这是一篇引用 Medium上Tom Standage最新关于无人驾驶的文章.

What’s it like to ride in a self-driving car?

乘坐无人驾驶车是一种什么感觉？

It’s thrilling for a minute or two, and then boring. Which is a good thing
头两分钟先是兴奋, 然后就感到无聊. 但这应该是一个好事

Where we’re going, we don’t need steering wheels
我们打算去哪里, 我们不需要方向盘

Autonomous vehicles (AVs) are one of the most talked-about technologies of the moment. And little wonder: they promise to revolutionise the transport of people, and physical goods, just as dramatically as the internet transformed the delivery of information. But they raise many questions. When will they be available? Will they be safe? Will they make car-ownership obsolete? And most of all: what is it like to ride in a car that drives itself?

无人驾驶是目前谈论的最多(最热门)的技术之一. 并不奇怪: 就像互联网改变了信息的传播方式一样的戏剧性, 无人驾驶技术承诺给人员和货物的运输带来革命性的巨变的同时也带来了诸多疑问. 这些技术啥时候成熟? 它们安全吗? 它们会使人们不再需要对车辆有拥有权吗? 这其中最重要的问题是: 乘坐自动驾驶的车辆到底是一种怎样的体验?

I’ve spent the past few months working on a 10,000-word special report on AVs for The Economist, which was published in this week’s issue. The focus of my report is mostly on the long-term implications of AVs, based on the assumption (a reasonable one, I think) that the technology can be made to work reliably in the next few years. Rather than focusing on the minutiae of things like the ever-changing industry alliances, or who is suing who, I concentrated instead on the impact on urban planning, the transformation of retailing and the broader social and political implications of cars that can drive themselves. I spoke to as many urban planners and social historians as machine-learning experts or car-industry executives. All this horizon-scanning and future-gazing was fun. But to kick off the report, I had to actually go in a self-driving car. Which is how I found myself, on a snowy morning a few weeks ago, standing in a car park in Pittsburgh, waiting for an automated ride.

我已经花了几个月的时间为”经济学人”准备一份关于无人驾驶车辆10,000字的特别报告, 这份报告会在本周发表. 基于技术在今后的几年内应该变得更加成熟的假设(这是一个合理的假设), 我的这份报告主要关注点在于无人驾驶(对我们的)长期影响. 与其去关注那些细枝末节的事情, 例如不断变化的行业联盟, 或者谁起诉了谁, 我更加关注无人驾驶车辆对城市规划的影响, 对零售业的改变和对更广泛的社会和政治的影响. 我和很多城市规划者, 社会历史学家, 也包括机器学习专家, 汽车行业的高管交谈过. 所有这些全方位的审视和对未来的展望都非常有趣. 但是抛开这份报告, 我觉得我更有必要坐进一辆无人驾驶的车里. 这就是为啥, 在前几周的一个下雪的早上, 我发现自己站在匹兹堡的一个停车场, 等待一次无人驾驶的体验.

Three years ago I went in a self-driving car in Shanghai. It was quite a basic example: what is known in the field as a “Level 2” vehicle. This means it can steer itself, and maintain a safe distance from the car in front, while driving in highway traffic. I rode in an Audi A7, and a few cars now on the market (notably those made by Tesla) are capable of Level 2 automation. But the driver is required to keep hands on or near the wheel, and to pay attention to the surroundings, in case anything unexpected happens. With the next level up, Level 3, the car takes more responsibility for monitoring its surroundings, allowing the driver to relax a bit more. But if the car encounters a situation it cannot deal with, it sounds a warning telling the driver to resume control. The first Level 3 vehicle, the Audi A8, goes on sale this year.

三年前我在上海尝试过一辆无人驾驶汽车. 那是一辆最基本的样车: 在这个领域内作为”Level 2”的车辆. 这意味着它可以在高速公路上自动驾驶, 并保持于前方车辆一定的安全距离. 当时我乘坐的是一辆Audi A7, 现在市场上达到Level 2的车辆有好一些了(尤其是Tesla生产的). 但是驾驶员需要把手放在方向盘上或靠近方向盘的地方, 并且注意周围的环境, 才能应对任何不可预期的事情发生. 再上一个级别的, 就是Level 3, 这类的车辆可以监控它周围环境时承担更多的责任, 让驾驶员更加的轻松. 但是如果这类车辆遇到它不能处理的情况, 就会发出警告的声音用来提醒驾驶员恢复控制. 第一辆Level 3的车辆, Audi A8, 今年会开卖.

Level 2 and Level 3 are really just glorified forms of cruise control. A truly self-driving vehicle doesn’t just follow the road ahead of it. It does route-planning and knows where it’s going. It handles junctions, crossings, traffic lights and road signs, and interacts smoothly with other vehicles, pedestrians and cyclists. This is, to say the least, a big leap. A Level 4 vehicle is defined as one that can do all of this, without any input from a human driver, within a limited area: in practice, a city neighbourhood that has been mapped in very fine detail, to give the car a big head start in understanding its surroundings. A Level 5 vehicle (something that does not yet exist) is one that can in theory drive anywhere, like a human driver. That may be an unattainable goal: some people dislike driving at night, or in snow, and I would not volunteer to drive a car in Delhi unless I really had to. The upshot is that the most advanced AVs on the roads today are generally Level 4 vehicles that operate within specific regions of particular cities.

Level 2和Level 3基本上就是定速巡航的增强形式. 真正的无人驾驶汽车不仅仅是沿着路, 朝前开而已. 它也要规划路线, 并且知道它打算去哪里. 它可以处理遇到车辆汇入点, 十字路口, 交通信号灯和路面的标志时的各种状况, 并且和路面上的其他车辆, 行人和自行车平稳的互动. 这个至少才可以说是一个巨大的飞跃. 在一个被限定的区域内, Level 4的无人驾驶车辆就是可以在没有任何人类驾驶员干预的条件下完成上述所有目标的车辆. 这个被限定的区域实际上就是已经被精细的绘制在地图上的城市, 这让我们的无人驾驶车辆在理解它的周围环境中有了一个很好的开端. Level 5的无人驾驶车辆(目前还不存在)就是那种理论上可以在任何地方无人驾驶的车辆, 就像人类驾驶员一样. 这也许是一个无法达成的目标: 有些人不喜欢在夜间开车, 或下雪的时候开车, 同样我也不愿意在”Delhi”自愿开车, 除非迫不得已. 结果就是目前路上最先进的无人驾驶车辆只是一般意义上的第4代无人驾驶车辆, 只能在特定的城市的指定区域驾驶.

Different cities offer different testing environments. Phoenix, Arizona is popular because it has a regular grid system and reliably good weather (snow can confuse the LIDAR sensors that AVs use to scan their surroundings). AVs can also be seen on the roads in and around Mountain View, for similar reasons, and because so many technology firms are based in the Bay Area. The early history of self-driving vehicles was shaped by the rivalry between Stanford University in California and Carnegie Mellon University in Pittsburgh, which have produced many of the engineers now leading AV projects around the world. This has made Pittsburgh another hub of AV research and testing. The city is considered a more challenging environment than Phoenix, because its road layout is more complex, and the weather is worse. San Francisco’s urban environment is particularly complex, which is why Kyle Vogt, the boss of Cruise, an AV startup acquired by General Motors, says it is the best place for testing (check out his blog post for some very impressive video footage). If you can make it there, you might say, you can make it anywhere.

不同的城市提供不同的测试环境. 亚利桑那的凤凰城比较受欢迎, 是因为它有着规则的网格道路和好天气(大雪可以让无人驾驶车辆扫描他们周围环境的LIDAR传感器失灵). 基于同样的理由, 我们也可以在山景城的路上看到无人驾驶车辆, 也是因为太多的技术公司都在湾区. 无人驾驶的早起历史是由加州的斯坦福大学和匹兹堡的卡内基梅隆大学竞争而形成的, 这给现在的世界输出了大量的工程师来引导无人驾驶的项目. 这点也让匹兹堡成为另外一个无人驾驶的研究和测试中心. 这座城市具有被认为比凤凰城更具有挑战的环境, 因为它的马路的布局更加复杂, 并且天气情况更加恶劣. 旧金山的市区的环境也是特别复杂, 直就是为啥被通用汽车收购的无人驾驶创业公司的老板Kyle Vogt, 认为它是最佳的测试地点(你可以在他的博客上找到很多印象深刻的视频短片). 如果你在旧金山可以搞定, 你可以说你可以在任何地方搞定无人驾驶.

A self-driving Uber vehicle. That round thing on the top is the LIDAR sensor.

Anyway, back to Pittsburgh. Uber has hired a lot of engineers from Carnegie Mellon, and Uber’s Advanced Technologies Group, which is developing its self-driving cars, is based in the city. The vehicle I climbed into was a modified Volvo XC90, with a bundle of extra sensors, including cameras and a spinning LIDAR unit, on its roof. Ryan, the vehicle’s safety driver, manually drove the vehicle out of the car park and onto the public roads, before pressing a button to engage the self-driving system. And then the car started driving itself.

不管怎么说, 先回到让我们先回到匹兹堡. Uber已经从卡内基梅隆雇佣了大量的工程师, Uber开发它无人驾驶车辆的技术团队也坐落在匹兹堡. 我爬进去的是一辆根据Volvo XC90改造的车辆, 车顶上带着一堆外置的传感器, 包括摄像头和可以转动的LIDAR单元. Ryan, 这辆车的安全驾驶员, 在按下一个按钮启动自动驾驶系统之前, 他驾驶这辆车从停车场开出来, 并且开到马路上. 然后这辆车才开始靠它自己驾驶.

At first, the experience is thrilling. It seems like magic when the steering wheel turns by itself, or the car gently slows to a halt at a traffic light. The autonomous Uber drove carefully but confidently in downtown traffic and light snow, slowing down when passing a school or approaching the brow of a hill, and putting its foot down (as it were) when faced with an open, straight road with no other traffic. The most noticeable difference from a human driver was that the vehicle made no attempt to avoid Pittsburgh’s notorious potholes, making the ride slightly bumpy at times. Sitting in the back seat, I could see a digital representation, displayed on an iPad mounted between the front seats, of how the car perceived the world, with other vehicles, pedestrians and cyclists highlighted in clusters of blue dots. I felt as though I was living in the future. But then, after a minute or two, the novelty wore off. When technology works as expected, it’s boring.

起初的体验是很激动人心的. 当方向盘自己转动的时候, 或者这辆车渐渐的减速停在交通信号灯前, 使它看上去像魔法. 这个无人驾驶的Uber在市中心拥挤的交通和小雪的情况下小心并自信的驾驶着, 当通过学校或接近山顶的时候会降低自己的速度, 并且在遇到开阔的没有其他车辆的直行道路上, 它会踩下油门(就好像踩下油门). 和人类司机相比较最大的区别就是这辆车没有试图躲避匹兹堡名声狼藉的坑坑洼洼, 使整个驾驶过程有些轻微的颠簸. 坐在后排, 我可以看见一个数字仪表盘, 显示在一个安装在前排座椅中的的iPad上, 用高亮的一组蓝点标记其他车辆, 行人和自行车, 展现无人驾驶的Uber是如何观察这个世界的. 我感觉自己就像生活在未来世界. 但是过了几分钟, 新奇感就消失了, 技术如预期的工作, 它是显得很枯燥了.

How the car sees the world. Objects of particular interest are shown in blue.

This is, in fact, exactly the reaction that engineers are hoping for. Noah Zych, Uber’s head of system safety for autonomous cars, told me that after working on AVs for ten years, he was finally able to offer his parents a ride in a self-driving car last year when they came to visit. After their ride ended, he asked them what they thought of it. “And my mom said, ‘actually, it was kind of boring’. And that’s the response that we really want,” he says. Uber has offered some riders in Pittsburgh and Phoenix the option to travel in its self-driving vehicles, provided the start and end points of their ride fall within their area of operation. (Riders can say no if they want to.) Around 50,000 people have travelled in Uber’s self-driving cars in the past couple of years. Uber wants to understand how to design the in-car experience (such as what information should be shown on the screen), and it also wants to reassure both riders and other road-users about the safety of autonomous vehicles. “The best way to convince people that a self-driving vehicle is going to be safe and capable of driving them around in the future is to give them that first experience,” says Mr Zych.

事实上, 这是工程师们期待的反馈. Noah Zych, Uber自动驾驶系统安全部门的头, 他告诉我他的无人驾驶领域工作了十年后, 他终于可以给来去年来参观的父母提供一次无人驾驶的乘坐体验. 试乘体验之后, 他问他们的感受. “然后我母亲说, ‘事实上, 有些无聊’, 这就是我们想要的反馈,”. Uber已经为在匹兹堡和凤凰城的一些车手提供无人驾驶车辆的选择, 只要他们提供的驾驶的起始点和终点落在可以操作的区域内. (驾驶者可以说不, 如果他们想这样的话). 在过去的几年里, 大概有50,000左右的人已经参与了Uber的无人驾驶体验. 通过这些反馈, Uber想知道如何设计车内的体验(例如怎样的信息应该被展示到屏幕上), 并且它也想让乘客和路人对无人驾驶感到放心. Mr Zych说, “最好的方式说服人们无人驾驶的车辆在未来会变得越来越安全就是给他们提供一手的体验”.

Ryan, the safety driver in my self-driving Uber, had to take over occasionally, for example to steer the car around a delivery truck that had blocked the road — the car was programmed to play things safe and wait, rather than cross the double-yellow lines in the middle of the road — and to guide the car through roadworks where the lane markings had been recently changed. A couple of times he also took over when the car looked as though it might be passing a bit too close to another vehicle. In each case a collision was unlikely, Ryan explained, but if people think a collision is imminent, they will not feel safe. So part of his job is to flag up instances where the car’s driving style could be tweaked to provide a better experience for passengers. At the end of each day, the contents of the car’s on-board computers are downloaded for analysis. Each time the safety driver had to take over — an event known as a “disengagement” — the corresponding data can be analysed to see how the car’s software could be improved. It is then possible to simulate how the car would have responded with various modifications to its algorithms. “We can play it back again and again, vary the scenario and see the distribution of outcomes,” says Mr Zych. After being tested in simulation, the improved software is then rolled out in real vehicles. It is first tested on a small subset of routes, called “canonical” routes, which test different aspects of its behaviour. If it works as expected, the software is then rolled out for general use.

Ryan, 是我的自动驾驶车里的安全司机, 有时候不得不主动接管车辆, 举例来说, 驾驶车辆绕开挡住马路的一辆卸货卡车 - (遇到这种情况)这辆自动驾驶的车辆被设定保持尽可能的安全, 并且进入等待状态, 而不是穿过马路中间的双黄线 - 并引导车辆通过最近改变车道标线的道路工程. 有几次, 当这辆车子看上去好像和其他车辆过于接近的时候, 他也接管了驾驶. Ryan解释到, 碰撞的情况其实是不会发生的, 但是如果人们认为碰撞将要发生, 他们会感到不安全. 为了给乘客提供更好的体验, 他的部分工作就是在这辆车驾驶风格中可以微调的地方标记这些实例. 每天工作结束前, 这辆车子的车载电脑上的内容会被下载下来用以分析. 每次安全司机不得不介入的情况被认定为一次”脱靶” - 对应的数据可以被分析用来如何改进这辆车的软件. 这样就可以模拟如何让车辆通过对算法的改进来做出不同的响应. 在模拟环境中测试之后, 改进的软件会在真实的车辆中更新. 我们可以一次又一次地回放，改变场景并查看结果的分布. 首次测试会在线路选取较小的子集进行, 称之为”标准的”线路, 用来测试软件的不同方面. 如果按照预期的工作, 软件会正式升级.

I spent most of my hour in a self-driving Uber discussing disengagements, algorithm design and user interfaces, which (to me, at least) are just as exciting as being in a futuristic robocar. And even when the driving algorithms are working perfectly, there are several practical questions that still have to be addressed. For example, how will people actually hail driverless vehicles? They can’t just stop anywhere, or they will block traffic and annoy people. Human drivers can pick a good place to stop, but machines will need help. Uber has already started identifying good pick-up and drop-off points in some cities, and suggesting them to riders of human-driven vehicles. But it may be that in future, streets will have designated pick-up and drop-off areas; already, some university campuses and apartment blocks are being built with ride-hailing in mind. And how will a self-driving vehicle be able to tell that everyone is on board and ready to go? Some kind of “start” button will be needed — and a “stop” button, too, in case a rider suddenly wants to get out of the vehicle. (The driverless Uber has a “pull over” button for this.)

我在这辆自动驾驶的Uber上花了大量的时间(和Ryan)讨论”脱靶”的情况, 算法设计和用户界面, 这些对于我来说和在一辆未来的robocar一样激动人心. 然而即使当驾驶算法可以完美的工作, 这里仍然有一些实际的问题需要被解决. 举例来说, 将来人们如何和无人驾驶车辆打招呼? 它们不可以随便停车, 否则它们会阻塞交通并且干扰人们(的正常活动).无人驾驶车辆如何能够告诉车上的乘客准备出发? 某种类型的”开始”按钮还是需要的 - 当乘客忽然想下车的时候, “停止”按钮也是需要的. 但是或许不久的将来, 街道会重新设计上客和下客的区域. 人类的司机可以选择一个最佳的地方停车, 但是机器仍然需要协助. Uber已经开始在某些城市标识理想的上客和下客的位置, 并且建议他们乘坐人类驾车辆. 已经有一些大学校园和公寓大楼正在建设中(with ride-hailing in mind). (无人驾驶的Uber有一个”靠边停车的”按钮来对应这种情况).

Waymo, the self-driving unit of Google’s parent company, hopes to launch a robotaxi service in Phoenix later this year. Waymo has the lowest disengagement rate in the industry, and is generally considered the leader in the field; its autonomous vehicles can now operate in Phoenix without the need for safety drivers. GM’s Cruise, which is fast catching up with Waymo, hopes to launch a robotaxi service in 2019, using autonomous Chevy Bolts that do not have a steering wheel, pedals or any other kind of manual controls. So they, too, will have to be able to operate entirely autonomously without a safety driver. Dozens of other firms are also working on self-driving vehicles. Over the coming months and years more AVs will take to the roads in more cities, and the areas in which they operate will gradually expand. Probably sometime in the 2020s, you will take your first ride in a self-driving car. It will be exciting at first — but then, if all goes well, it should quickly become reassuringly boring.

在今后的几年里, Waymo, Google母公司的自动驾驶部门, 打算在凤凰城提供无人驾驶的出租车服务. 在业界, Waymo的”脱靶”率是最低的, 并且被公认为这个领域内的领导者; 通用汽车的Cruise, 是最接近Waymo技术的, 他们希望在2019年提供无人驾驶的出租车服务, 使用自动驾驶的Chevy Bolt, 这种车没有方向盘, 踏板和其他各种手动控制的东西. 所以它们将不得不在没有安全司机的情况下完全自动驾驶. 一堆其他的公司都正在研发自动驾驶的车辆. 在今后的几个月里和几年内, 更多的无人驾驶车辆将会在更多的城市里上路, 并且它们的行驶范围会更加广阔. 有可能在2020年, 你可以在无人驾驶的车辆. 它首先将会是兴奋的, 然后, 如果它运行正常, 它会变得让人踏实的无聊.

Waymo’s fully self-driving cars are here