In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., obtaining an accurate estimate of the positions and trajectories of connected vehicles in a certain area. State-of-the-art solutions are based on the periodic broadcasting of the position information of the network nodes, with an inter-transmission period set by a congestion control scheme. However, the movements and maneuvers of vehicles can often be erratic, making transmitted data inaccurate or downright misleading. To address this problem, we propose to adopt a dynamic transmission scheme based on the actual positioning error, sending new data when the estimate overcomes a preset error threshold. Furthermore, the proposed method adapts the error threshold to the operational context according to an innovative congestion control algorithm that limits the collision probability among broadcast packet transmissions. This threshold-based strategy can reduce the network load by avoiding the transmission of redundant messages, and is shown to improve the overall positioning accuracy by more than 20% in realistic urban scenarios.

中文翻译：

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一种用于车载网络中高效动态映射的自适应广播策略

在这项工作中，我们面临着在车联网场景中实现高效动态映射的问题，即获得特定区域内联网车辆的位置和轨迹的准确估计。最先进的解决方案基于网络节点位置信息的周期性广播，并具有由拥塞控制方案设置的传输间期。然而，车辆的运动和操纵往往不稳定，导致传输的数据不准确或完全具有误导性。为了解决这个问题，我们建议采用基于实际定位误差的动态传输方案，当估计超过预设误差阈值时发送新数据。此外，所提出的方法根据限制广播数据包传输之间的冲突概率的创新拥塞控制算法使错误阈值适应操作上下文。这种基于阈值的策略可以通过避免冗余消息的传输来减少网络负载，并且在现实的城市场景中可以将整体定位精度提高 20% 以上。