Serial Data Parsing for High-Fidelity GNSS Integration in ETSI C-ITS Vehicular Networks

This thesis presents the design, implementation, and validation of a robust, open-source approach to Cooperative Intelligent Transport Systems (C-ITS), with special emphasis on integrating Global Navigation Satellite System (GNSS) data from Real Time Kinematics (RTK) receivers. By leveraging hardware such as the ArduSimple RTK2B board in conjunction with the u-blox ZED-F9R module, the system captures high-fidelity positioning information, indispensable for safety-critical and efficiency-driven vehicular applications. The framework centers on the OScar (Open Stack for Car) project, an ongoing C++ implementation of the ETSI C-ITS standards, designed to expedite adoption and reduce costs through open-source distribution. A key focus is the development of a serial data parser for UBX and NMEA protocols, which processes the incoming GNSS messages and encapsulates them into the V2X C-ITS Services such as the Cooperative Awareness Basic Service (CABS) and the Vulnerable Road Users Awareness Basic Service (VBS). By strictly adhering to the layered structure of C-ITS comprising the Application, Facility, Network/Transport, Access, and supplementary Management and Security layers, OScar ensures modular, interoperable message handling. Field experiments and simulations verify the parser’s performance as well as the real-time feasibility of populating CAM structures with accurate position, speed, and heading data. In turn, these messages enable low-latency hazard detection, traffic flow optimization, and advanced driver-assistance features. Through comparative performance testing against existing tools like GPSD, the thesis also underscores the advantages of high-frequency updates in safety scenarios. By merging open-source flexibility, established communication standards, and centimeter-level positioning precision, this work demonstrates how the OScar framework can serve as a cost-effective, future-ready solution for C-ITS deployments. The resulting software stack sets a significant milestone toward widespread vehicular connectivity, paving the way for enhanced road safety and coordinated transport ecosystems.