福建师范大学学报（自然科学版）2025，Vol.41Issue(1)：11-20,10.DOI:10.12046/j.issn.1000-5277.2024050069
面向分布式数据安全共享的高速公路路网拥堵监测
Research on Expressway Network Congestion Monitoring for Secure Sharing of Distributed Data
摘要
Abstract
The application of artificial intelligence(AI)technology for monitoring the condi-tion of expressway networks has become a prominent research area.However,challenges such as data silos and privacy protection hinder intelligent decision-making in this domain.To address these issues and enable secure sharing of distributed data for intelligent decision-making,particularly with regard to congestion,a strategy based on federated learning is proposed.This strategy employs real-time camera data and utilizes a fully homomorphic encryption scheme within the federated learning framework.This enables the establishment of an encrypted,intelligent decision-making architecture to develop a congestion status monitoring model based on optimized road segments.The results indicate that,while ensuring the security and privacy of distributed data,this approach can effec-tively monitor expressway congestion.关键词
高速公路路网/道路拥堵状态/数据安全共享/智能决策/联邦学习/同态加密Key words
expressway network/road congestion status/secure data sharing/intelligent deci-sion-making/federated learning/homomorphic encryption分类
计算机与自动化引用本文复制引用
李林锋,陈羽中,姚毅楠,邵伟杰..面向分布式数据安全共享的高速公路路网拥堵监测[J].福建师范大学学报（自然科学版）,2025,41(1):11-20,10.基金项目
国家自然科学基金项目(62471142) （62471142）
福建省高校产学合作项目(2024H6006) （2024H6006）
福建高速集团十四五发展规划智慧出行重点科研攻关项目(2022Y121) （2022Y121）
