Data-Driven and Intelligent Multimodal Transportation: Next-Generation Systems and Applications
数据驱动与智能多模式交通：下一代系统与应用
| Chair: | Co-chair: |
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Zhengli Wang | Zhenjie Zheng |
Nanjing University, China | The Hong Kong Polytechnic University, China |
Keywords: | Topics: |
· Multimodal Transportation (多模式交通) · Data-Driven (数据驱动) · Intelligent (智能化) · Next-Generation (系统与应用) | · Methods for Fusion and Preprocessing of Heterogeneous Traffic Data (多源异构交通数据融合与预处理方法) · Big Data-Based Prediction of Multimodal Traffic Flow (基于大数据的多模式交通流量预测) · Spatiotemporal Dynamic Modeling of Transportation Demand (交通需求时空动态建模) · Collaborative Optimization of Multimodal Transport Networks (多模式交通网络协同优化) · Integration of Autonomous Driving with Multimodal Transport (自动驾驶与多模式交通的融合) · Intelligent Signal Control and Coordinated Management of Multimodal Traffic Flows (Adaptive Traffic Light Optimization) (智能信号控制与多模式交通流协同管理) |
Summary:
· This session focuses on data-driven and intelligent technologies empowering multimodal transportation systems, exploring cutting-edge theories and innovative applications for next-generation transport. It covers topics such as intelligent scheduling, cross-modal coordination, and data mining, aiming to advance multimodal transportation towards higher efficiency, intelligence, and sustainability.
· 本专题聚焦数据驱动与智能技术赋能的多模式交通系统，探索下一代交通系统的前沿理论与创新应用，涵盖智能调度、跨方式协同、数据挖掘等方向，旨在推动多模式交通向高效化、智能化与可持续方向发展。
Submission Deadline: 2025/10/20