Adaptive Vehicle Platooning with Joint Network-Traffic Approach
Adaptive Vehicle Platooning with Joint Network-Traffic Approach
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DOI：
10.1109/globecom46510.2021.9685116
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发表时间：
2021-12
期刊：
影响因子：
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通讯作者：
Chinmay Mahabal;Hua Fang;Honggang Wang;Qing Yang
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文献类型：
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作者：
Chinmay Mahabal;Hua Fang;Honggang Wang;Qing Yang
智能交通系统已成为全球最热门的研究课题之一，互联和自动驾驶汽车（CAV）是其核心。通过研究不受实时交通和车辆网络损失影响的车辆队列，可以改进自动驾驶汽车的应用。在这项工作中，我们探讨了公路环境下网络模型和队列系统模型集成的必要性。提出的队列模型具有自适应的长度，提供节点车辆的合并和退出。这克服了所有排节点应该有一个共同的源和目的地的假设。高度模块化排设计解决了现有排模型存在的继电器选择、加速度阈值等问题。该算法优化了网络参数（如通信距离）和车辆动态参数（如速度和加速度阈值）之间的权衡。它考虑了SINR和链路稳定性等网络边界以及车辆在队列中的持续时间等车辆轨迹参数。这优化了流量吞吐量，同时保持稳定使用PID控制器。该工作试图在保持整体交通吞吐量的同时增加车辆在队列中的包含时间。
The Intelligent Transportation System has become one of the most globally researched topics, with Connected and Autonomous Vehicles(CAV) at its core. The CAV applications can be improved by the study of vehicle platooning immune to real-time traffic and vehicular network losses. In this work, we explore the need to integrate the Network model and Platooning system model for highway environments. The proposed platoon model is designed to be adaptive in length, providing the node vehicles to merge and exit. This overcomes the assumption that all the platoon nodes should have a common source and destination. The challenges of the existing platoon model, such as relay selection, acceleration threshold, are addressed for highly modular platoon design. The presented algorithm for merge and exit events optimizes the trade-off between network parameters such as communication range and vehicle dynamic parameters such as velocity and acceleration threshold. It considers the network bounds like SINR and link stability and vehicle trajectory parameters like the duration of the vehicle in the platoon. This optimizes the traffic throughput while maintaining stability using the PID controller. The work tries to increase the vehicle inclusion time in the platoon while preserving the overall traffic throuahput.