Reflection loss-based roadway water depth measurement for driver safety

Abstract

Flood fatalities generally occur in flood-prone areas such as low water bridges and tunnels, and most are vehiclerelated. The existing water depth measurement solutions are neither cost-efficient nor suitable for roadway scenarios. This paper proposes two water depth measurement methods that can be integrated into cellular networks. The proposed methods reuse the periodic communication signals of 5G and 6G to avoid allocating dedicated sensing signals and conflicting with the communication requirements. The main idea of these methods is based on the fact that the Reflection Loss (RL) induced by a water surface exhibits a strong dependence on the water depth. The peak counting method measures the water depth by counting the successive RL peaks separated by a constant spacing. The RL fingerprinting method integrates the RL peak positions and the measured RL values to determine the water depth. Several factors affecting the water depth measurement resolution are also analyzed. The simulation results show that the measurable water depth range of the proposed methods is larger than the water depth that may pose danger to vehicles, indicating that the proposed methods are feasible for roadway scenarios.