GNSS Technology for Precise Positioning in CCAM: A Comparative Evaluation of Services

Abstract

Cooperative, connected, and automated mobility (CCAM) can lead to a significantly improved transport system by increasing safety and efficiency, and reducing emissions. To achieve the goal of fully automated mobility and self-driving vehicles, accurate and reliable positioning is essential. Positioning methods in CCAM often use sensor fusion combining data from multiple sensors with Global navigation satellite system (GNSS) positioning data. In this paper, we focus on the status of GNSS technology by investigating position accuracies and integrities of different state-of-the-art GNSS technologies. We conduct field tests using a self-driving vehicle in Drammen, Norway. Three different types of GNSS positioning services are explored, and a reference trajectory delivered by the vehicle's navigation system is used to determine the performance of each service. We show that the performance of the GNSS methods alone does not fulfill the requirements needed to obtain fully automated mobility. Moreover, we observe a general decreasing trend in GNSS accuracy for more challenging surroundings.

Ground Deformation Monitoring for Subway Structure Safety Based on GNSS

“…The rapid development and highly Integrated application of satellite positioning, computers, wireless communication, and data management technologies provide reliable technical support for solving the problem of real-time, continuous, all-weather settlement monitoring. Among these technologies, satellite positioning based on big data technology has high-precision, automation, all-weather operation, a high data collection frequency, high reliability, and wide application area characteristics [5,6], making it superior to other means of meeting safety supervision requirements. These properties make it ideal for overcoming the previously mentioned engineering observation problems.…”