Fuzzy logic-based intersection management for delay minimization in intelligent transportation systems using V2X communication

Advancement and standardization of technologies are having a significant impact on the intelligent transportation system. However, traffic delays continue to be a major concern due to the in-quantifiable effect it has directly on traffic participants and indirectly on other aspects of life such as the economy and emergency services. This thesis proposed a fuzzy logic-based approach for intersection management using V2X communication and synchronization with regular traffic light systems to minimize vehicular traffic delays. The fuzzy logic model accepts queue length, waiting time, speed, and distance as input and output phase duration for the intersection schedule. Traffic simulation under varying vehicular flow rates was performed to validate the performance of the proposed approach in isolated and multiple intersection coordination involving HPVs and NPVs. In isolated intersections, the proposed approach achieved 33.15% and 16.18% better delay minimization compared to static and a recently proposed approach [1] respectively. It also achieved 17.82% and 12.16% in terms of throughput improvement. A paired sample t-test shows that the proposed approach achieved a statistically significant difference in delay minimization and throughput improvement than the static/fixed-time controllers. Extension of the approach to network-wide traffic management with special consideration for high-priority vehicles also shows similar results in terms of delay and throughput. It achieved 57.75% for HPVs and 35.68% for high-priority vehicles and non-priority vehicles in terms of delay minimization compared to the standard preemptive approach.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

Fuzzy logic, Intelligent transportation system, Connected and autonomous vehicles, Fuzzy inference system, Intersection management

Year dc:date.issued

2024

Author dc:creator

• Zachariah, Babangida

Advisor dc:contributor.advisor

• Elgazzar, Khalid

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/1909

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/1909