Parallel Intelligent Systems for Integrated High-Speed Railway Operation Control and Dynamic Scheduling

Area of Science:

• Intelligent Systems
• Railway Engineering
• Operations Research

Background:

• A significant information exchange gap exists between operation control and dynamic scheduling in high-speed railway systems (HRSs).
• This gap impedes the integrative improvement and overall efficiency of HRSs.

Purpose of the Study:

• To explore a feasible solution for bridging the information exchange gap in HRSs.
• To enhance the efficiency of HRSs through integrated operation control and dynamic scheduling.

Main Methods:

• The study analyzes and constructs parallel intelligent systems using the ACP approach (Artificial systems, Computational experiments, Parallel execution).
• Experiments are conducted on typical HRS scenarios using the developed parallel intelligent systems.

Main Results:

• The developed parallel intelligent systems provide powerful tools for studying current HRS operations.
• Effective control and management strategies for actual HRSs are achieved through experimental validation.

Conclusions:

• The proposed parallel intelligent systems offer a viable solution to bridge the information exchange gap in HRSs.
• These systems facilitate further research and development in integrated operation control and dynamic scheduling for HRSs.