迈凯伦认为2026年F1规则下顶尖车手仍能发挥关键作用
针对车手们抱怨软件深度干预驾驶的2026年新规，卫冕车队冠军迈凯伦认为顶尖车手仍能凭借驾驶技术对比赛结果产生影响。
为什么迈凯伦认为在F1 2026规则下最优秀的车手仍然能发挥关键作用
在车手们纷纷批评软件对赛车操控过度干预之际，这支去年的车队总冠军得主表示，天赋依然重要
自F1赛季开始之前，抱怨声就已经不绝于耳。这些不满时有加剧，尤其是在那些所谓的“能量匮乏”赛道上——那里的弯道与直道比例以及弯道类型，都不利于新一代赛车在单圈中为电池充电。
在迈阿密大奖赛前实施的一项规则调整，缓解了因车手电量状态不同而导致的备受诟病的“悠悠球式比赛”。但最近，由于动力单元的自学习算法会针对赛道状况和驾驶技术的细微变化做出反应而造成的速度差异，引发了大量的焦虑。
在斯帕，皮亚斯特里 将其形容为一种“相当糟糕的参赛方式”。
但这种情况在短期内不会改变，尽管有人主张应完全禁止机器学习工具——他们通常会引用F1运动规则中的一句话来作为“一锤定音”的论据。B1.9.1条款规定：“车手必须独自且无辅助地驾驶赛车”。
仍然有人认为，最优秀的车手能够应对这些新挑战，无论它们多么晦涩难懂和令人烦恼。这是迈凯伦工程部门技术总监 Neil Houldey 在F1夏休期间一次圆桌采访中所持的观点。
“实际上，那些明白自己需要做什么的车手、那些头脑清醒的车手、那些世界上最优秀的F1车手，仍然会是最快的，”当被 Motorsport 问及目前是否能够准确评估车手表现时，他这样说道。
"它可能在某些方面发生了变化……这不全是关于最高速度，而是关于后台正在进行的、生成单圈时间的思维过程。
"[斯帕]就是一个很好的例子，实际上Oscar得到了一个稍微不同的动力输出计划，这意味着他损失了零点几秒，但仍然和Lando不相上下。
"但我认为这些事情会相互抵消。你仍然能在整体单圈时间以及比赛中看到好车手和稍逊车手之间的差距。
"我的回答其实是，一切最终都会趋于平衡。可能会有某场比赛或某次排位赛让其中一位车手处于劣势，但我仍然认为最好的车手最终会在赛季结束时出现在最好的位置。"
卫冕冠军兰多·诺里斯在匈牙利大奖赛上夺得了他今年的首场分站冠军。
从根本上说，现行规则体系的局限在于车辆能够储存的能量，该规则将电力输出与内燃机动力近乎按50:50分配。由于电池必须在整圈中不断充电，出于安全及性能的原因，需要软件介入来逐渐降低电力输出，而不是让其突然耗尽。
这套机器学习软件还具有性能方面的功能，它是工程师们试图确定“最优圈”的一部分——即能带来最快单圈时间的能量回收与输出组合。迈阿密规则调整的效果是让国际汽联有更大余地降低能量回收限制，从而以峰值速度换取更持久（虽然略低）的极速。
但这一切都要求车手的操控输入（如油门位置）保持一致。例如，如果车手在某个弯角进攻过于激烈，在同一位置比队友损失了更多车速，那么重新加速就会消耗电能，因此车手会受到惩罚，在圈的后面阶段可用的电能就会更少。
Houldey 认为这是一种与车手们以往所习惯的完全不同层级的风险与回报：激进驾驶现在带来的回报，比一种更讲究头脑、更有纪律的驾驶方式要少。
“这绝对更像是一场考验思维的比赛，”他说。
“而且现在车手需要应对的事情，确实比以前多了很多——即便是在2022-25年[地面效应时代]，车手要做的事情就已经很多了。但现在又多了一层额外的东西，你不仅要把过弯速度把握好，还必须把你管理能量输出的方式、油门开度，诸如此类的方方面面，都做到绝对正确。
“对于工程团队来说，要榨出这些赛车的最大性能，技术难度确实更高了；而对于车手来说，要把这些赛车的潜力发挥到极致，技术难度也更高了。而最终，一如既往，赛车、车手、工程团队的最佳组合才能做出最好的成绩。”
英文原文
Why McLaren feels the best drivers can still make a difference under F1 2026 rules
Amid much criticism from the drivers about the heavy-handed intervention of software in their control of the car, last year’s constructors’ championship-winning team says talent still counts
The complaints have been rumbling since before the start of the Formula 1 season. Periodically they intensify, especially at so-called ‘energy-starved’ circuits where the ratio of corners to straights, and the type of corners, mitigate against the new-generation cars being able to recharge their batteries through the lap.
A tweak to the regulations implemented ahead of the Miami Grand Prix reduced some of the much-criticised ‘yo-yo racing’ caused by drivers being in different states of charge. But more recently speed differences caused by the power units’ self-learning algorithms reacting to small variations in track conditions and driving technique have caused a great deal of angst.
In Spa, Oscar Piastri described it as a "pretty crap way of going racing".
But the situation isn’t going to change in the immediate future, even though there are those who argue in favour of the machine-learning tools being banned entirely – usually citing a phrase from F1’s sporting regulations as a mic drop. Section B1.9.1 states: "The driver must drive the car alone and unaided".
And there is still an argument to state that the best drivers will manage these new challenges, abstruse and bothersome though they may be. That was the perspective of McLaren’s technical director for engineering Neil Houldey in a round-table interview conducted during F1’s summer break.
"Actually the drivers who understand what they need to do, the ones who are switched on, the ones who are the best F1 drivers in the world are the ones who are still going to be the fastest," he said when asked by Motorsport if it’s currently possible to assess driver performance accurately.
"It may have changed in terms of… It's not all about top speed, it's about the thought processes going on in the background that generate that lap time.
"[Spa] is a good example where actually Oscar did get a slightly different deployment schedule, which meant he lost a couple of tenths, but was up with Lando.
"But I think those things balance out. You still see the difference between the good drivers and the less good drivers in the overall lap time and then in the race as well.
"My answer really would be that it all evens out in the end. That there might be a race or a qualifying session here or there where that disadvantages one driver or the other, but I still think you see the best drivers come out in the best place at the end of the season."
Defending champion Lando Norris took his first GP win of the year in Hungary
Fundamentally the limitation of the current ruleset, with its near-50:50 split of electrical deployment to internal combustion power, is the amount of energy the car can store. Since the battery has to be recharged throughout the lap, software intervention is required for safety as well as performance reasons, to taper the electrical deployment rather than have it run out suddenly.
The machine-learning software also has a performance function in that it forms part of the engineers’ attempts to establish the "optimal lap" – the combinations of harvesting and deployment which gives the fastest lap time. The effect of the Miami rule tweaks, which gave the FIA more leeway to reduce energy harvesting limits, was to trade off peak speeds against a more sustained (if slightly lower) top speed.
But all this requires the driver to be consistent with the control inputs such as throttle position. If they attack a corner too aggressively and scrub off more speed than their team-mate in the same place, for instance, re-accelerating costs electrical power so they are punished by having less available later in the lap.
Houldey views it as a different order of risk and reward than drivers are used to: aggression now carries fewer rewards than a more cerebral and disciplined approach.
"It's definitely more of a thinking game," he said.
"And there's definitely a lot more going on for the drivers than there was – even 2022-25 [the ground-effect era] there was a lot happening for the drivers to be doing. But now it's that extra bit, and you've got to get not only your cornering speeds right, but you've got to get the way you go about deploying your energy, your throttle position, whatever it might be, absolutely right as well.
"It's certainly more technically challenging for the engineering team to get the most out of these cars, and it's more technically challenging for the drivers to get the most out of these cars. And in the end, as always, the best combination of car, driver, engineering team ends up doing the best job."
Motorsport.com ·
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