Fortune | FORTUNE 21小时前
Waymo experimenting with generative AI, but exec says LiDAR and radar sensors important to self-driving safety ‘under all conditions’
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Waymo公司在其自动驾驶出租车服务中,尽管也在探索生成式AI等新技术,但仍将激光雷达(LiDAR)和雷达视为大规模运营的最安全方式。公司副总裁Srikanth Thirumalai强调,相比仅依赖摄像头的系统,LiDAR和雷达提供了“额外的安全网”,确保在包括极端天气在内的所有条件下都能获得足够数据来做出驾驶决策。Waymo已通过超过1亿英里的无人驾驶里程验证了其多传感器融合方法的有效性,并展示了LiDAR在识别潜在危险方面的优势。尽管Waymo也在研究多模态AI模型,但目前仍认为传统传感器是实现大规模安全自动驾驶的关键。

🛡️ Waymo坚守多传感器融合策略:公司副总裁Srikanth Thirumalai重申,在规模化自动驾驶出租车服务中,激光雷达(LiDAR)和雷达是保障安全的关键,能提供比仅依赖摄像头的系统更强的“安全网”,尤其是在应对复杂和极端天气条件下。

🚗 实际案例佐证LiDAR优势:Waymo展示了LiDAR传感器在摄像头未能捕捉到行人意图(如准备穿越马路)或车辆(如绕行停靠巴士)的情况下,成功识别并规避风险的案例,凸显了其在提升安全性方面的实际价值。

📊 安全记录与规模化验证:Waymo已累计超过1亿英里的无人驾驶里程,并已扩展到五个城市,这证明了其以LiDAR和雷达为基础的自动驾驶技术在实际应用中的可靠性和可扩展性。公司将自身安全记录视为衡量自动驾驶系统有效性的重要客观指标。

💡 AI技术探索与融合:Waymo并未停止技术创新,正在积极研究将Gemini等生成式AI和多模态模型(如EMMA)整合到其技术栈中,以期提升目标检测和道路理解能力,但同时也承认这些AI模型在成本、处理能力和传感器融合方面仍面临挑战,尚未能独立支撑大规模安全驾驶。

🆚 对比其他厂商的差异化:文章对比了Waymo与特斯拉在自动驾驶传感器策略上的根本差异,特斯拉主张“LiDAR是愚蠢的”,仅使用摄像头,而Waymo则认为这种做法在规模化应用中存在潜在风险,并对摄像头单一方案的安全性持保留态度。

Waymo is experimenting with generative AI and other technologies for its self-driving cars, but the company believes the assortment of laser sensors and radars mounted on its cars remains the safest way to run a robotaxi service at scale—at least for now.

“We’ve done a lot of research. We’re aware of what works and what doesn’t work at our scale and what we need to do,” Srikanth Thirumalai, who is vice president of onboard engineering for the current robotaxi industry incumbent, Waymo, said this week at the Ai4 Conference in Las Vegas. 

While rivals like Tesla are pushing self-driving cars that rely solely on video cameras, Waymo’s Thirumalai says the combination of LiDAR and radar provides “an additional safety net” to make sure that the company has the adequate data it needs to make driving decisions “under all conditions”—including extreme weather.

Thirumalai was speaking on stage in an interview with Fortune. Earlier that day, Thirumalai gave a solo presentation, describing Waymo’s AI stack and approach to safety in detail that has allowed the company to scale its operation to five cities by mid-2025 and conduct more than 100 million driverless miles. In his presentation, Thirumalai showed a video of how LiDAR sensors on the Waymo Jaguar I-PACE had picked up movement from human beings readying to jump in the road, even when the vehicle’s cameras had not—or a woman preparing to go around a stopped bus and directly into the path of a Waymo robotaxi. In both instances, Waymo’s robotaxi stopped or maneuvered out of the way to avoid contact with the pedestrians, according to the videos.

The presentation showed the stark contrast in approaches between Waymo and one of its newer rivals, Tesla, which launched a small-scale, invite-only robotaxi service in Austin this June, with safety drivers in the passenger seat. Tesla, which was demonstrating its full self-driving (FSD) technology via demo rides at the Ai4 Conference, is only using video cameras and its AI technology for FSD and Tesla Robotaxi, after years of Elon Musk stating that other sensors are expensive and unnecessary. “LiDAR is a fool’s errand,” Elon Musk said in 2019. “Anyone relying on LiDAR is doomed. Doomed! [They are] expensive sensors that are unnecessary.”

Thirumalai wouldn’t say directly whether he considered camera-only self-driving systems like Tesla’s to be safe for the public roads. He said that you have to consider “the whole process” of how a system is built, tested, then validated, and he also said that you cannot statistically compare Waymo’s system to another, because of the lack of comparable safety metrics. General Motors’ subsidiary Cruise, which also used LiDAR and radar systems, suspended operations earlier this year after it failed to relaunch after a serious accident in San Francisco. For context, Tesla said it had driven 7,000 driverless miles at the end of July, compared to Waymo’s 100 million.

“If we are talking about objective measures, then we have to look at the statistics of our safety record, at scale, right?” Thirumalai said. “When someone actually says: Yes, we matched your safety at your scale with a different system, that’s great. We’ll take that.” 

Waymo is regularly testing new technology as it becomes available, according to Thirumalai. As part of that experimentation, he said that Waymo has researched how multimodal models like Gemini can be incorporated into the Waymo tech stack (Waymo has not tested any other generative AI models besides Google’s Gemini, Thirumalai confirmed). The robotaxi company has published several papers of its research into multimodal models, including a city-scale traffic simulation with a generative world model as well as Waymo’s research around EMMA, Waymo’s End-to-end Multimodal Model for Autonomous driving. Waymo has reported that co-training its vehicles with EMMA helped with things like object detection and road graphs, saying there was “potential” for EMMA as a generalist model for autonomous driving applications. However, EMMA is expensive, can only process a small number of image frames, and does not incorporate LiDAR sensors or radar—all of which lead to “challenges” for using EMMA as a “standalone model for driving”

Thirumalai said incorporating generative AI models into the self-driving tech stack is an area of “intense research,” and that he believes this will continue. “But there’s a lot more work that’s going to be needed to make the system as simple as possible,” he said.

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Waymo 自动驾驶 LiDAR AI 安全
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