Special Session Ⅴ
Advanced Multi-Objective Optimization and Distributed Cooperative Control in Intelligent Transportation Networks
(智能轨道、交通与运输工程的多目标优化和协同控制关键技术及应用)
Chair: | Co-chair: |
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Cong Jin | Ming Yan |
Communication University of China, China | Communication University of China, China |
Keywords: | Topics: |
· Intelligent Transportation Systems (智能交通系统) · Transportation Planning (交通规划) · Autonomous Vehicles (自动驾驶) · Railway Transportation (铁路运输) · Wireless Sensor Networks (无线传感器网络) · Multi-Objective Optimization (多目标优化) · Cooperative Control of Multi-Agent (多智能体协同控制) | · Intelligent Equipment and Technology for Rail Transit (轨道运输装备与关键技术) · Railway–Air–Maritime Transportation (铁路—空—海联运) · Transportation Planning (交通规划) · Highway Transportation (公路运输) · Multi-Objective Optimization (多目标优化) · Graph Neural Networks (图神经网络) · Unmanned Systems (无人系统) · Multi-Agent Cooperation (多智能体协同) |
Summary:
· This research focuses on multi-objective collaborative optimization and control technologies in intelligent rail transit and transportation systems. By integrating multi-objective decision-making algorithms (e.g., dynamic Pareto optimization) and distributed collaborative control architectures (e.g., multi-agent-based resource scheduling), it addresses multidimensional optimization challenges spanning transport efficiency, energy consumption management, safety, and service quality. The work drives engineering applications in scenarios such as intelligent train scheduling and urban traffic network management, with key breakthroughs in real-time decision-making in dynamic environments and interoperable control of heterogeneous systems.
· 该研究聚焦于智能轨道交通与运输系统中的多目标协同优化与控制技术，通过集成多目标决策算法（如动态Pareto优化）和分布式协同控制架构（如基于多智能体的资源调度），解决运输效率、能耗管理、安全性与服务质量等多维度协同优化问题，并推动其在智能列车调度、城市交通网络管理等场景的工程化应用。核心突破包括动态环境下的实时决策与异构系统的互操作控制。
Submission Deadline: 2025.7.30