An Adaptive Broadcasting Strategy for Efficient Dynamic Mapping in Vehicular Networks

TL;DR

This paper introduces an adaptive broadcasting strategy for vehicular networks that dynamically adjusts transmission based on positioning error and congestion, significantly improving mapping accuracy and reducing network load.

Contribution

It proposes a novel error-threshold-based transmission scheme combined with congestion control, enhancing dynamic mapping accuracy in vehicular networks.

Findings

Positioning accuracy improved by over 20% in urban scenarios

Reduces network load by avoiding redundant messages

Adapts transmission based on real-time error and congestion levels

Abstract

In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., to obtain 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 passes a preset error threshold. Furthermore, the proposed method adapts the error threshold to the operational context according to a 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.