论文标题
V2X场景的车道合并协调模型
A Lane Merge Coordination Model for a V2X Scenario
论文作者
论文摘要
使用连接服务的合作驾驶一直是自动驾驶汽车的有希望的途径，第五代移动网络（5G）提供了低潜伏期和进一步的可靠性支持。在本文中，我们介绍了基于集中式系统的车道合并协调的申请，用于连接的汽车。该应用程序向道路上的连接车辆提供了轨迹建议。该应用程序包括流量编排作为主要组件。我们应用机器学习和数据分析，以预测连接的车辆是否可以成功完成车道合并的合作操作。此外，完成了安全合并所需的加速度和标题参数。结果证明了几种现有算法的性能以及如何选择其主要参数以避免过度拟合。
Cooperative driving using connectivity services has been a promising avenue for autonomous vehicles, with the low latency and further reliability support provided by 5th Generation Mobile Network (5G). In this paper, we present an application for lane merge coordination based on a centralised system, for connected cars. This application delivers trajectory recommendations to the connected vehicles on the road. The application comprises of a Traffic Orchestrator as the main component. We apply machine learning and data analysis to predict whether a connected vehicle can successfully complete the cooperative manoeuvre of a lane merge. Furthermore, the acceleration and heading parameters that are necessary for the completion of a safe merge are elaborated. The results demonstrate the performance of several existing algorithms and how their main parameters were selected to avoid over-fitting.
