Johns Hopkins AI工具使用交通、天气和行为数据预测碰撞事故,以帮助减少事故。 Johns Hopkins AI tool predicts crashes using traffic, weather, and behavior data to help reduce accidents.

约翰·霍普金斯工程师开发了一个AI工具,名为“安全交通联合驾驶员”,通过分析交通模式、天气、道路设计和驾驶行为来预测车祸。 Johns Hopkins engineers have developed an AI tool called SafeTraffic Copilot that predicts car crashes by analyzing traffic patterns, weather, road design, and driver behavior. 该系统利用基因人工智能和来自66 000多起事故的数据,帮助决策者评估调整交通信号时间等变化如何降低坠机率。 Using generative AI and data from over 66,000 accidents, the system helps policymakers evaluate how changes like adjusting traffic signal timing could reduce crash rates. 其目的是在包括摩托车使用率高的地区在内的不同环境中改善道路安全,并旨在支持城市规划中以数据为驱动的决策。 It aims to improve road safety in diverse environments, including areas with high motorcycle use, and is designed to support data-driven decisions in urban planning. 该研究于2025年10月在《自然通信》中发表。 The research was published in Nature Communications in October 2025.