Korištenje velikih skupova podataka (Big Data) u procesu planiranja međugradskog prijevoza putnika

master's thesis

• Title (english): Using Big Data in Intercity Passenger Transport Planning Process
• Author: Ivan Mišura
• Mentor: Marko Ševrović (mentor)
• Committee member: Mario Šafran (predsjednik povjerenstva)
• Committee member: Tomislav Fratrović (član povjerenstva)
• Committee member: Kristijan Rogić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Transport and Traffic Sciences; (Division of Transport); (Department of Urban Transport); Zagreb
• Defense date and country: 2023-09-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Traffic and Transport Technology; Intelligent Transport Systems and Logistics

Abstract

Big Data tehnologija donosi brojne prednosti i moguće ju je uključiti u sve aspekte poslovanja, pa tako i u transportne procese. Big Data ili veliki skupovi podataka mogu povećati efikasnost poslovanja, smanjiti troškove i općenito poboljšati kvalitetu poslovnih procesa i zadovoljstvo korisnika. Ovaj rad istražuje mogućnosti primjene Big Data sustava u međugradskom prijevozu putnika te prikazuje njihov značaj u procesu planiranja prijevoza. Cilj ovog rada je prikazati na koji način se koristi Big Data tehnologija kako bi, uz njezinu upotrebu, pozitivno utjecali na proces planiranja prijevoza. Osim širokih mogućnosti primjene, treba pripaziti i na brojne izazove vezane uz privatnost i sigurnost podataka, kao i na tehničke izazove koji se pojavljuju u procesu njihove obrade i analize. U ovom radu općenito su opisani veliki skupovi podataka, načini njihove primjene u prometnom sustavu te su prikazani konkretni primjeri njihovog korištenja u planiranju međugradskog prijevoza putnika. Iako se suvremeni elektronički sustavi temelje na obradi velike količine podataka, ti podaci su samo djelić onoga što nas stvarno okružuje i postoji oko nas. U sklopu ovog diplomskog rada prikazani su mogućnosti primjene Big Data sustava za potrebe definiranja potrebne prijevozne ponude te procjenu mogućih slabosti prometne mreže međugradskog prijevoza putnika. Prikazane su prednosti i nedostatci korištenja različitih modova prijevoza na različitim udaljenostima putovanja, čime se otvara mogućnost poboljšanja učinkovitosti međugradskih prometnih sustava i promiče koordinirani razvoj regionalne integracije.

Abstract (english)

Big Data technology brings numerous adventages and it is possible to include it in all aspects of buisnnes, including transport processes. Big Data or large data sets can increase buisness efficiency, reduce costs and generally improve the quality of buisness processes and customer satisfaction. This master thesis investigates the use of Big Data in intercitiy passenger transport and shows its significance in the transport planning process. The aim of this research is to show how Big Data technology can be used in order to positively influence the transport planning process. In addition to wide application possibilities, one should also be aware of the numerous challenges that manifest themselves in data privacy and security, as well as technical challenges that arise in the process of data processing and analysis. In this master thesis, Big Data Systems are generally described, as well as the ways of their application in transport system, and concrete examples of their use in planning intercity passenger transport are presented. Although the amount of data we process seems very large, it is only a part of what really surrounds us. This master thesis also gives an assessment of the possible weaknesses of the transport network of intercity passenger transport, and of the need to increase or decrease the transport supply. The advantages and disadvantages of using different transport modalities at different travel distances are presented, which opens up the possibility of improving the efficiency of the intercity transport systems and promotes the coordinated development of regional integration.

• Keywords: veliki skupovi podataka; prometno planiranje; modeliranje udaljenosti putovanja; međugradski prijevoz; planiranje prijevoza putnika
• Keywords (english): Big Data; transportation planning; transportation demand forecasting; intercity transport; passenger transportation planning
• Language: croatian
• URN:NBN: urn:nbn:hr:119:501396
• Study programme: Title: Intelligent Transport Systems and Logistics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka prometa (magistar/magistra inženjer/inženjerka prometa)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2023-09-19 09:57:56