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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - SMART (Smart Automation of Rail Transport)

Teaser

Summary

The main goal of the project SMART- SMart Automation of Rail Transport is to increase the effectiveness and capacity of rail freight through the contribution to automation of railway cargo haul at European railways by developing of:
â€¢ a prototype of an autonomous obstacle detection system, and
â€¢ a real-time marshalling yard management system.

The SMART solution for obstacle detection (OD) will provide prototype hardware and software algorithms for obstacle detection on the rail tracks ahead of the locomotive. The system will combine different vision technologies: thermal camera, night vision sensor (camera augmented with image intensifier), multi stereo-vision system and laser scanner in order to create a sensor fusion system for mid (up to 200 m) and long range (up to 1000 m) autonomous obstacle detection during day and night operation, as well as during operation in poor visibility condition. In this way, SMART will make an important contribution to the vision of a fully automated rail freight system.

The SMART real-time marshalling yard (RTMY) management system will provide optimisation of available resources and planning of marshalling operations in order to decrease overall transport time and costs associated with cargo handling. The yard management system will provide real time data about resources available over open and TAF/TSI standard data formats for connection to external network systems and shared usage of marshalling yards between different service providers. All activities of marshalling Yard (MY) work stream are in line with objective to increase efficiency in the MYs and sidings and to reduce lead-time and costs as well as to simplify business processes as real time decision support system for deviations in decision making processes in MY will decrease time for making decisions by dispatchers and other users

Work performed

In the reporting period, work performed in both workstreams, Autonomous Obstacle Detection (OD) and Real-time Marshalling Yard (MY) Management, was in line with the planned work described in DoA.

The main results achieved within OD workstream in the reporting period involve definition of requirements and specification of the multi-sensory system. Starting from the defined requirements and specification, the sensors of OD system were selected/developed. All sensors were integrated into the sensor housing to enable easy mount and dismount onto/from different test vehicles. Conformance testing of all OD sub-systems was done, and the several field tests were conducted on railtrack sites in Aachen, Germany, and in Nis, Serbia, achieving so TRL4-5. Development of software algorithms for reliable obstacle detection has started and the first results are given in deliverable D3.1. The HW infrastructure is fully completed and ready for further fireld tests to be performed in the next project period to support further development of OD software for autonomous recognition of obstacles on the railtracks ahead of the locomotive and for the calculation of distances to those obstacles.

The main results achieved within MY workstream in the reporting period involve analysis and specification of requirements for MY management. Modelling processes in MYs were done and essential data and processes for providing optimisation of available resources and planning of marshalling operations in order to decrease overall transport time and costs with cargo handling were selected and described in details. Standard data formats were analyzed and were taken into account in the initial phase of developing RTYM system. The chosen platform allows integration to existing IT platforms on marshalling yards. Concept solution of real-time yard management (RTYM) system was done as well as database structure of the RTYM system. Software development for real time decision support system has started based on achieved results in WP4 and WP5. Initial version of Visualization and Planning module with Data Input and Data Output submodules was done during the reporting period. The reached TRL is 4

Final results

The SMART Obstacle Detection System (ODS) will advance state of the art in several aspects. In contrast to state of the art onboard ODSs, which recognise obstacles up to 100m, SMART ODS will be the first system able to recognise obstacles beyond 200m and up to 1000m during day and night operation. SMART will develop a novel night vision sensor-camera augmented with image intesifier to be integrated with different vision sensors and a laser sensor. In this way, SMART will contribute to long term goal of autonomus cargo haul trains necessary for implementation of EU transport strategy.

The SMART marshalling Yard (MY) management system will be a web-based information system for supervision and management of marshalling yards that will enable marshalling yards officials to view marshalling yard representation including receiving yard, hump, classification yard and departure yard. Integration with the marshalling yard automation system should lead to the automation of the marshalling process from planning to execution. SMART MY Management System will be a novel machine-learning based decision system that can give optimal or near-optimal solution for any marshalling yard operation in real time.In this way, SMART will contribute to increased efficiency in the MYs and sidings and to reducing lead-time and costs as well as to simplifing of business processes.