Dynamic measures for transportation networks

Area of Science:

• Network Science
• Transportation Engineering
• Operations Research

Background:

• Current transportation network analyses often rely on simplified static representations.
• Static models neglect critical dynamic factors like travel times, waiting times, and schedule compatibility.
• This omission leads to a loss of relevant information and inaccurate network topology insights.

Purpose of the Study:

• To develop and apply a dynamic network representation for transportation systems.
• To incorporate travel and waiting times into shortest path calculations.
• To define and compare dynamic network measures against static ones for topological analysis.

Main Methods:

• Developed a dynamic network model considering synced paths and waiting times.
• Computed shortest paths using the dynamic model.
• Defined dynamic network, node, and edge measures for topological analysis.
• Validated the approach using a toy model and a real-world low-cost carrier schedule dataset.

Main Results:

• Significant discrepancies were observed between measures derived from static and dynamic network representations.
• Dynamic measures provide a more accurate topological analysis of transportation networks.
• The study highlights the limitations of static representations in capturing real-world transportation dynamics.

Conclusions:

• Dynamic network analysis offers a more accurate method for understanding transportation systems.
• Static representations are insufficient for capturing the complexities of real-world transportation networks.
• The proposed dynamic measures are valuable for a comprehensive topological assessment.