A Performance Study of Mobility Speed Effects on Vehicle Following Control via V2V MIMO Communications

Area of Science:

• Intelligent Transportation Systems (ITS)
• Autonomous Vehicle Technology
• Wireless Communication Systems

Background:

• Vehicle-to-vehicle (V2V) communications are crucial for advancing intelligent transportation systems (ITS), enhancing driving safety, optimizing traffic flow, and enabling autonomous vehicle development.
• The performance of V2V communication channels, environmental conditions, traffic patterns, and vehicle speeds critically influence the precision of autonomous vehicle control systems.

Purpose of the Study:

• To propose a versatile system-level framework for investigating, experimenting with, and verifying V2V communication impacts on autonomous vehicle control.
• To analyze the effects of varying mobility speeds and communication channel types on V2V communication quality and subsequent vehicle control.

Main Methods:

• Development of a system-level framework to model vehicle functionality, communication channels, and driving scenarios.
• Experimental setup involving a leader vehicle at 36 km/h in a high-building environment performing a lane change, with a follower vehicle's speed varying from 40 km/h to 80 km/h.
• Measurement of communication link quality for both single-input and single-output (SISO) and multiple-input and multiple-output (MIMO) systems under different speed differentials.

Main Results:

• Single-input and single-output (SISO) communication demonstrated lower efficiency compared to multiple-input and multiple-output (MIMO) communication.
• A speed difference of 4 km/h (leader at 36 km/h, follower at 40 km/h) resulted in SISO link quality below 0.85, leading to unstable follower vehicle control.
• Increasing follower vehicle speed to 80 km/h improved SISO link quality to approximately 0.95 due to reduced inter-vehicle distance, enhancing control stability.
• Multiple-input and multiple-output (MIMO) communication effectively mitigated the negative impacts of SISO communication, offering superior performance and enabling correct follower vehicle decision-making.

Conclusions:

• MIMO communication techniques and optimal signal selection are vital for overcoming the limitations of SISO communication in V2V systems.
• Enhanced communication quality, particularly through MIMO, directly translates to more reliable and stable autonomous vehicle control, even under challenging speed differentials and environments.
• The developed framework provides a valuable tool for accelerating research and development in V2V communication for autonomous driving applications.