Game Theory-Based Signal Control Considering Both Pedestrians and Vehicles in Connected Environment

Area of Science:

• Traffic Engineering
• Transportation Science
• Game Theory Applications

Background:

• Traffic signal control is crucial for efficient traffic management and pollution reduction.
• Existing game theory research often overlooks pedestrian needs at intersections.
• Pedestrians are significant participants influencing intersection dynamics.

Purpose of the Study:

• To develop a game theory-based signal control approach considering both vehicles and pedestrians.
• To minimize and equalize queued vehicles and pedestrians across traffic phases.
• To optimize green light duration using the Nash bargaining solution.

Main Methods:

• Utilizing game theory and the Nash bargaining solution for signal phase optimization.
• Implementing a fixed cycle length with optimized green durations.
• Conducting simulations using SUMO software to evaluate the approach.
• Comparing the proposed strategy against the actuated signal control baseline.

Main Results:

• Reduced pedestrian and vehicle delay.
• Decreased vehicle queue lengths, fuel consumption, and CO2 emissions.
• More equitable queue length distribution across lanes compared to actuated control.
• Demonstrated superiority and stability over the baseline approach under various demand scenarios.

Conclusions:

• The proposed game theory approach effectively balances vehicle and pedestrian needs.
• The strategy enhances traffic efficiency, reduces environmental impact, and promotes fairness.
• This method offers a more comprehensive and equitable solution for intelligent traffic signal control.