IT Operations Automation · Real-time Analytics
Jingxiong Expressway operators struggled with rigid workflows, fragmented data and systems, weak video perception, and slow emergency handling, which limited the precision and responsiveness of highway operations management.
Reported impact
The branch created a model-driven operations layer that improved monitoring accuracy, sped up emergency and information workflows, reduced manual operating effort, and made multi-party highway coordination more intelligent.
Hebei Expressway Group's Jingxiong Expressway branch used Baidu AI Cloud to build a highway-operations large model on top of Qianfan ModelBuilder and Qianfan AppBuilder. Baidu pre-trained the model with expressway operating data and tuned it for four specialized domains: event detection, emergency response, information handling, and business interaction. Those capabilities are exposed through seven scenario applications that act as a 'digital operations expert' able to combine perception, cognition, and decision support. The deployment uses professional-terminology understanding, knowledge enhancement, and content generation to detect road events around the clock, generate reports automatically, coordinate multi-party information, and support voice-driven cross-system commands that can reach data, functions, and APIs directly.
Operational road data is used to pre-train the highway model, which then ingests live event signals and user requests from highway business systems. The model analyzes conditions, drafts response plans or reports, and issues voice-driven commands across systems, data stores, and APIs to coordinate monitoring, emergency action, and information release.
Baidu built the highway industry large model on general large-model capabilities and pre-trained it on expressway operating data (original: 在百度通用大模型能力基础上，基于高速公路运行数据进行预训练，打造高速行业大模型).
Initial estimates show 80%+ business-system efficiency gains, 95%+ event-detection accuracy, and 80%+ improvements in emergency response and information release (original: 初步测算，业务系统效率提升80%以上，事件检测准确率提升至95%以上，应急处置效率和信息发布效率提升80%以上).
It supports voice-driven cross-system, cross-function, cross-data, and cross-API access for queries, knowledge-base calls, information collaboration, report generation, and command issuing (original: 通过语音语义指令就可以实现跨系统直达、跨功能直达、跨数据直达和跨API的打通).
The case describes the industry's first scenario large model for expressway operations management on Jingxiong Expressway in Hebei (original: 行业首个面向高速公路运营管理的场景大模型).
The solution forms four specialized models and seven innovative applications for event detection, emergency disposal, information handling, and business interaction (original: 形成面向事件检测、应急处置、信息处置、业务交互四类专属模型和七项创新应用).
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