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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2022-22-1-60-66
A study of the influence of human factors on the speed of urban rail transport
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Article in Russian
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Abstract
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Lyakhovenko Ju.A., Popov I.Yu. A study of the influence of human factors on the speed of urban rail transport. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2022, vol. 22, no. 1, pp. 60–66 (in Russian). doi: 10.17586/2226-1494-2022-22-1-60-66
Abstract
The paper presents a model for assessing the state of transport hubs of public rail transport and investigates the dependence of the movement speed of urban rail transport on the influence of external random human-based factors. The study considers the following factors: the movement of other vehicles and pedestrians, repair on road sections, and the density of traffic of vehicles and pedestrians. The proposed model of the transport hub contains many intersections, rail traffic lines, and mixed traffic lanes within the framework of the traffic rules. The solution to the problem is based on the methodology of multi-agent systems. The basis of the proposed approach is the definition of the architecture of individual agents and the input parameters of the expected system responses. The software platform PTV Vissim, which allows building models of traffic flows with various types of vehicles, is used. During the simulation of the multi-agent system, a significant dependence of the speed of urban rail transport on the traffic density and the presence of repair work was revealed. A distinctive feature of the proposed approach is that it considers the influence of the human factor. The obtained approach can be used to design transport hubs for the unimpeded movement of unmanned urban rail transport.
Keywords: multi-agent systems, modeling, railway transport, human factors, modeling of traffic flows
Acknowledgements. This work is partially supported by the Ministry of Science and Higher Education of Russian Federation, state assignment No. 2019-0898.
References
Acknowledgements. This work is partially supported by the Ministry of Science and Higher Education of Russian Federation, state assignment No. 2019-0898.
References
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