“智慧大脑”保道路运营

Core Viewpoint - The first digital warning system for highway operation safety in snowy environments has been officially launched in China, providing a smart solution for winter road safety management [1][2]. Group 1: System Overview - The platform was developed by a team from Harbin Institute of Technology in collaboration with Heilongjiang Provincial Transportation Investment Group, focusing on the urgent need for highway operation and maintenance under severe weather conditions [1]. - The system integrates five core technologies: multi-source perception of road surface snow and ice, assessment of anti-skid performance, analysis of driving safety on icy roads, risk warning for snowy roads, and advanced prediction of road surface conditions [1]. Group 2: Technological Features - The platform utilizes a high-precision sensor matrix and an anti-skid performance database to digitize and visualize all road elements [2]. - It employs big data analysis and AI algorithms to accurately identify potential risks, providing multi-channel risk alerts to traffic participants through SMS and pop-up notifications [2]. Group 3: Operational Efficiency - The system features a multi-level warning mechanism that dynamically adjusts speed limits based on warning levels and feeds back results to sensing terminals, creating a complete loop of monitoring, warning, response, and feedback [2]. - This innovation effectively addresses road blockages caused by snowfall and enhances overall traffic emergency management efficiency [2]. Group 4: Future Implications - The key technologies of the platform have been included in the Ministry of Transport's compilation on disaster monitoring and emergency response for highway infrastructure, supporting the successful hosting of the 2025 Asian Winter Games in Harbin [2]. - As data expands and algorithms improve, the platform is expected to further enhance the intelligence level of China's transportation infrastructure, ensuring safe operation and maintenance during adverse weather conditions [2].