VANET中的联合路由与控制优化
Joint Routing and Control Optimization in VANET
AI总结：
提出DynaRoute联合优化框架，结合轨迹感知路由、实时轨迹预测与安全约束车队协同，在动态VANET中同时保障车队稳定、数据传输和自适应路由性能。
摘要：
本文提出DynaRoute，这是一种面向动态车辆网络的自适应联合优化框架，通过轨迹感知路由和安全约束的车辆协同，同时解决车队控制与数据传输问题。DynaRoute借助车队安全控制保证车辆持续运动，同时通过实时轨迹预测优化传输路径并确保数据可靠。该方案实现三个关键目标：（1）通过准确的数据传输维持车队稳定性；（2）基于车辆运动模式实现自适应路由；（3）提升智能交通系统的整体性能。DynaRoute需要预定义交通模型，并利用本地车辆状态信息适应动态网络条件。我们给出了全面的仿真结果，表明DynaRoute在多种复杂场景下能够保持控制与传输性能，并且与传统方法相比显著提高了吞吐量和可靠性。
英文摘要：
In this paper, we introduce DynaRoute, an adaptive joint optimization framework for dynamic vehicular networks that simultaneously addresses platoon control and data transmission through trajectory-aware routing and safety-constrained vehicle coordination. DynaRoute guarantees continuous vehicle movement via platoon safety control with optimizing transmission paths through real-time trajectory prediction and ensuring reliable data. Our solution achieves three key objectives: (1) maintaining platoon stability through accurate data transmission, (2) enabling adaptive routing based on vehicle movement patterns, and (3) enhancing overall intelligent transportation system performance. DynaRoute equires predefined traffic models and adapts to dynamic network conditions using local vehicle state information. We present comprehensive simulation results demonstrating that DynaRoute maintains control and transmission performance in multiple complex scenarios while significantly improving throughput and reliability compared to traditional approaches.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
