GNSS for rail automation & driverless cars: A give and take paradigm

Autor: Rispoli F., Enge P., Neri A., Senesi F., Ciaffi M., Razzano E.
Přispěvatelé: Institute of Navigation, Rispoli, F., Enge, P., Neri, A., Senesi, F., Ciaffi, M., Razzano, E.
Jazyk: angličtina
Rok vydání: 2018
Popis: GNSS positioning with high Integrity and accuracy attributes is a key application for implementing more efficient and safer automated train systems. The goal is an overall system concept and train equipment that is competent in high multipath environments, suitable for being integrated into the train safe platform ensuring at the same time economy on total cost of operations. Connected cars applications rely also on accurate and safe positioning and have in common with the trains the operational environment and a centralized command and control system. This paper introduce the give and take paradigm to liaise train control systems and autonomous cars stake holders and develop a common GNSS platform. The ambition is to export to the autonomous cars the safety capabilities of train control systems demonstrated during tens of years of operations, and to exploiting the large car’s market potential to lower the GNSS platform costs. The paper starts with the characteristics of the European Railways Train Management Systems (ERTMS) that guarantees the highest safety levels through a platform which is interoperable, standard and certifiable with harmonized procedures. Then we describe the plan to validate and certify the GNSS positioning applications into the ERTMS, which is one of the Game Changer technologies of the ERTMS evolution plan. The synergy with the connected cars is discussed by first introducing the virtual track concept to drive a car on the road as a train on the railways and then by developing the virtual horizon to safely monitor the way ahead detecting obstacles. The roadmap is driven by the ERSAT GGC (Galileo Game Changer) H2020 project, involving the rail community, and the EMERGE initiative, dealing with the automotive sector.
Databáze: OpenAIRE