Cooperative Simultaneous Localization and Mapping (C-SLAM) is an active research topic in mobile robotics. However, its application in the field of autonomous driving is rare. While the advent of Vehicle-to-Everything (V2X) communication has empowered Connected Autonomous Vehicles (CAV) to exchange data with each other, recent research on CAV cooperation tasks has primarily focused on cooperative perception and global positioning improvement. Techniques for organizing multiple CAV to work together to achieve localization and mapping in unknown environments have not been actively explored. We propose a C-SLAM system for CAVs that employs sparse LiDAR feature representations to enable vehicles to exchange data using standard V2X messages. The system was tested in real environments using two connected vehicles. The results show that the proposed V2X-based C-SLAM system can operate in both centralized and decentralized manners and output accurate pose estimates and global maps, showing promising application possibilities.