Periodic Reporting for period 1 - RAILGAP (RAILway Ground truth and digital mAP)
Período documentado: 2021-01-01 hasta 2022-06-30
Novel signalling systems are expected to use Digital Maps to implement Automatic Train Operation (ATO) functions or to augment technologies such as European Global Navigation Satellite Systems (EGNSS), inertial sensors or optical sensors for localization purposes. However, the construction of a Digital Map with current technologies requires expensive railway surveying campaigns. Additionally, the cost for their maintenance and update is a major challenge that prevents its adoption. With regard to the design of Digital Maps and trackside signalling subsystems, they are based on the knowledge of two types of data: (a) the longitudinal positions of Points Of Interests (POIs) (e.g. light signals, ETCS markers) with respect to the track centreline and (b) the grades or slopes of the track segments adjacent to them. Therefore, as a first step, such designs require the acquisition or the verification of the data related to POIs (i.e. nominal values of locations and gradients along with their related accuracies) and this causes extra costs and time-consuming surveying activities leading to delays in the commissioning of the lines.
With regard to the evolution of Control-Command and Signalling (CCS) systems, a new verification infrastructure is also needed to characterize new on-board solutions in terms of train position, speed and acceleration errors, as well as to assess their expected performance. The performance analysis of signalling systems is in most of previous work analysed with project dependent mechanisms and procedures Unfortunately, there is no agreed methodology for building “reference ground truth data” in railway applications. Up to now, the investigated Ground Truth methodology has required the use of the track database and the availability of absolute and relative reference measurement systems associated with the lines for which the Ground Truth had to be built. Moreover, these methodologies also suffer of other two limitations, i.e. they provide (a) “reference ground truth data” for the train position only and (b) no information about the accuracy of the provided “reference ground truth data”.
The RAILGAP project aims to develop a methodology and related toolset for building and maintaining Digital Maps based on the post-processing of data recorded by trains in commercial service, equipped with Commercial Off The Shelf (COTS) sensors like GNSS receivers, cameras, Inertial Measurement Units (IMUs), and LIDARs. On the other side, a similar approach and development can be used to provide “high precision and high accuracy ground truth reference data” as true values for carrying out error and performance analysis. The RAILGAP project has three main objectives. The first one is the development of an innovative Ground Truth methodology and related toolset that overcome the above described constraints and limitations; they are based on the post-processing of recorded measurement data and provide reference ground truth data and related accuracies for different types of physical entities such as position, velocity, acceleration, and attitude. This Ground Truth does not require (a) installation of trackside equipment or modifications to existing trackside signalling subsystems and (b) a-priori knowledge of track databases. The second objective is to perform field surveys by using measured physical entities collected with trains during commercial services for building and maintaining Digital Maps. The third one is the use of Artificial Intelligence (AI) techniques to off-line process big amount of collected data to allow the extraction of the information required for building and maintaining Digital Maps. The RAILGAP measurement system used for both methodologies is composed of COTS sensors like GNSS antenna and receivers, cameras, IMUs, and LIDARs.
With regard to the evolution of Control-Command and Signalling (CCS) systems, a new verification infrastructure is also needed to characterize new on-board solutions in terms of train position, speed and acceleration errors, as well as to assess their expected performance. The performance analysis of signalling systems is in most of previous work analysed with project dependent mechanisms and procedures Unfortunately, there is no agreed methodology for building “reference ground truth data” in railway applications. Up to now, the investigated Ground Truth methodology has required the use of the track database and the availability of absolute and relative reference measurement systems associated with the lines for which the Ground Truth had to be built. Moreover, these methodologies also suffer of other two limitations, i.e. they provide (a) “reference ground truth data” for the train position only and (b) no information about the accuracy of the provided “reference ground truth data”.
The RAILGAP project aims to develop a methodology and related toolset for building and maintaining Digital Maps based on the post-processing of data recorded by trains in commercial service, equipped with Commercial Off The Shelf (COTS) sensors like GNSS receivers, cameras, Inertial Measurement Units (IMUs), and LIDARs. On the other side, a similar approach and development can be used to provide “high precision and high accuracy ground truth reference data” as true values for carrying out error and performance analysis. The RAILGAP project has three main objectives. The first one is the development of an innovative Ground Truth methodology and related toolset that overcome the above described constraints and limitations; they are based on the post-processing of recorded measurement data and provide reference ground truth data and related accuracies for different types of physical entities such as position, velocity, acceleration, and attitude. This Ground Truth does not require (a) installation of trackside equipment or modifications to existing trackside signalling subsystems and (b) a-priori knowledge of track databases. The second objective is to perform field surveys by using measured physical entities collected with trains during commercial services for building and maintaining Digital Maps. The third one is the use of Artificial Intelligence (AI) techniques to off-line process big amount of collected data to allow the extraction of the information required for building and maintaining Digital Maps. The RAILGAP measurement system used for both methodologies is composed of COTS sensors like GNSS antenna and receivers, cameras, IMUs, and LIDARs.
During the first 18 months of the project, the user requirement understanding phase related to the Ground Truth and the Digital Map were executed. The main reached results were:
- Identification and description of the user needs related to Digital Map and Ground Truth from different user perspectives, e.g. IMs, RUs, Signalling Suppliers, Research Organizations and Railway Interoperability Laboratories.
- Transformation of the identified User Needs into Functional and Not-Functional User Requirements of the RAILGAP Infrastructure.
- Identification and description of the Constraints and the Obligations coming from the applicable Railways Directives, Regulations, and Standards on the use of new technologies (e.g. visual camera images vs the obligations on privacy) and on the new mitigations required to cope with new hazards associated with their use.
The identified User Needs and the requirements are described in the public deliverable D2.1 “User Requirements Document related to Digital Map and Reference Measurement Values & Procedures”.
In addition, the following main activities were also executed:
- State of the Art of the proposed technologies COTS Hardware such as, for example, EGNSS, IMU, LIDAR, and Camera in the context of railway applications or other severe industrial environments with focus on the achievable performance and robustness;
- Specification of the information to be measured for each type of the selected technology and to be characterized in the railway environment;
- Identification of the measurement equipment;
- Specification and development of the measurement procedures for collecting the different types of measurements from EGNSS, IMUs, LIDARs, Cameras;
- Preliminary characterization of the technologies used in RAILGAP aimed at addressing error models, fault detection methods and sensor fusion solutions for different sensor technologies in railway environments.
The preliminary results are reported in the public deliverable D4.1 “Sensor Error Models in Railway Environment”.
The project website at the link https://railgap.eu/) contains (a) general information about the structure, objectives and progress of the RAILGAP project, (b) links to some intermediate results and to public deliverables, (c) publishable summaries of confidential deliverables, and (d) dissemination material such the project brochure and videos.
- Identification and description of the user needs related to Digital Map and Ground Truth from different user perspectives, e.g. IMs, RUs, Signalling Suppliers, Research Organizations and Railway Interoperability Laboratories.
- Transformation of the identified User Needs into Functional and Not-Functional User Requirements of the RAILGAP Infrastructure.
- Identification and description of the Constraints and the Obligations coming from the applicable Railways Directives, Regulations, and Standards on the use of new technologies (e.g. visual camera images vs the obligations on privacy) and on the new mitigations required to cope with new hazards associated with their use.
The identified User Needs and the requirements are described in the public deliverable D2.1 “User Requirements Document related to Digital Map and Reference Measurement Values & Procedures”.
In addition, the following main activities were also executed:
- State of the Art of the proposed technologies COTS Hardware such as, for example, EGNSS, IMU, LIDAR, and Camera in the context of railway applications or other severe industrial environments with focus on the achievable performance and robustness;
- Specification of the information to be measured for each type of the selected technology and to be characterized in the railway environment;
- Identification of the measurement equipment;
- Specification and development of the measurement procedures for collecting the different types of measurements from EGNSS, IMUs, LIDARs, Cameras;
- Preliminary characterization of the technologies used in RAILGAP aimed at addressing error models, fault detection methods and sensor fusion solutions for different sensor technologies in railway environments.
The preliminary results are reported in the public deliverable D4.1 “Sensor Error Models in Railway Environment”.
The project website at the link https://railgap.eu/) contains (a) general information about the structure, objectives and progress of the RAILGAP project, (b) links to some intermediate results and to public deliverables, (c) publishable summaries of confidential deliverables, and (d) dissemination material such the project brochure and videos.
Even though different R&D projects used LIDAR, IMU and EGNSS, only some of them have done an accurate technology characterization in railway environments. In addition, the Ground Truth facilities developed up to now satisfied specific projects’ needs only and required significant investments. Furthermore, no public information is available on methodologies for executing accurate and precise railway surveys and building Digital Maps, by using measured data collected with commercial trains.
The RAILGAP project aims at providing the characterizations of the LIDAR, IMU and EGNSS technologies in railway environment and the definitions of both methodologies (i.e. Ground Truth and Digital Map) to the R&D communities as project public deliverables. In particular, the RAILGAP Ground Truth provides “reference data along with their accuracy” for different types of quantities to be monitored (i.e. position, speed and acceleration) and does not require installation of trackside equipment and the a priori knowledge of the database of the lines.
The RAILGAP project aims at providing the characterizations of the LIDAR, IMU and EGNSS technologies in railway environment and the definitions of both methodologies (i.e. Ground Truth and Digital Map) to the R&D communities as project public deliverables. In particular, the RAILGAP Ground Truth provides “reference data along with their accuracy” for different types of quantities to be monitored (i.e. position, speed and acceleration) and does not require installation of trackside equipment and the a priori knowledge of the database of the lines.