Collectively optimal routing for congested traffic limited by link capacity

Area of Science:

• Complex network theory
• Urban traffic systems
• Transportation engineering

Background:

• Urban street grids are complex networks susceptible to traffic congestion.
• Understanding traffic flow dynamics is crucial for efficient urban planning.
• Heterogeneity in link capacities and transport loads significantly impacts network performance.

Purpose of the Study:

• To optimize the traffic-supporting capacity of complex networks modeling city street grids.
• To investigate routing strategies that minimize congestion in heterogeneous networks.
• To identify methods for reducing overall traffic congestion and average travel times.

Main Methods:

• Modeling city street grids as complex networks.
• Analyzing networks with heterogeneous link capacities and transport loads.
• Developing routing strategies based on minimizing the ratio of betweenness to capacity for each link.

Main Results:

• A novel routing strategy was identified to optimize network capacity for congested traffic.
• The proposed strategy minimizes the maximum ratio of betweenness to capacity across all network links.
• Significant reductions in overall traffic congestion and average travel times were observed.
• Judicious utilization of slower, smaller-capacity links proved effective in congestion mitigation.

Conclusions:

• Optimized routing in complex networks can enhance the capacity to support congested traffic.
• Minimizing the betweenness-to-capacity ratio is a key strategy for efficient traffic flow.
• Strategic use of diverse link capacities offers a viable approach to reducing urban traffic congestion and improving travel times.