  Inter-vehicle communication for autonomous vehicles (AVs) stands to provide
significant benefits in terms of perception robustness. We propose a novel
approach for AVs to communicate perceptual observations, tempered by trust
modelling of peers providing reports. Based on the accuracy of reported object
detections as verified locally, communicated messages can be fused to augment
perception performance beyond line of sight and at great distance from the ego
vehicle. Also presented is a new synthetic dataset which can be used to test
cooperative perception. The TruPercept dataset includes unreliable and
malicious behaviour scenarios to experiment with some challenges cooperative
perception introduces. The TruPercept runtime and evaluation framework allows
modular component replacement to facilitate ablation studies as well as the
creation of new trust scenarios we are able to show.
