Control Subarea Division for Coordinated Signal Control: A Colored Random Walk and Path Entropy Approach to...

Area of Science:

• Intelligent Transportation Systems
• Traffic Engineering
• Network Science

Background:

• Coordinated signal control relies on effective control subarea division.
• Existing methods struggle with dynamic traffic loading and state propagation.
• Accurate division is crucial for optimizing traffic flow and reducing delays.

Purpose of the Study:

• To propose a novel control subarea division method.
• To explicitly model traffic-state propagation using advanced techniques.
• To improve upon existing methods for dynamic traffic conditions.

Main Methods:

• Integrated state-guided colored random walk and path entropy analysis.
• Constructed random walk process using intersection correlation and traffic state.
• Identified subareas by minimizing path response distribution discrepancy.
• Utilized five metrics: spatial delay variance reduction, delay reduction, congestion mitigation, stop reduction, and queue reduction.
• Validated using a VISSIM microsimulation model with dynamic traffic loading.

Main Results:

• The proposed method outperformed Whitson and Fast Newman methods across all five metrics.
• Achieved 41.47% variance reduction of spatial delay.
• Secured 23.77% delay reduction rate.
• Demonstrated 25.96% congestion mitigation index.
• Showcased 23.59% stop reduction rate.
• Attained 15.08% queue reduction rate.

Conclusions:

• The proposed method effectively models traffic-state propagation for improved control subarea division.
• It enhances spatial balance and network efficiency in dynamic traffic environments.
• The method successfully mitigates bottlenecks, reduces stops, and suppresses queue accumulation.