On the GNSS Augmentation Services for the ERTMS Train Control and Connected Car Applications: Technical Synergies and Opportunities
Francesco Rispoli, Alessia Vennarini, Alessandro Vizzarri, Radiolabs; Roberto Capua, Sogei; and Alessandro Neri, Roma TRE University, and Radiolabs
Date/Time: Thursday, Sep. 22, 11:26 a.m.
Rail and Road transport systems are evolving to progressively introduce automation with the ultimate goal of autonomous driving. Both are characterised by the need to guarantee a high level of safety to mitigate/avoid driver’s behaviour and also by adopting standardizable solutions when new technologies, external to their traditional ecosystem, are introduced. Concerning rail, the ERTMS (European Railways Train Management System) is already a standard solution largely adopted worldwide, the only one able to guarantee the highest safety level ever reached on land transports (SIL 4 – implying a Tolerable Hazard Rate of 10E-9/hour related to the maximum allowed speed and stopping position). The ERTMS is now in the process to adopt GNSS for the train positioning function, having accumulated almost 10 years of field experimentations in Italy driven by RFI – the Italian railways infrastructure manager who has a plan to deploy the ERTMS on the whole Italian railways network.
On the road side, connected car is being introduced as a means to automate cars with appropriate quality of service level when the management of vehicles is supported by a centralised authority as in the ERTMS system. Both ERTMS and Connected Car applications rely on the knowledge of the vehicle’s position with similar integrity levels. Considering also that the operational environment is practically the same, a common approach in providing augmentation services has attracted, during the last years, the research managed by the authors, and presented for the first time at the ION GNSS Conference in 2018, . Since then two specific projects were launched: HELMET funded by EUSPA and EMERGE a strategic initiative of the Italian Ministry of Economical Development that is coordinated with STELLANTIS’s projects.
Looking forward, we can expect that the requirements concerning the vehicle location determination systems will become more and more stringent with the increase of automation. In rail, the driver will be the increase of traffic density and possibly the average train speed. To take full advantage of dynamic rail traffic management, the separation between convoys should by under control of the radio block center. Today, the main impediment is represented by the static partition of a line into blocks of predefined length. In fact, each block can by occupied at the same time by one train only. Since detection of the presence of a train occupying a given block is performed by a track circuit, switching to the concept of a moving block surrounding a train, foreseen by ERTM Level 3, requires a new technology that can virtualize the current physical track circuits, in a manner similar to the way the virtual balises are replacing the physical ones. Thus, while in ERTMS Level2 determination of the track on which the train is operating is a function activated in a few specific cases, whenever track circuits are removed the train location determination system has to continuously provide such an information. It means, that in case of positioning provided by a GNSS receiver alone the standard deviation of the Gaussian Overbounding Distribution of the across track error should be of order of decimeters. Thus, while for the implementation of the ERTMS Level2, processing of dual frequency, multiconstellation code pseudoranges with SBAS augmentation data could be sufficient, support of moving block could impose adoption of position techniques based on carrier phase processing, like RTK or PPP. This, in turn, implies that carrier phase integrity monitoring has to be accomplished. Nevertheless, the main impact will not be on the receiver side but on the augmentation and integrity monitoring side. In fact, this approach will ask for a denser set of monitoring reference stations.
Concerning automotive, the current trend of switching over from traffic flow control to vehicle control will ask for an increase in the degree of cooperation among vehicles and smart roads. This implies that, in addition to position, velocity and acceleration accurate timing will be needed. This process may be accelerated by the recent crisis in freight transport experimented by UK due to shortage of foreign drivers. In fact, extensive use of platooning where one driver at time takes care of several vehicles may mitigate the scarcity of drivers, in addition to the reduction of fuel consumption.
While at the present, perception sensors are used to compile the current scenario, eventually integrated with the electronic horizon, consisting of the dynamics of the other vehicles in the proximity and to plan the actions to avoid collisions while following a selected route, in a cooperative environment where each vehicle is under control of a remote control node, each vehicle has to accurately follow the assigned path, with the imposed speed, in a timing way. Therefore, vehicles, will be driverless but not autonomous anymore, at least in a strict sense. This fact may drastically change the role of GNSS in the vehicle control system. On the other hand, services like robo-taxy must operate even with no one on board, although remote supervision and manual overriding in case of problems is possible.
Among land and maritime transport systems, the rail sector has been the first to investigate and then to adopt the use of GNSS for safety critical applications. Concerning Europe, it is a subject of formal definition by the European Union Agency for Railways (ERA) and will be included in the next ERTMS STI CCS. Very recently, RFI, the Italian rail infrastructure manager, after the successful experimentations carried out in the recent H2020 ERSAT GGC, has released the specifications document for the procurement of ERTMS/ETCS Level 2 signaling system incorporating satellite technologies. In Australia and in China rail lines adopting signaling systems making use of GNSS for train localization, similar to the ERTMS, are already operational. In U.S.A. GPS technologies have been incorporated into several types of Positive Train Control (PTC) systems.
Due to the small capacity of the radio-link between the train and the Radio Block Center adopted by ERTMS, only the Differential GNSS receiver mode and EGNOS OS aided mode are currently supported. On the other hand, with the coming into service of the Future Rail Mobile Communications System standard this limitation will be overcome, and more accurate solutions like RTK and PPP will become applicable. In the meanwhile, hybridization with IMUs has been widely experimented.
Concerning roads, the technological progress in the automotive sector led to the development of electronic driver support systems. These systems have been developed during the last years to reduce road accidents caused by the human errors, to reduce pollutions, to transport mobility-impaired people, and to reduce driving related stress. Target levels of accuracy and integrity are at least two orders of magnitude more challenging than those achieved in aviation.
We remark that, to put a vehicle in a fail-safe mode, despite their specific aspects, rail and road traffic management systems require the knowledge of both vehicle dynamics and confidence intervals. This information is vital for the on-board computer to determine the braking curve for avoiding collisions with adjacent vehicles and persons or things in the vicinity of the vehicle. The smaller the confidence interval is, the smaller becomes the safety buffer around current and predicted vehicle locations, and denser the traffic the system is able to manage in a safe way. Therefore, High Accuracy and High Integrity are of paramount importance to increase traffic capacity on the lanes and also on the railways.
Concerning the integrity, several approaches have been proposed starting from the Receiver Autonomous Integrity Monitoring algorithms developed for avionics applications. Their main limitation is the effectiveness in handling multiple SIS faults, as those caused by multipath characterizing the harsh environments in which the vehicles may operate. To overcome this limitation, a set of solutions have been proposed under the umbrella of ARAIM (Advanced Receiver Autonomous Integrity Monitoring), originally developed for avionics. The usage of the GNSS location estimates in planning and decision making requires decimeter or even centimeter accuracy and asks for reliable RTK/PPP/SSR services with integrity guaranteed. Particularly, the SRR (State Space Representation) foresees that a reference station network models the key errors over a wide geographical area. These corrections are then sent to the rover who uses these received data to model the GNSS errors. The achievable performance depends on which error models are transmitted to the user.
Thus, to achieve performance supporting tomorrow rail and road applications, we propose an approach based on the integration of different augmentation systems to realize a multi-modal, multi-service augmentation network rather than on the building a dedicated augmentation network which is much more expensive. The rationale for a multimodal augmentation system is simply to:
• Provide a general augmentation solution tailored to high integrity and high accuracy applications operating in the same environment, with the ability to provide differentiated services on demand, possibly switching among them upon request.
• Exploit the potential of the new GNSS features not available on current SBAS systems.
• Utilize as far as possible the existing SBAS infrastructures.
• Provide a liability mechanism through a service level agreement with the train and road infrastructure managers respectively.
That network should be public and operated by a service provider.
Since the SBAS systems currently in operation (WAAS in USA and EGNOS in Europe) monitor just a subset of the GNSS SISs, we have studied a two-tiers augmentation architecture for the multimodal traffic management. This two-tiers augmentation architecture is based on the integration of a SBAS like EGNOS (1rst tier) and a local system (2nd tier). This approach extends the two-tiers augmentation architecture verified and tested in the framework of H2020 ERSAT EAV and RHINOS Projects, in the rail context, . With such an architecture, the Augmentation Control Centre, can apply the SBAS corrections and integrate Local Reference Stations to the SBAS RIMS (Reference Integrity and Monitoring Stations) measurements, in order to derive the integrity status of the system as a whole system (Local Reference Stations and GNSS signals). On top of the SBAS and Local networks there are two adaptation layers optimized for the rail and the automotive applications, respectively.
The satellite and constellation fault detection are performed by the 1rst tier through the SBAS system RIMS. Relevant measurements can be therefore used as a reference for a further level of monitoring (e.g., the 2nd tier). The 2nd tier, through local Reference Stations, is in charge of applying SBAS corrections and improving the local and global fault detection performances, through single and double difference with the first layer. Through the above integration, the 2nd tier is able to monitor the healthiness of the RS network. Within such framework, the second network can be based on COTS receiver, leading to a low-cost densification of the 1st layer. In principle, existing RS network, can be used for implementing the 2nd tier.
Such Multimodal 2-tiers augmentation architecture has been tested for real-time operations within the ERSAT EAV and RHINOS projects, through an upgrade of the operational Italian RTK/NRTK GRDNet-GNSS R&D Network. Due to the recent manufacturer’s developments of low-cost receivers, such networks can be further densified, leading to new paradigms for single error precise estimations and broadcasting to the user and for this reason proper research activities are on-going. In the GRDNet, the real-time integrity monitoring has been implemented through an adaptation layer transmitting to the GNSS receiver on board of the train an RTCM like message derived from the well-known high precision standard that includes an integrity mask containing the relevant flags reporting the health status of each satellite in view. SIS and Reference Station Fault Detection and Exclusion (FDE) is essentially based on the monitoring of the Differential Pseudorange Residuals (DPR), the Double Phase Difference Residuals (DPDR), and the Double Difference Residuals (DDR) of the pseudoranges measured by both the Reference Stations of the 2nd tier and those of the 1st tier.
On the other hand, local hazards cannot be mitigated by the provision of traditional augmentation networks due to the fast decay of their spatial correlation. Thus, to mitigate their impact we introduced the local hazard source maps  that complement the other Augmentation data, made available to the GNSS receivers operating on board of the vehicle. Thus, the 2nd tier provides to the vehicle both the augmentation data related to global and local hazards, including the information needed to compute the related contributions to the Protection Levels. The local hazard source maps will have to be created during the surveys performed when building and updating the transportation infrastructures databases.
The economical sustainability of the proposed multimodal augmentation architecture needs to be evaluated in detail. One strong argument in favor of this solution is the economy of scale due to the synergy between train control systems and connected cars applications. This synergy can generate a demand for GNSS services at least two orders of magnitude higher that of any other safety critical application stand-alone. Furthermore, the costs for implementing and operating this infrastructure are much lower than those of dedicated networks and can be sustained by the investments to deploy the ERTMS on the regional railway lines and the smart roads. On top of that, the greatest benefit will be an increase of safety and transport capacity reducing the need to build new infrastructures. For the railways a priority is to “extract” additional capacity from the existing rail infrastructure to allow trains to travel closer to each other and for the roads to drastically reduce the accidents.
The designed Augmentation Subsystem is able to serve different applications in a multi-modal framework. The Augmentation Network, based on a Network of Reference Stations providing real-time raw measurements to the Control Centre, is compliant to RTCM SC-104 and will comply with the RTCM SC-134 as soon as it will be released (some of the authors are members of RTCM SC-134).
Our Paper will be organised in 6 sections. Section 1 will Introduce the key requirements in terms of integrity of the ERTMS and Connected Car applications. Section 2 will discuss the state of the art of possible architectures and relevant implementation aspects. Section 3 will address the specific topic of standardization and roadmap. Section 4 will be devoted to the design of the AU-Network and of the Proof of Concept. Section 5 will report results from the test campaigns. Section 6 will be dedicated to the technical and economical sustainability making reference to the Rail And Connected applications underway in Italy.
 F. Rispoli, P. Enge, A. Neri, F. Senesi, M. Ciaffi, E. Razzano, "GNSS for Rail Automation & Driverless Cars: A Give and Take Paradigm," Proceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 1468-1482. https://doi.org/10.33012/2018.16053
 C. Stallo, A. Neri, P. Salvatori, R. Capua and F. Rispoli, "GNSS Integrity Monitoring for Rail Applications: 2-tiers method," in IEEE Transactions on Aerospace and Electronic Systems, vol. 55, no. 4, pp. 1850-1863, Aug. 2019. doi: 10.1109/TAES.2018.2876735.
 A. Neri, R. Capua, A. Filip, A. Ruggeri, S. Baldoni, "Integrity Bounds for Rail and Road Applications Based on Local Hazard Maps," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 4157-4169. https://doi.org/10.33012/2021.18079
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