Harmonization of NPRS Observations for a Seamless RTK Positioning Service in Automated Driving Applications

Rieck, Carsten; Jarlemark, Per; Nord, Stefan; Alissa, Samieh; Gunnarsson, Fredrik · 2021 · Crossref

DOI: 10.33012/2021.17887

archive: archived pipeline: cataloged verified

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Summary

The NPAD (Network-RTK Positioning for Automated Driving) project addresses the critical need for robust, centimeter-level absolute positioning for automated vehicles. While onboard sensors provide relative positioning, Global Navigation Satellite Systems (GNSS) are required for absolute location relative to maps and infrastructure. Existing Network-Real Time Kinematic (Network-RTK) solutions, designed for surveying and agriculture, suffer from scalability issues and long re-initialization times when devices move between reference station coverage areas. These limitations make them unsuitable for mass-market automated driving, which requires seamless handovers and efficient distribution to a large number of mobile clients. The project aimed to develop a scalable system for distributing Network-RTK correction data via cellular networks, leveraging 3GPP standards and existing Swedish GNSS infrastructure. The project was coordinated by RISE Research Institutes of Sweden and involved industrial partners including AB Volvo, Scania, Einride, Ericsson, and Lantmäteriet. The methodology involved six work packages: defining positioning requirements based on OEM use cases; designing and implementing a scalable correction data distribution system using a virtual network of reference stations; integrating navigation solutions into GNSS platforms; and developing test cases for validation. The team leveraged the existing Lantmäteriet/SWEPOS GNSS reference infrastructure to create a virtual reference station network. They implemented a prototype location server based on 3GPP Release 15 specifications to provision correction data via cellular networks (LTE/5G) using both unicast and broadcast modes. Testing was conducted at the AstaZero proving ground and along Highway 40 between Gothenburg and Borås, utilizing platforms such as the Einride Pod. The project successfully developed and demonstrated an efficient distribution system for Network-RTK correction data, enabling centimeter-level accuracy for a large number of simultaneous users. The implementation validated the technical solution, including seamless handovers between base stations and reference stations. The results confirmed that the proposed architecture could handle the scalability requirements of automated driving, overcoming the limitations of current NRTK procedures that struggle with high message loads and re-initialization delays. The project also established specific positioning requirements for automated driving, emphasizing integrity and the ability to relate position estimates to map data. The significance of this work lies in its contribution to the infrastructure necessary for widespread automated driving. By adapting existing public-sector GNSS infrastructure and integrating it with cellular network standards, the project provides a cost-effective and scalable solution for high-accuracy positioning. This enables not only automated vehicles but also other mobile platforms like drones and maritime vessels to benefit from reliable absolute positioning. The findings support the transition from niche, high-cost RTK applications to a mass-market service, facilitating coordinated mobility, sensor data sharing, and robust autonomous navigation systems.

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• lane positioning