Communicability geometry captures traffic flows in cities

Area of Science:

• Complex systems analysis
• Network science
• Urban mobility studies

Background:

• Understanding network flow dynamics is crucial for complex systems.
• Identifying item routes within networks remains a significant challenge.
• Urban vehicular traffic provides real-world data for network flow models.

Purpose of the Study:

• To investigate vehicular traffic flow patterns in urban networks.
• To compare flow distribution between shortest paths and communicability shortest paths.
• To explore the theoretical underpinnings of traffic route selection.

Main Methods:

• Utilized observational data from four cities of varying characteristics.
• Applied a coarse-grained theory of network traffic flow.
• Derived a communicability function incorporating vehicular propagation speed.

Main Results:

• Observed higher vehicular traffic flow on communicability shortest paths compared to traditional shortest paths.
• Evidence supports an 'all-routes' flow model over simple shortest-path routing.
• Traffic flow patterns were consistent across diverse urban environments.

Conclusions:

• Communicability shortest paths better represent actual traffic flow than conventional shortest paths.
• Drivers' route choices are influenced by perceptions of congestion, leading to 'all-routes' flow.
• Findings enhance the understanding of complex network dynamics and urban mobility.