Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Optimized Control-Centric Communication in Cooperative Adaptive Cruise Control Systems

Mahdi Razzaghpour, Shahriar Shahram, Rodolfo Valiente, Mahdi Zaman, Yaser P. Fallah

TL;DR

The paper tackles the challenge of scalable cooperative driving in dense traffic by rethinking V2X communications for CACC. It introduces a control-aware ETC framework integrated with Model-Based Communication, supported by Gaussian Process predictions, to curb communication while preserving platoon stability and safety. Through simulations on a 10-vehicle platoon, the approach achieves a 47% reduction in transmissions with negligible effect on control performance, even under substantial packet losses. The findings suggest a practical path toward robust, scalable cooperative driving in future dense traffic networks.

Abstract

In this study, we explore an innovative approach to enhance cooperative driving in vehicle platooning systems through the use of vehicle-to-everything (V2X) communication technologies. As Connected and Autonomous Vehicles (CAVs) integrate into increasingly dense traffic networks, the challenge of efficiently managing communication resources becomes crucial. Our focus is on optimizing communication strategies to support the growing network of interconnected vehicles without compromising traffic safety and efficiency. We introduce a novel control-aware communication framework designed to reduce communication overhead while maintaining essential performance standards in vehicle platoons. This method pivots from traditional periodic communication to more adaptable aperiodic or event-triggered schemes. Additionally, we integrate Model-Based Communication (MBC) to enhance vehicle perception under suboptimal communication conditions. By merging control-aware communication with MBC, our approach effectively controls vehicle platoons, striking a balance between communication resource conservation and control performance. The results show a marked decrease in communication frequency by 47\%, with minimal impact on control accuracy, such as less than 1\% variation in speed. Extensive simulations validate the effectiveness of our combined approach in managing communication and control in vehicle platoons, offering a promising solution for future cooperative driving systems.

Optimized Control-Centric Communication in Cooperative Adaptive Cruise Control Systems

TL;DR

The paper tackles the challenge of scalable cooperative driving in dense traffic by rethinking V2X communications for CACC. It introduces a control-aware ETC framework integrated with Model-Based Communication, supported by Gaussian Process predictions, to curb communication while preserving platoon stability and safety. Through simulations on a 10-vehicle platoon, the approach achieves a 47% reduction in transmissions with negligible effect on control performance, even under substantial packet losses. The findings suggest a practical path toward robust, scalable cooperative driving in future dense traffic networks.

Abstract

In this study, we explore an innovative approach to enhance cooperative driving in vehicle platooning systems through the use of vehicle-to-everything (V2X) communication technologies. As Connected and Autonomous Vehicles (CAVs) integrate into increasingly dense traffic networks, the challenge of efficiently managing communication resources becomes crucial. Our focus is on optimizing communication strategies to support the growing network of interconnected vehicles without compromising traffic safety and efficiency. We introduce a novel control-aware communication framework designed to reduce communication overhead while maintaining essential performance standards in vehicle platoons. This method pivots from traditional periodic communication to more adaptable aperiodic or event-triggered schemes. Additionally, we integrate Model-Based Communication (MBC) to enhance vehicle perception under suboptimal communication conditions. By merging control-aware communication with MBC, our approach effectively controls vehicle platoons, striking a balance between communication resource conservation and control performance. The results show a marked decrease in communication frequency by 47\%, with minimal impact on control accuracy, such as less than 1\% variation in speed. Extensive simulations validate the effectiveness of our combined approach in managing communication and control in vehicle platoons, offering a promising solution for future cooperative driving systems.
Paper Structure (14 sections, 14 equations, 5 figures, 2 tables)

This paper contains 14 sections, 14 equations, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Cooperative Adaptive Cruise Control (CACC)
  4. Vehicle-to-Vehicle (V2V) Communication
  5. Optimizing MAS Communication with Event-Triggered Strategies
  6. Model-Based Communication (MBC)
  7. Preliminaries and Problem Formulation
  8. Vehicle Model and Predictive Control Design
  9. The Role of Event-Triggered Conditions
  10. Control-aware Triggering
  11. Experimental Results
  12. Implementation Aspects
  13. Analysis and Results
  14. Conclusion

Figures (5)

  • Figure 1: An explanation of the communication structure used by vehicles is presented, where dashed lines represent the exchange of information between them. The term $d_i$ is used to describe the gap between the $n^{th}$ vehicle and the one directly in front of it.
  • Figure 2: Functioning of CACC system using TTC with a PER of 0, and a constant communication rate at 10 Hz.
  • Figure 3: Functioning of the CACC system using control-aware triggered ETC, with a PER of 0, a threshold at level 6, and an average communication frequency set at 5.28 Hz.
  • Figure 4: Functioning of the CACC system with TTC, with a PER of 0.6, and a constant communication rate at 10 Hz.
  • Figure 5: Functioning of the CACC system using control-aware triggered ETC, with a PER of 0.6, a threshold at level 6, and an average communication frequency set at 5.28 Hz.