Main objectives of HELMET are:
1.To develop a cyber-secured multimodal, multi-sensor integrity monitoring architecture based on EGNSS to introduce High Integrity Location Determination System (LDS) for cars and trains automation aggregating the demand of monitoring rail and road assets with UAV, with the following properties:
o implementation of multi-frequency and multiple constellations solutions (i.e. at least GPS and Galileo) Signal In Space (SIS) integrity monitoring, including code pseudoranges, carrier phase and Doppler, together with EGNOS as well as its future evolution (to V3);
o exploitation of the high accuracy services and the authentication features provided by Galileo;
o full support of high on-board safe positioning and monitoring by sensor fusion and combination;
o standard authenticated interface for providing Authenticated High Integrity and High Accuracy services for multiple applications (i.e. rail, automotive, UAV for rail and road applications);
o full compliance with European requirements and regulations
2.To assess the system performance by a Proof-of-Concept (PoC), creating a liaison with EMERGE, the Italian project based on Galileo and 5G for the connected car, to exploit the urban test bed in the town of L’Aquila. The PoC will be realised by exploiting both real data collected in the field and synthetic data used to reproduce rare GNSS SIS (Signal-In- Space)
fault events, including satellite malfunctions, anomalous atmospheric behaviours and local faults affecting individual users, such as multipath, shadowing, intentional (i.e. jamming, spoofing and meaconing) and unintentional interferences occurring in the selected environment. Through this activity, the aim is to verify:
> the feasibility of the multi-modal AIMN primarily for railways and connected cars, previously described;
> the ability of this Augmentation Network to enable services provided by UAVs in support of rail and road services;
> the capability to detect and mitigate local effects on the OBU in order to provide integrity monitoring to the user.
3.To draw a roadmap for exploitation and future standardization and certification of HELMET results in terms of (a) the designed multi-modal AIMN architecture, and (b) high integrity and accuracy OBU algorithms fully customized for land transportation (rail and road). This will be carried out by exploiting the synergy between road and rail and taking into account the outcomes of the previous H2020 GSA projects, including RHINOS, ERSAT-EAV, STARS and ERSAT-GGC, where RDL and other partners have been involved. A strong relationship with the Italian project EMERGE, coordinated by RDL with FCA (Fiat Chrysler Automobiles), will be performed for derivation and harmonization of system requirements for connected and semiautonomous car applications. Moreover, the EMERGE test-bed will be used for HELMET proof-of-concept set-up and validation. Finally, a steering committee, involving different rail, road and UAV stakeholders, and associations (as the RTCM Committee, “Working Group-C on Next Generation GNSS”) will be created, since the project beginning, for the derivation of user needs, specific use cases and harmonization of functional, performance and RAMS (Reliability, Availability, Maintainability, and Safety) system specifications.
