INTELLIGENT SYSTEM FOR AUTOMATION SEARCH OF PUBLIC TRANSPORT ROUTES

Keywords: GPS-sensor, data base, class diagrams, knowledge base, decision support, use case diagrams, satellite connection, model-view-controller

Abstract

This article is devoted to automation of search of routes of passenger flows of inhabitants of the city on the basis of routes of public transport. To do this, it is proposed to use satellite data that reflect the movement of passengers. Based on the analysis of data arrays of information on the movement of cellular subscribers and the use of message messages to determine the effectiveness of passenger routes of public transport, the article proposes to create a system of automatic search of public transport routes, which includes different classes of charts and data bases. You can use data from cellular operators to do this. This can increase the accuracy of certain traffic volumes and the ability to monitor them in real time. Reliable information on the routes of urban public transport allows to determine passenger flows and efficiently perform transport services. The main requirements for modeling the city’s passenger traffic are presented. Methods of obtaining data on determining the city’s passenger traffic and public transport are considered. Documentation for the creation of the ISASR (Intelligent System for Automation Search of Routes) project has been developed. The MVC (Model-View-Controller) architectural template was used to develop the project. Class diagrams and precedent diagrams have been developed for the model. Database structures have been created and vehicle types and user types have been defined. Algorithms for finding routes for different situations, with different latitude and longitude coordinates, as well as different number of stops and transfers have been developed.

References

1. Elkosantini, S., & Darmoul, S. (2013). Intelligent Public Transportation Systems: A review of architectures and enabling technologies. У 2013 international conference on advanced logistics and transport (ICALT). IEEE. https://doi.org/10.1109/icadlt.2013.6568465 [in English].
2. Ghanbari, M., Mehr, A. G., & Nehzat, H. (2015). Introducing an intelligent transportation system decision support model for the highways in Iran based on fuzzy logic. International Journal of Soft Computing and Engineering (IJSCE), 3(5), 101–104. URL: https://www.researchgate.net/publication/304022544_Introducing_an_Intelligent_Transportation_System_Decision_Support_Model_for_the_Highways_in_Iran_Based_on_Fuzzy_Logic (date of access: 19.01.2022) [in English].
3. Mnif, S., Darmoul, S., Elkosantini, S., & Ben Said, L. (2018). An immune multiagent system to monitor and control public bus transportation systems. Computational Intelligence, 34(4), 1245–1276. https://doi.org/10.1111/coin.12181 [in English].
4. Mnif, S., Elkosantini, S., Darmoul, S., & Ben Said, L. (2019). An immune network based distributed architecture to control public bus transportation systems. Swarm and Evolutionary Computation, 50, 100478. URL: https://doi.org/10.1016/j.swevo.2018.12.004 [in English].
5. Salazar-Cabrera, R., Pachón de la Cruz, Á., & Madrid Molina, J. M. (2020). Sustainable transit vehicle tracking service, using intelligent transportation system services and emerging communication technologies: A review. Journal of Traffic and Transportation Engineering (English Edition), 7(6), 729–747. https://doi.org/10.1016/j.jtte.2020.07.003 [in English].
6. Szücs, G. (2015). Decision support for route search and optimum finding in transport networks under uncertainty. Journal of Applied Research and Technology, 13(1), 125–134. https://doi.org/10.1016/s1665-6423(15)30011-0 [in English].
7. Zannat, K. E., & Choudhury, C. F. (2019). Emerging big data sources for public transport planning: A systematic review on current state of art and future research directions. Journal of the Indian Institute of Science, 99(4), 601–619. https://doi.org/10.1007/s41745-019-00125-9 [in English].

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Published
2022-04-28
How to Cite
Holyk, O., Zhesan, R., Miroshnichenko, M., & Skalik, M. (2022). INTELLIGENT SYSTEM FOR AUTOMATION SEARCH OF PUBLIC TRANSPORT ROUTES. Scientific Journal of Polonia University, 50(1), 290-301. https://doi.org/10.23856/5034
Section
TECHNOLOGY, CREATIVITY, IMPLEMENTATION