An Interest-Based Approach for Reducing Network Contentions in Vehicular Transportation Systems

Area of Science:

• Computer Science
• Transportation Engineering
• Network Engineering

Background:

• Traffic management systems (TMS) are crucial for addressing urban mobility challenges.
• 5G and vehicular networking technologies are poised to enhance TMS for smarter, safer, and faster transportation.
• Existing infrastructure-based TMS face challenges like low delivery ratios and high latency in dense smart city environments due to network congestion.

Purpose of the Study:

• To propose an interest-based approach, I am not interested in it (IAN3I), to mitigate network contention and reduce reliance on infrastructure in TMS.
• To enable fully-distributed traffic management and opportunistic content sharing within vehicular networks.
• To improve the efficiency and reliability of traffic information dissemination in smart cities.

Main Methods:

• Developed IAN3I, an interest-based vehicular traffic management system.
• Vehicles opportunistically store and share traffic information based on recipient interest.
• Simulated IAN3I in a realistic scenario to evaluate its performance against state-of-the-art approaches.

Main Results:

• IAN3I significantly reduced transmitted messages by up to 95%.
• Packet collisions were decreased by up to 98%.
• Latency was reduced by up to 55% without compromising traffic management performance.

Conclusions:

• IAN3I effectively reduces network contention and infrastructure dependence in traffic management systems.
• The interest-based, distributed approach enhances vehicular network efficiency and reliability.
• IAN3I offers a promising solution for smart city transportation challenges.