Smart sensors have become pervasive in railway transportation applications, particularly in Europe where digital technologies are increasingly being applied to the railway signaling field. In the future, safety-critical track-side train detection equipment, such as track circuits and axle counters, will be eliminated in favor of an accurate position estimate supplied by the train. However, the best approach to calculate an accurate position estimate remains an open research question, especially due to the high availability and reliability required. This article describes two static experiments performed with a global navigation satellite system (GNSS) module, which demonstrate that the real-world accuracy achievable with GNSS and real time kinematic (RTK) alone is not sufficient for safety critical applications, meaning further complementary sensors are required. Furthermore, a custom sensor node containing a GNSS module with RTK and an inertial measurement unit (IMU) has been used to acquire several data sets from an operating passenger train during dynamic tests on a railway line between Formigine and Modena, in Emilia-Romagna, Italy. These labeled GNSS and IMU data have been made freely available to the scientific community. The positioning accuracy of the GNSS and RTK measurements is evaluated, providing an in-depth study of the localization error and satellite coverage on the entire route. We demonstrate, with experimental evaluation, that centimeter accuracy (1.9 +/- 0.8) cm) is achievable under favorable static conditions, while accuracy can deteriorate to 8 m with RTK in urban scenarios with many reflections and poor sky view, worse than with GNSS alone. Under controlled conditions we show that shielding the GNSS receiver without RTK with a grounded metal plate causes a reduction in accuracy from 0.8 +/- 0.04 to 3.7 +/- 0.55 m in the least and most shielded case respectively. Our dynamic tests on a train show that although at least meter-level accuracy (1.08 +/- 1.3 m) is achievable with GNSS and RTK alone under dynamic conditions, a sensor fusion approach is necessary to accurately localize trains when GNSS conditions are poor or GNSS is unavailable.
Mikhaylov, D., Amatetti, C., Polonelli, T., Masina, E., Campana, R., Berszin, K., et al. (2023). Toward the Future Generation of Railway Localization Exploiting RTK and GNSS. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 72, 1-10 [10.1109/TIM.2023.3272048].
Toward the Future Generation of Railway Localization Exploiting RTK and GNSS
Amatetti, C;Polonelli, T;Campana, R;Vanelli-Coralli, A;Magno, M;Benini, L
2023
Abstract
Smart sensors have become pervasive in railway transportation applications, particularly in Europe where digital technologies are increasingly being applied to the railway signaling field. In the future, safety-critical track-side train detection equipment, such as track circuits and axle counters, will be eliminated in favor of an accurate position estimate supplied by the train. However, the best approach to calculate an accurate position estimate remains an open research question, especially due to the high availability and reliability required. This article describes two static experiments performed with a global navigation satellite system (GNSS) module, which demonstrate that the real-world accuracy achievable with GNSS and real time kinematic (RTK) alone is not sufficient for safety critical applications, meaning further complementary sensors are required. Furthermore, a custom sensor node containing a GNSS module with RTK and an inertial measurement unit (IMU) has been used to acquire several data sets from an operating passenger train during dynamic tests on a railway line between Formigine and Modena, in Emilia-Romagna, Italy. These labeled GNSS and IMU data have been made freely available to the scientific community. The positioning accuracy of the GNSS and RTK measurements is evaluated, providing an in-depth study of the localization error and satellite coverage on the entire route. We demonstrate, with experimental evaluation, that centimeter accuracy (1.9 +/- 0.8) cm) is achievable under favorable static conditions, while accuracy can deteriorate to 8 m with RTK in urban scenarios with many reflections and poor sky view, worse than with GNSS alone. Under controlled conditions we show that shielding the GNSS receiver without RTK with a grounded metal plate causes a reduction in accuracy from 0.8 +/- 0.04 to 3.7 +/- 0.55 m in the least and most shielded case respectively. Our dynamic tests on a train show that although at least meter-level accuracy (1.08 +/- 1.3 m) is achievable with GNSS and RTK alone under dynamic conditions, a sensor fusion approach is necessary to accurately localize trains when GNSS conditions are poor or GNSS is unavailable.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.