2 Driverless Cars Crashed Going 155 mph. That Could Be a Good Thing
2 Driverless Cars Crashed Going 155 mph. That Could Be a Good Thing
两辆无人驾驶赛车以155英里/小时的速度相撞，但这可能是一件好事
The grandstands erupted with shock as engineers clutched their heads in the paddock. One driverless race car, produced by the company PoliMove, slammed into Unimore’s slowing vehicle in an event held by the Abu Dhabi Autonomous Racing League (A2RL). 当看台上一片哗然，工程师们在维修区抱头惊叹时，一辆由PoliMove公司制造的无人驾驶赛车，在阿布扎比自动驾驶赛车联盟（A2RL）举办的赛事中，猛烈撞上了Unimore车队正在减速的车辆。
At the famous racing track in Imola, Italy, Autodromo Internazionale Enzo e Dino Ferrari, both cars crashed in an area called Rivazza. This is the circuit’s final sequence, made up of corners that are notoriously difficult to navigate. Formula 1 champions have met a similar fate here. But this time, the impact posed no danger to the drivers because there weren’t any. 在意大利伊莫拉著名的恩佐与迪诺·法拉利国际赛道上，两辆车在名为Rivazza的区域相撞。这是该赛道的最后一段，由一系列以极难通过而闻名的弯道组成。一级方程式赛车（F1）的冠军们也曾在此遭遇过类似的命运。但这一次，撞击并没有对车手造成任何危险，因为车里根本没有人。
Launched in 2024, A2RL sought to introduce self-driving cars to the motorsport to test the boundaries of their current capabilities. And this year’s race at Imola revealed those edges, demonstrating the gap between the computational abilities of autonomous vehicles and their capacity to respond when something goes wrong. A2RL于2024年启动，旨在将自动驾驶汽车引入赛车运动，以测试其当前能力的极限。今年在伊莫拉举行的比赛揭示了这些极限，展示了自动驾驶车辆的计算能力与它们在突发状况下的应对能力之间存在的差距。
Only two of the five cars in the final completed the race. The UAE’s Kinetiz finished first, followed by Germany’s Constructor Racing. PoliMove clocked in at third place, though its battered entrant had to be replaced for the podium ceremony. Two-time winner TUM withdrew its car after it developed a brake problem during the formation lap. 决赛中的五辆车仅有两辆完成了比赛。阿联酋的Kinetiz车队获得第一名，德国的Constructor Racing车队紧随其后。PoliMove车队获得第三名，尽管其受损的赛车不得不被替换以参加领奖台仪式。曾两次夺冠的TUM车队在编队圈出现刹车故障后退出了比赛。
Participating teams had just nine days of physical testing before the race, in conditions that included rain and hail. This also happened to be the league’s first international competition away from its usual testing ground at Abu Dhabi’s Yas Marina Circuit. 参赛车队在赛前仅有九天的实地测试时间，且期间经历了雨雪天气。这也是该联盟首次离开其位于阿布扎比亚斯码头赛道的常规测试基地，在国际赛场上进行比赛。
So why choose one of motorsport’s most unforgiving tracks? “Because everybody can do ‘easy’, right?” says Nicola Palarchi, engineering director at Aspire, the company that founded A2RL. “We have to show we go where it matters.” 那么，为什么要选择赛车运动中最严苛的赛道之一呢？“因为每个人都能做‘简单’的事，对吧？”A2RL创始公司Aspire的工程总监Nicola Palarchi说，“我们必须证明我们去的是真正重要的地方。”
Palarchi made it abundantly clear that autonomous racing did not intend to compete with human racing, which would remain its own motorsport. It could even support the latter. Palarchi明确表示，自动驾驶赛车并不打算与人类赛车竞争，后者将保持其独立的运动地位。它甚至可以为人类赛车提供支持。
Because autonomous racing is pitched as more than spectacle: It’s a laboratory with guardrails. Its proponents describe it as a way to test perception, prediction, and vehicle control at extreme speeds without endangering a human driver. These are all factors in the safety of driverless cars in the real world, and so measuring the limits at which these vehicles succeed—or perhaps more importantly fail—can inform future improvements in the technology. 因为自动驾驶赛车不仅仅是一场表演：它是一个带有护栏的实验室。支持者将其描述为一种在极端速度下测试感知、预测和车辆控制的方法，且不会危及人类驾驶员。这些都是现实世界中无人驾驶汽车安全性的关键因素，因此，衡量这些车辆成功——或者更重要的是失败——的极限，可以为未来的技术改进提供参考。
The first hurdle is perception. The vehicle’s sensors identify its location and surroundings, informing planning software that then chooses a trajectory. Finally, the control system translates that decision into steering, acceleration, and braking. Racing makes each of these stages more challenging, since at high speeds, vehicles have less time to interpret incomplete information, predict another car’s movements, and execute an evasive maneuver. 第一个障碍是感知。车辆的传感器识别其位置和周围环境，通知规划软件，然后由软件选择轨迹。最后，控制系统将该决策转化为转向、加速和制动。赛车运动使这些阶段中的每一个都更具挑战性，因为在高速下，车辆几乎没有时间去解读不完整的信息、预测另一辆车的动向并执行避让动作。
“The car will be blind for a certain point because the track drops off,” Alexander Winkler, A2RL’s head of sporting, said before the final. If one vehicle stopped beyond that drop, he explained, the car behind could have less than a second to react. That warning proved prescient. “由于赛道有落差，车辆在某一点会处于盲区，”A2RL体育主管Alexander Winkler在决赛前说道。他解释说，如果一辆车停在落差之后，后车可能只有不到一秒的时间做出反应。这一警告被证明具有预见性。
Unimore said its car, Gianna, initiated a safety stop after losing all data from its lidar and radar sensors. GPS alone could not locate the car accurately enough to continue racing at speed. The team said future systems could use cameras and an inertial measurement unit to continue at a slower pace until precise localization returned. In other words, the car stopped because it lacked a reliable fallback. Unimore车队表示，其赛车Gianna在丢失了激光雷达和雷达传感器的所有数据后启动了安全停车。仅靠GPS无法提供足够的定位精度以维持高速比赛。车队表示，未来的系统可以使用摄像头和惯性测量单元以较慢的速度继续行驶，直到恢复精确的定位。换句话说，这辆车停下来是因为它缺乏可靠的备用方案。
PoliMove’s vehicle, Eva, detected Gianna ahead, according to the team, but could not avoid hitting it. Gianna had braked with a force of approximately 1 g, with Eva just 1.5 seconds behind it. 据PoliMove车队称，其赛车Eva检测到了前方的Gianna，但无法避免碰撞。Gianna以大约1g的力刹车，而Eva当时仅在它身后1.5秒的距离。
PoliMove said its system identified the danger and began an evasive maneuver. But perception, decisionmaking, trajectory replanning, actuator response, and vehicle dynamics all introduce delays. Once Gianna braked that severely mid-corner, the team said, a collision was physically impossible to avoid. PoliMove表示，其系统识别出了危险并开始了避让动作。但感知、决策、轨迹重规划、执行器响应和车辆动力学都会带来延迟。车队表示，一旦Gianna在弯道中进行如此剧烈的刹车，物理上就不可能避免碰撞。
Even F1 legends like Fernando Alonso and Carlos Sainz have crashed at this part of the track. However, the A2RL teams’ explanation exposes a problem that faster processors alone cannot solve: An autonomous vehicle may recognize a hazard and still be unable to respond before physics takes over. 即使是费尔南多·阿隆索和卡洛斯·塞恩斯这样的F1传奇人物也曾在这段赛道上发生过碰撞。然而，A2RL车队的解释揭示了一个仅靠更快的处理器无法解决的问题：自动驾驶车辆可能会识别出危险，但在物理定律接管之前，它仍然无法做出反应。
TUM’s failure was less algorithmic but equally instructive. The team said its car, Hailey, retired after the rear-left brake became stuck at low-to-medium pressure during the formation lap. Even sophisticated autonomous software cannot compensate for mechanical faults. TUM车队的失败虽然与算法关系不大，但同样具有启发性。车队表示，其赛车Hailey在编队圈时左后刹车卡在低至中等压力状态，随后退赛。即使是复杂的自动驾驶软件也无法弥补机械故障。
Kinetiz’s car, Sparkz, took the lead all the way to a first-place podium finish with Constructor AI’s vehicle as the runner-up. But almost any result can be considered progress when the failures produce useful edge cases: sensor loss, compromised localization, sudden braking, limited visibility, and interaction between autonomous systems making separate decisions. Kinetiz的赛车Sparkz一路领先，最终夺冠，Constructor AI的车辆获得亚军。但当失败能产生有用的边缘案例时，几乎任何结果都可以被视为进步：传感器丢失、定位受损、突然刹车、视野受限，以及做出独立决策的自动驾驶系统之间的相互作用。
Beyond crash data, Palarchi says these motorsport environments provide the opportunity to develop more resilient hardware. Temperatures in cockpits can get near 170 degrees F, and—while hopefully your robotaxi is not that hot—radars and lidars that can withstand high heat can be useful in our warming cities. 除了碰撞数据外，Palarchi表示，这些赛车环境提供了开发更具韧性硬件的机会。驾驶舱内的温度可接近170华氏度（约77摄氏度），虽然希望你的自动驾驶出租车不会那么热，但能够承受高温的雷达和激光雷达在气候变暖的城市中将非常有用。
Chee Kiong Ong, deputy team principal at Kinetiz, also observes that predictive algorithms developed on the track could eventually help civilian vehicles respond to emergencies. “You could probably apply it to make the car stop itself in a safer manner or control it at the limits so that you can save lives,” he says. Kinetiz车队的副领队Chee Kiong Ong也观察到，在赛道上开发的预测算法最终可以帮助民用车辆应对紧急情况。“你或许可以应用它让汽车以更安全的方式自动停车，或者在极限状态下控制它，从而挽救生命，”他说。
One caveat is that, unlike other lab testing, the companies aren’t required to share the precise data collected from their vehicles. The data from A2RL’s EAV 25, the racing car developed by the league based on modified Dallara SF23 cars, currently stays within the competition. 需要注意的一点是，与其他实验室测试不同，这些公司不需要共享从其车辆收集的精确数据。A2RL的EAV 25（由联盟基于改装的Dallara SF23赛车开发）的数据目前仅限于比赛内部使用。
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