Fuzzy Traffic Control with Vehicle-to-Everything Communication

Area of Science:

• Intelligent Transportation Systems
• Computational Intelligence
• Traffic Engineering

Background:

• Vehicle-to-everything (V2X) communication offers efficient traffic signal control (TSC) but faces challenges due to low penetration rates.
• Existing V2X-based TSC systems require supplementary mechanisms to function effectively under low V2X adoption.

Purpose of the Study:

• To propose and evaluate novel methodologies for traffic signal control that are effective even with low V2X penetration rates.
• To investigate the application of simple and fuzzy logic in V2X-enabled traffic signal control.

Main Methods:

• Developed two new methodologies using simple and fuzzy logic within the COLOMBO framework.
• Compared the performance of the proposed methods against the existing COLOMBO approach.
• Evaluated TSC quality considering both intersection-wide and directional performance.

Main Results:

• The proposed simple and fuzzy logic methods demonstrate effective traffic signal control performance.
• The study suggests that TSC can be addressed as a logical problem rather than solely an optimization problem.
• The methods show promise for realistic scenarios, even with low vehicle-to-everything (V2X) penetration rates.

Conclusions:

• New simple and fuzzy logic approaches offer viable solutions for traffic signal control under low V2X penetration.
• The findings support the treatment of traffic signal control as a logical problem.
• The proposed methods are suitable for future research and implementation in real-world traffic scenarios.