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EN
The paper presents the analysis and discussion of video detection data usage for discrete transport systems safety improvement. The Autonomous Vehicles (AV) and the Augmented Reality (AR) research in connection with a Driving Assistance (DA) are presented. This article is going to show where the border between those two fields of interest is and how they are going to influence on the future of automotive. The proposal of the AR system – based on soft-computing methods used for an object classification problem – is given. The input data are taken from the real traffic monitoring system located at the set of roads in Poland. Data from the monitoring devices are used to analyze the travel time of vehicles – elements of the transportation system. The travel time model taking into account the real road situation is built. The proposed solution can be an essential tool for the owner and administrator of the transportation systems
EN
The paper proposes a method of reliability and functional analysis related to discrete transport systems. The proposed analysis is based on modelling and simulating of the system behaviour. Monte Carlo simulation is used for proper reliability and functional parameters calculation. The simulator is built using Scalable Simulation Framework (SSF). No restriction on the system structure and on a kind of distribution is the main advantage of the method. The paper presents some exemplar system modelling. The authors stress the problem of influence of the reliability parameters for final functional measures (required time of delivery) – the key value to calculate the availability of the system. They also propose to measure the economic quality of discrete transport system by “profit function”. The presented problem is practically essential for defining an organization of vehicle maintenance and transportation system logistics.
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