Approach for Development of Real-Time Marshalling Yard Management System

Dimitrov, L.; Purgic, S. P.; Tomov, Pancho; Todorova, Mirena

doi:10.1109/hitech.2018.8566369

Cited by 8 publications

(1 citation statement)

References 3 publications

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“…For the fully autonomous train operation all the activities and responsibilities of train operators need to be taken over by several systems that can sense the environment and overlook the scene, detect potentially dangerous objects on the train's path and react accordingly and in the right way [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

AI Powered Obstacle Distance Estimation for Onboard Autonomous Train Operation

2022

Teh. vjesn.

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This paper proposes a novel method for an AI powered improvement of the estimation of a distance between the camera and an imaged object using image-plane homography. The method exploits the homography between two planes, the image plane and the rail tracks plane, and an artificial neural network that reduces the estimation error based on collected experimental data. The SMART multi-sensory onboard obstacle detection system has 3 vision sensors -an RGB camera, a thermal vision camera and a night vision camera, in order to achieve greater reliability and robustness. Although the methodology presented in this paper is applicable for each vision sensor, the proposed method was tested with the thermal camera and in impaired visibility scenarios. The validation of estimated distances is done with respect to real measured distances from the camera stand to the objects (humans) involved in the experiments. Distances are estimated with a maximum error of 2% and the proposed AI powered system can provide a reliable distance estimation in impaired visibility conditions.

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Section: Introductionmentioning

confidence: 99%

AI Powered Obstacle Distance Estimation for Onboard Autonomous Train Operation

2022

Teh. vjesn.

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Towards the Improvement of Yard Management Systems (YMS) Using Radio Frequency Identification (RFID)

Alieksieiev

Kovalenko

Stryzhak

et al. 2022

International Conference on Reliable Systems Engineering (ICoRSE) - 2022

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Formation of the freight trains with a fixed train schedule

et al. 2021

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The hypothesis of the study consists of the detailed consideration of the process of accumulation of wagons, taking into account the arrival of individual groups of wagons, determination of options for freight trains with a fixed train schedule and substantiation of analytical dependencies that determine the cost of wagon-hours for accumulating trains and obtaining new scientific results on this basis. Their practical use will make it possible to more accurately and reasonably normalize the idle time of cars under accumulation, as well as to clarify the methodology for calculating the train formation plan. The research methodology is based on existing methods and methods of forming freight trains for a rational way of implementing the train schedule. Results of the study: the methods of standardizing the idle time of cars under accumulation were stated, the regulations of idleness of cars at the sorting yard were clarified, and options for optimizing the plan for the formation of trains were proposed.

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Approach for Development of Real-Time Marshalling Yard Management System

Cited by 8 publications

References 3 publications

AI Powered Obstacle Distance Estimation for Onboard Autonomous Train Operation

AI Powered Obstacle Distance Estimation for Onboard Autonomous Train Operation

Towards the Improvement of Yard Management Systems (YMS) Using Radio Frequency Identification (RFID)

Formation of the freight trains with a fixed train schedule

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