Enhancing platoon performance: A novel approach to speed and direction control using V2X communication

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
A. Boubakri, Sonia Mettali Gammar
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引用次数: 0

Abstract

Autonomous vehicle platoons have become an increasingly popular solution to enhance driving system performance and facilitate the safe integration of these vehicles on the roads. To ensure efficient platoon traffic, it is essential to effectively manage both speed and direction within this group of vehicles. It is in this context that this research is situated. Our primary objective is to enhance the performance of speed and direction controllers, as the ability of vehicles to adjust these parameters in a coordinated manner is crucial for the success of platoon traffic. To achieve this, we have developed a novel speed control approach based on neural networks and fuzzy logic, utilizing V2X communication. By incorporating environmental parameters through vehicle-to-vehicle communication and considering the specific goals of the platoon, our neuro-fuzzy system can accurately calculate optimal speeds and directions for the vehicles. Our experiments have demonstrated the effectiveness of this approach compared to traditional and advanced methods, improving both energy efficiency and temporal coordination of autonomous vehicles within the platoon.
提高排级性能:利用 V2X 通信控制速度和方向的新方法
为提高驾驶系统性能并促进这些车辆在道路上的安全集成,自动驾驶车辆排成一排已成为一种日益流行的解决方案。为确保高效的排车交通,必须有效地管理这组车辆的速度和方向。本研究正是在这一背景下进行的。我们的主要目标是提高速度和方向控制器的性能,因为车辆以协调的方式调整这些参数的能力对于排状交通的成功至关重要。为此,我们利用 V2X 通信开发了一种基于神经网络和模糊逻辑的新型速度控制方法。通过车对车通信纳入环境参数,并考虑到车队的具体目标,我们的神经模糊系统可以准确计算出车辆的最佳速度和方向。我们的实验证明,与传统方法和先进方法相比,这种方法非常有效,既提高了能源效率,又改善了排内自动驾驶车辆的时间协调。
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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
22
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