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Sensor data sharing in vehicular networks can significantly improve the rangeand accuracy of environmental perception for connected automated vehicles.Different concepts and schemes for dissemination and fusion of sensor data havebeen developed. It is common to these schemes that measurement errors of thesensors impair the perception quality and can result in road traffic accidents.Specifically, when the measurement error from the sensors (also referred asmeasurement noise) is unknown and time varying, the performance of the datafusion process is restricted, which represents a major challenge in thecalibration of sensors. In this paper, we consider sensor data sharing andfusion in a vehicular network with both, vehicle-to-infrastructure andvehicle-to-vehicle communication. We propose a method, named BidirectionalFeedback Noise Estimation (BiFNoE), in which an edge server collects and cachessensor measurement data from vehicles. The edge estimates the noise and thetargets alternately in double dynamic sliding time windows and enhances thedistributed cooperative environment sensing at each vehicle with lowcommunication costs. We evaluate the proposed algorithm and data disseminationstrategy in an application scenario by simulation and show that the perceptionaccuracy is on average improved by around 80 % with only 12 kbps uplink and 28kbps downlink bandwidth.

Edge-Aided Sensor Data Sharing in Vehicular Communication Networks