为何不学特斯拉弃用激光雷达 Rivian：成本低可补足摄像头短板

快科技12-17

快科技12月17日消息，同为美国造车新势力，然而Rivian在自动驾驶路线上显然和特斯拉有着不同的见解和坚持。近日，Rivian首席执行官RJ Scaringe在一场最新采访中解释了公司为什么在自动驾驶方案中使用激光雷达。他表示：“在构建模型的过程中、以及在摄像头真正变得显著更强之前，有一些成本很低、速度很快的方法可以用来补足摄像头的短板。”同时举出了具体的例子，比如穿透雾气、穿透密集的雪或大雨，...

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href=http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251217115915a4551aff&s=b><strong>快科技</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>快科技12月17日消息，同为美国造车新势力，然而Rivian在自动驾驶路线上显然和特斯拉有着不同的见解和坚持。近日，Rivian首席执行官RJ Scaringe在一场最新采访中解释了公司为什么在自动驾驶方案中使用激光雷达。他表示：“在构建模型的过程中、以及在摄像头真正变得显著更强之前，有一些成本很低、速度很快的方法可以用来补足摄像头的短板。”同时举出了具体的例子，比如穿透雾气、穿透密集的雪或大雨，...</p>\n\n<a 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Scaringe在一场最新采访中解释了公司为什么在自动驾驶方案中使用激光雷达。他表示：“在构建模型的过程中、以及在摄像头真正变得显著更强之前，有一些成本很低、速度很快的方法可以用来补足摄像头的短板。”同时举出了具体的例子，比如穿透雾气、穿透密集的雪或大雨，都可以用雷达来解决，“而在极远距离、远远超过摄像头或人眼可见范围的探测上，我们也可以用激光雷达来解决——我们的激光雷达探测距离可达275米。”另外他还指出，拥有来自雷达和激光雷达的数据集还有一个好处：你可以更快地训练摄像头。他强调称，这里“训练”，并不是指手写代码去完成这些事情。“模型本身能够理解这些信息，当你把这些数据喂给系统时，由于这些不同传感器模态之间并不重叠、但各自有不同的优势和弱点，神经网络就能更好地判断：远处那个模糊的东西到底是一辆车、是一个人、还是建筑物反射出来的影像？”当同时拥有雷达和激光雷达的帮助时，摄像头在远距离看到的那个模糊目标，就可以更快地被“校准为真实情况”，他最后总结道。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"1","news_tag":"","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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为何不学特斯拉弃用激光雷达 Rivian：成本低 可补足摄像头短板

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为何不学特斯拉弃用激光雷达 Rivian：成本低可补足摄像头短板