尼亚州表示,将取消需在试验的自动驾驶汽车里配备安全驾驶员的规定。
Clean, dream machines
清洁,理想的机器
Assuming the technology can be made to work as AV firms expect, it is not hard to imagine the beginnings of the driverless era. Cost means that self-driving vehicles will at first serve as robotaxis, summoned using a ride-hailing app. That way they get used more, offsetting their costs, and provide transport that is cheaper per mile than owning a car, undermining the case for car ownership, at least for townies. UBS, a bank, reckons that urban car ownership will fall by 70% by 2050. Today’s cars sit unused 95% of the time, so a widespread switch to robotaxis would let urban land wasted on parking be reallocated.
假设这项技术可以像自动驾驶汽车公司预期的那样工作,不难想象无人驾驶时代即将到来。从成本的角度考虑,自动驾驶技术会首先使用出租车上,提供叫车服务。越是习惯这种方式,越能提供每英里更便宜的运输方式,来抵消了他们的成本,从而减少汽车拥有量,至少会减少城里汽车拥有者的情况。 UBS(瑞士联合银行)认为,到2050年,城市汽车拥有量将下降70%。现有汽车95%的时间未被使用,因此广泛转用自动驾驶出租车,可以让城市停车场浪费的土地得以重新分配。
AVs would dramatically reduce the number of road deaths and, being electric, cut harmful emissions in places with clean grids. Clever routing, closer spacing between vehicles and dynamic congestion-charging could cut traffic. Like cars before them, AVs will reshape cities (a long commute is easier if you work or sleep en route) and redefine retailing (shops can come to you). Carmakers will face enormous change ; instead of selling to individuals, they will supply fleet operators, or reinvent themselves as “mobility service” providers.
无人驾驶汽车将极大地减少交通死亡率,而且由于使用电力启动,这种电力清洁能源网络能够减少有害排放物。选择路径时更聪慧,车辆间距可以控制得更小,动态控制拥挤收费,都可以减少交通拥堵。像之前的汽车一样,无人驾驶汽车将改造整个城市的面貌(长途通勤的人们将更加方便,因为人们可以在路上继续工作或者休息),也将改变零售方式(商店可以自动来到你身边)。汽车制造商将会面临巨大变革(具体见文章),他们不再向个人出售,还而是为车辆运营商服务,或者将自身改造为“流动服务”供应商。
Economists and urban planners should rejoice because AVs mean that, for the first time, the unwelcome externalities associated with cars can be fully priced in. In particular, dynamic road-tolling and congestion charging, adjusting the cost per kilometre according to the time of day, level of traffic, length of trip and so on, will allow fine-tuning of entire urban-transport systems. By setting taxes and tolls accordingly, planners can subsidise rides in poor districts, for example, or encourage people to use public transport for longer trips. They can also ensure that the roads do not end up full of empty vehicles looking for riders. Such granular road-pricing is the logical conclusion of existing schemes. Some cities already have congestion-charging regimes, subsidise ride-hailing in poor areas ill-served by public transport, or impose per-ride taxes on Uber, Lyft and their kind.
经济学家和城市规划者应当感到高兴,因为无人驾驶汽车时历史上第一次意味着,不受欢迎的汽车相关外部效应,都可以充分反映出来。特别地,动态的道路收费和拥堵收费以后都可以根据每天的时间、交通水平、路途距离等等来调整每公里收费,这将对整个城市交通系统进行微调。通过设置税收,征收通行费,城市规划者可以把钱用于补贴贫困地区的交通,或者鼓励人们在长途旅行时乘坐公共交通工具。他们也可以通过无人驾驶汽车避免城市中很多一辆辆空载的汽车寻找乘客。这种颗粒状的道路定价时将现有交通逻辑分析得出的结论。一些城市已经开始征收交通拥挤费用,给那些交通不便的贫困地区补贴租车服务,或者提供像uber、Lyft之类的出租车。
Yet the same tolling schemes that will let city planners minimise congestion or subsidise robotaxi services in underserved “transport deserts” have a darker side—and one to which too little attention has been paid. AVs will offer an extraordinarily subtle policy tool which can, in theory, be used to transform cities; but in the hands of authoritarian governments could also become a powerful means of social control.
然而,这类收费项目在城市里可以帮助城市规划者减少拥堵,在服务较差的交通稀缺地带补贴无人驾驶出租车,但是这些还有阴暗的一面,而这一面目前几乎无人关注。无人驾驶汽车作为精妙独一的政策工具,理论上可以改变城市面貌;而一旦落入权威型政府手上,也可以成为控制社会的有力方式。
Panopticons on wheels
轮上的圆形监狱
For a start, AVs will record everything that happens in and around them. When a crime is committed, the police will ask nearby cars if they saw anything. Fleet operators will know a great deal about their riders. In one infamous analysis of passenger data, Uber identified one-night stands. If, as seems likely, human-driven cars are gradually banned on safety grounds, passengers could lose the freedom to go anywhere they choose. The risk that not all robotaxis will serve all destinations could open the door to segregation and discrimination. In authoritarian countries, robotaxis could restrict people’s movements. If all this sounds implausible, recall that Robert Moses notoriously designed the Southern State Parkway, linking New York City to Long Island’s beaches, with low bridges to favour access by rich whites in cars, while discriminating against poor blacks in buses. And China’s “social credit” system, which awards points based on people’s behaviour, already restricts train travel for those who step out of line.
首先,无人驾驶汽车会记录发生在汽车里以及汽车周边的所有事情。当有犯罪行为出现,警察会询问周边汽车,是否“看”到什么。车辆调度员将会知晓驾驶员的大量信息。在一篇分析乘客数据的臭名昭著的文章中,优步表示识别出了一夜情。如果出于安全考虑,人们逐渐禁止人工驾驶汽车——这好像具有很大可能性——乘客或许会失去选择目的地的自由。并不是所有的无人驾驶出租车都会去往任意一个地方,这可能会为人群隔离和歧视以可乘之机。在威权国家,无人驾驶出租车可以限制人们的出行。如果你觉得这听起来天方夜谭,请想想 Robert Moses恶意设计的南方州大道, 南方州大道连接了纽约市和长岛沙滩,桥梁高度低,有利于汽车出行的有钱白人,但歧视了乘坐公交车出行的贫穷黑人。国内的“社会信用”体系,根据人们的行为奖励积分,已经限制“越线”之人乘坐火车出行。
So as robotaxi services roll out this year, and expand to cover wider areas in more cities in the years to come, there is more to think about than technology and transport policy. Experiments with different pricing schemes, decisions about whether to ban private vehicles from city centres, and license auctions for competing private robotaxi operators sound harmless enough. But collectively they represent a seismic shift for society. Autonomous vehicles offer passengers freedom from accidents, pollution, congestion and the bother of trying to find a parking space. But they will require other freedoms to be given up in return—especially the ability to drive your own vehicle anywhere. Choices about who can go where, when and how are inescapably political in nature.
所以随着自动驾驶的出租车服务在今年推出,并在未来几年扩展到更多城市以覆盖更广泛的地区,除了技术和运输政策,还有更多需要考虑的问题。尝试不同的定价方案,决定是否禁止私人车辆进入城市中心,以及对竞争的私人的无人驾驶出租车运营商进行许可拍卖,听起来都是无害的。但总而言之,它们代表了社会的巨大转变。自动驾驶汽车把乘客从事故、污染、堵塞和寻找停车位中解放出来。但人们同时要放弃其他一些自由,特别是去任何地方都能驾驶自己的车。关于谁可以去哪里,在何时以及怎么去,本质上都属于不可回避的政问题。
A century ago cars were seized upon as a solution to the drawbacks of horses, which were clogging city streets with manure. The broader social consequences of cars, both good and bad, were entirely unforeseen. Today the danger is that AVs will be treated merely as a technological solution to the problems associated with cars and that, once again, the wider impacts will be overlooked. AVs have the potential to transform physical transport as radically as packet-switching transformed the delivery of data. But as with the internet, realising their benefits is a matter of politics as well as technology. AVs offer a chance to forge a new and better trade-off between personal mobility and social impact—but only if the lesson of the horseless carriage is applied to the era of the driverless car.
一个世纪以前,汽车的出现解决了马的缺点:马粪堵塞了城市街道。汽车所带来更广泛的社会问题,不管好坏,都是当初完全无法预料到的。今天的担忧是,自动驾驶汽车将被仅仅视为一种技术解决方案,来应对普通汽车相关问题,又一次,其更广泛的影响将被忽视。像分组交换彻底改变数据传输方式一样,自动驾驶汽车有可能彻底改变物理传输方式。又如互联网,意识到它们的好处既是技术问题也是政治问题。自动驾驶汽车提供了一个机会,可以在个人流动性和社会影响力之间达成一种更新更好的平衡,但前提是自动驾驶汽车时代吸取了传统汽车的教训。
packet-switching:is a method of grouping data transmitted over a digital network into packets which are composed of a header and a payload. Data in the header is used by networking hardware to direct the packet to its destination where the payload is extracted and used by application software. Packet switching is the primary basis for data communications in computer networks worldwide.(by Wikipedia)
翻译组:
Cece,女,消防工作者,CATTI三笔
Evelyn,女,消防工作者,CATTI三笔
Jane,女,卫生民工,经济学人爱好者
Alieen,女,大四数学狗,经济学人爱好者
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Neil,男,外贸民工,经济学人镀锌粉
Samantha,女,外企低管,邓伦未婚妻
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观点 |评论|思考
本次观点由Wesley独家奉献
Wesley, 男,自由职业,经济学人爱好者
无人驾驶汽车对人类生活的影响除了在出行方式方面,还有对城市的重塑。首先,城市将可以节省出大量的公共空间。有研究机构做过一项关于旧金山城市研究和非营利性城市规划的调查报告,用来观测无人驾驶汽车的营运效率,他们发现,以无人驾驶汽车运营能力估计,将可以减少400%的车辆交通压力,即使最保守的估计也会在200%,如果无人驾驶技术真的应用开来,城市将可以生出大量的公共空间。这些公共空间的来源包括原有的公共道路网络、公共停车场和加油站、居民住宅的停车库,所有这些都将会因为无人驾驶汽车的普及而有不同程度的减小甚至是取消。其次是建筑物和街道界面会被重新设计,会有专门针对上门服务的上下车的地点被设计出来; 还有可能会引发城市扩张,更多的人可以使用更轻松的出行方式,导致人们思考居住在靠近城市和就业中心的地方,并因此改变目前的房产价值、规划控制和土地供应,更便利的通勤方式将对住宅地产价格产生影响,并可能人们对城市中心房产的偏好转向郊区房产。
无人驾驶汽车将会如何侵犯个人的隐私呢?要想让无人驾驶汽车更好的工作,从技术上讲就是要通过复杂的传感器为其注入海量数据,这样一来,无人驾驶汽车才能知道自己身在何方,要去往何处,并且能够追踪探测到出现在道路上的物体。无人驾驶汽车将依靠高科技的相机和将其精确的GPS数据来完成工作,这同时也意味着这辆汽车将要收集大量的车主信息。这些信息包括你的ID,家庭工作住址,家人朋友同事信息,生活喜好、饮食习惯、你与友人在车上的对话等等等等,即使你不愿意乘坐无人汽车而采取步行或自行车的方式,而路过的一辆辆无人汽车早将你的影像摄入其中,并共享到数据库中,这样你的行踪也无所遁形。在这样的时代,每个人都没有秘密。
而关于对用户数据的利用和保护的疑问,无人汽车公司却并不能给出一个明确的答案。前两年,美国马萨诸塞州参议院埃德·马尔基曾在一次美国国会举行的针对无人驾驶汽车的听证会上向来自Google.通用汽车以及Lyft的代表提问,对无人驾驶汽车能否承担起保护消费者隐私最低标准提出疑问,然而这些代表均为表态,谷歌首席法律顾问表示,现在就给出“最糟糕假设”或就所有数据将如何被使用下结论还为时尚早。
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