Li Bin: NIO's intelligent assisted driving system, based on a world model architecture and closed-loop reinforcement learning, has been deployed in over 950,000 intelligent electric vehicles
The Block
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At the 2026 World Intelligent Connected Vehicles Conference, Li Bin stated that NIO's intelligent assisted driving system, based on a world model architecture and closed-loop reinforcement learning, has been deployed on over 950,000 intelligent electric vehicles. The safe driving mileage has exceeded 9.14 billion kilometers, with a cumulative usage time of 112 million hours. He also mentioned that according to internal data and data from four insurance companies, the safety losses from accidents involving these vehicles have been decreasing year by year, with a reduction of more than 30%.
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IT Home, October 21st news: At the 2026 World Intelligent Connected Vehicles Conference, NIO's founder, chairman, and CEO Li Bin shared a set of the latest data:

As of now, NIO's intelligent assisted driving system, which is based on a world model architecture combined with closed-loop reinforcement learning, has been deployed in over 950,000 intelligent electric vehicles. The total safe driving distance covered by this system exceeds 9.14 billion kilometers, with a cumulative usage time of 112 million hours, preventing or mitigating the impact of 9.07 million potential accidents for users. According to internal data, the average safe driving distance achieved with human and vehicle collaboration is eight times that of driving solely by humans. Data from four insurance companies also support this, showing that for vehicles equipped with NIO's intelligent assisted driving system, accident-related safety losses have been decreasing year by year, with a reduction of over 30%.

As reported earlier today by IT, during a dialogue session at the 2026 World Intelligent Connected Vehicles Conference, Li Bin proposed that as autonomous driving enters its “second half,” the criteria for measuring its value need to return to two verifiable indicators.

Li Bin summarized these two indicators as: whether users are willing to pay for autonomous driving features, and whether autonomous driving can make users significantly perceive it as safer than driving by humans. He stated bluntly that if users are not willing to pay, no matter how well autonomous driving is described, it does not truly create value for users.

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