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As autonomous vehicles become more popular, some researchers remain worried about potential safety issues.
隨著自動駕駛汽車越來越受歡迎，一些研究人員仍然擔心潛在的安全問題。
Digital Trends reports researchers from Massachusetts Institute of Technology (MIT) have been looking at the differences between autonomous systems learning in training and real world issues.
麻省理工學院的研究人員一直在研究自主系統在訓練與現實問題之間的差異。
A model by MIT and Microsoft researchers is testing what the cars will do when the training they have "learned" doesn't match what is happening on the road.
麻省理工學院和微軟研究人員制作的模型正在測試：當汽車“學到"的訓練與實際道路情況不匹配時，汽車會發(fā)生什么情況。
Author of the paper Ramya Ramakrishnan said in a statement.
論文作者Ramya Ramakrishnan表示：
"Many times, when these systems are deployed, their trained simulations don't match the real-world setting [and] they could make mistakes, such as getting into accidents."
“很多時候，當系統部署之后，模擬訓練與現實環(huán)境不匹配時，汽車可能會出錯，比如發(fā)生事故。”
譯文屬可可英語原創(chuàng)，未經允許，不得轉載。
