The Cooperative Driving dataset (CODD) is a synthetic dataset generated using CARLA that contains lidar data from multiple vehicles navigating simultaneously through a diverse set of driving scenarios. This dataset was created to enable further research in multi-agent perception (cooperative perception) including cooperative 3D object detection, cooperative object tracking, multi-agent SLAM and point cloud registration. Towards that goal, all the frames have been labelled with ground-truth sensor pose and 3D object bounding boxes. The data structure is described in the README.md file. More information on how to use and visualise the dataset is available in the github repository: https://github.com/eduardohenriquearnold/CODD