Rivian 全自动驾驶豪赌:Autonomy+ 月费 49.99 美元叫板特斯拉 FSD

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在加州帕洛阿尔托绿树成荫的街道上,一辆看似普通的 Rivian R1S 电动 SUV 正在自主穿行。它经过 1939 年惠普创立的那间传奇车库,掠过斯坦福大学校园——21 年前,Sebastian Thrun 领导的团队正是在这里起步,其改装的大众 SUV "Stanley" 在 2005 年 DARPA 无人驾驶挑战赛中完成了 212 公里莫哈韦沙漠赛程,成为全球首辆无人工干预完成该课程的车辆。而今天,记者坐在这辆 Stanley 的"后裔"副驾上,体验的是 Rivian 的 Autonomy+ 系统——一套允许车主输入地址、然后由车辆自动驾驶至美国和加拿大任何已绘制地图目的地的点对点系统。这套系统即将搭载于年底前亮相的全新 R2 SUV,并通过 OTA 更新推送给最新的 R1S 和 R1T 车型。

价格战先行:订阅模式暗藏玄机

定价策略成为这场自动驾驶竞赛的首个交锋点。Rivian 将 Autonomy+ 定为每月 49.99 美元,或一次性支付 2500 美元。相比之下,特斯拉的 FSD(Full Self-Driving Supervised,命名颇具误导性)收费每月 99 美元,几乎是 Rivian 的两倍。奔驰即将在 CLA 级电动车上推出的 MB.Drive Assist Pro 则采取三年 3950 美元的订阅方案——但该系统仍要求驾驶员至少一只手不离方向盘。

不过需要清醒看待的是,尽管 Autonomy+ 表现出色,它在 SAE(美国汽车工程师学会)分级体系中仍属 Level 2+,即人类驾驶员必须随时准备接管。真正的战场在 L3 和 L4:前者允许驾驶员在限定时段"放手"处理邮件或观影(但不能睡觉),后者则意味着车辆可以独自出门取披萨、乘客可以躺在后座读报。目前在美国、中国和中东运营的 Robotaxi 已证明 L4 可行,但规模仅限二十余个城市的特定商业服务范围内。

【关键数据】

- Autonomy+ 订阅价格: 49.99 美元/月,或 2500 美元买断

- 竞品定价对比: 特斯拉 FSD 99 美元/月,奔驰三年订阅 3950 美元

- Uber 战略投资: 12.5 亿美元

- L4 Robotaxi 落地时间: 2028 年启动

- 首搭平台: 全新 R2 SUV,年内发布

技术路线:端到端 AI 与自研芯片的组合拳

Rivian 的技术方案有别于特斯拉的纯视觉路线:它组合了摄像头、毫米波雷达与激光雷达三重感知套件,并配备自研定制芯片处理传感器数据,其上运行 AI 自动驾驶模型。在获得 Uber 12.5 亿美元注资后,Rivian 计划于 2028 年组建 L4 级 Robotaxi 车队——而这些运营中的出租车,反过来又将成为把 L4 能力延伸至消费级车辆的"训练轮"。

更大的行业图景在于数据闭环。数百万辆联网汽车在全球每个角落巡航,持续向车企回传训练数据。当前的竞赛焦点,是将这些数据喂给具备"端到端"能力的 AI 模型——一种基于深度学习的架构,可将原始传感器数据直接转化为车辆控制指令。工程师们预期,凭借这一架构,长期被怀疑论者视为无解的边缘场景——混乱的城市街道、独特地理环境、密集人流、恶劣天气——终将被逐一攻克。

格局推演:2028 年或成分水岭

从长期看,Rivian 的处境颇为微妙。这家由 MIT 博士 RJ Scaringe 创立的公司媒体关注度极高,但要在 L4 竞赛中胜出,它面对的是特斯拉、丰田、奔驰、大众以及中国比亚迪等一众资金雄厚的巨头。Autonomy+ 以低于特斯拉一半的订阅价格切入市场,实质是用性价比换规模、用规模换数据——这与 Robotaxi 车队形成双轮驱动的逻辑一致。在 AI 浪潮重塑自动驾驶产业的当下,2028 年的 Robotaxi 落地节点或将成为检验这场豪赌成色的关键节点,其成败也将为整个行业的 L4 民用化路径提供重要参照。


出处:Rivian’s Gambit for Full Autonomy

英文原文
I’m sitting in a Rivian R1S SUV as it drives itself down the leafy streets of Palo Alto, Calif. , through areas crowded with touchstones of tech history. At one point I pass the landmark HP Garage , the one-car workshop where Hewlett-Packard, and, arguably, Silicon Valley, was founded in 1939. I skirt Stanford University, where a team led by computer science professor Sebastian Thrun won a US $2 million DARPA Grand Challenge in 2005. The team’s Volkswagen SUV, named Stanley, became the world’s first vehicle to navigate a grueling 212-kilometer Mojave Desert course with no human intervention. The Rivian I’m in might look like any other electric SUV in this affluent town, with its concentration of tech bros, venture capital, and startups. But inside this boxy EV is something special: an Autonomy+ system that will allow owners to enter an address, sit back, and let the vehicle drive to any mapped destination in the U.S. and Canada. This point-to-point system is one of the most advanced semiautonomous-driving systems coming to market. It is also a precursor of the company’s bid to make self-driving cars a reality, for robotaxis and—eventually—for everyday car buyers. After years of incremental advances and frustrating setbacks, self-driving has been swept up in the great AI resurgence, and is now a top priority for investors and global automakers , who envision vast new streams of profits. So here I am, 21 years after that DARPA challenge, riding shotgun in Stanley’s vastly more advanced descendant. Rivian’s Autonomy+ is intended to operate seamlessly on suburban streets like these, sensing and responding to traffic lights, crosswalks, and stop signs. That point-to-point system is set to debut on Rivian’s all-new R2 SUV by roughly the end of this year, and via over-the-air updates for its newest R1S and R1T models. Rivian says it will charge $49.99 a month, or $2,500 up front, versus Tesla’s $99 per month for its rival system, which is somewhat misleadingly called Full Self-Driving (Supervised), or FSD. Mercedes , meanwhile, plans to charge $3,950 for a three-year subscription for the forthcoming MB.Drive Assist Pro on its CLA-Class EV; that system still requires at least one hand on the steering wheel. Video released by Rivian shows the company’s R1 SUV being driven on a variety of urban and rural roads, according to the company. Rivian plans to introduce this self-driving system to compete with Tesla’s offering before the end of 2026. Rivian Impressive as it is, Autonomy+ is only a Level 2+ system in the classification system established by the Society of Automotive Engineers. Level 2+ means that a human driver must be ready to retake control at any moment. Rivian, along with a horde of deep-pocketed rivals, is aggressively working toward more impressive (and potentially lucrative) levels of autonomy. At Level 3, drivers could “check out” behind the wheel for limited periods, to scroll through emails or watch a movie—but not to sleep. The big race right now is to deliver Level 4 autonomy : A car you could (in theory) dispatch to pick up a pizza, and have it carted home on the heated, unoccupied driver’s seat—or in which you could spend the ride lounging alone in the back seat, enjoying a private slice while reading a newspaper. At Rivian’s software lab in Palo Alto, Calif., a technician evaluated code for the company’s self-driving system. Jason Henry/Bloomberg/Getty Images Robotaxis currently roaming the U.S., China, and the Middle East have proved that driverless, Level 4 autonomy is possible. These cars operate in relatively tiny numbers in a couple of dozen cities , and within the specific constraints of commercial services. Now Rivian and its many rivals—including Tesla, Toyota , Mercedes, Volkswagen , and China’s BYD are racing to bring that level of self-guided mobility to the masses. Rivian’s strategy combines a suite of cameras, radar, and lidar; a custom set of silicon chips, developed in-house, to process sensor data; and an AI autonomy model running on those chips. With $1.25 billion in backing from Uber, Rivian plans to graduate to a fleet of self-driving, Level 4 robotaxis starting in 2028. Those taxis, in turn, will be the literal training wheels for extending Level 4 ability to consumer vehicles. Meanwhile, millions of connected cars, as they cruise every nook and cranny of the globe, are already sending data to train automakers’ systems. The race is on to funnel those data through fast-improving AI models with “end to end” capability: an AI architecture, powered by deep learning, that processes raw sensor data directly into physical vehicle commands. So equipped, engineers anticipate they’ll be able to solve the tricky edge cases—tangled urban streets, unique geographies, swarms of pedestrians, inclement weather—that skeptics once deemed intractable. Rivian’s Plan for Level 4 Self-Driving Despite the company’s high media profile, including a spotlight on RJ Scaringe, its MIT-doctorate founder

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