Improving Vehicle Connectivity Through a Novel Self-Organizing Network Mechanism

Area of Science:

• Intelligent Transportation Systems (ITS)
• Automotive Engineering
• Network Communication

Background:

• The global Vehicle-to-Everything (V2X) market is expanding, necessitating advancements in V2X communication.
• Modern vehicles incorporate driver assistance and autonomous features, utilizing sensors like LiDAR for object detection and road safety.
• Existing Vehicle-to-Vehicle (V2V) communication requires enhancement for timely and accurate emergency message transmission.

Purpose of the Study:

• To propose a novel method for self-organization of vehicles in Intelligent Transportation Systems (ITS).
• To enhance the safety and reliability of vehicle networks through LiDAR-assisted grouping.
• To improve the efficiency of emergency message transmission in V2X communication.

Main Methods:

• Vehicles are organized into groups using LiDAR assistance for enhanced network safety.
• A comparison of data transmission strategies, specifically queuing data for an exponentially distributed random waiting time versus immediate transmission.
• Development of a self-organization method for vehicular networks.

Main Results:

• Grouping vehicles using LiDAR assistance was found to enhance vehicle network safety.
• Data transmission via queuing with an exponential random waiting time significantly outperforms immediate data transmission.
• The proposed method facilitates effective self-organization for vehicles in ITS.

Conclusions:

• The proposed self-organization method improves vehicular network safety and reliability.
• Implementing exponential random waiting times for data queuing is crucial for efficient emergency message delivery.
• Advancements in V2X communication, particularly V2V, are vital for the future of Intelligent Transportation Systems.