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Multimodalni načrtovalnik poti z integracijo podatkov v realnem času
ID Beus, Nedžad (Author), ID Pesek, Matevž (Mentor) More about this mentor... This link opens in a new window

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Abstract
Glede na vse večji pomen javnega prometa in skupnih storitev mikromobilnosti pred individualnim prometom ter splošno preusmeritev k bolj trajnostnim načinom prevoza, diplomska naloga želi zapolniti obstoječo luknjo na slovenskem trgu, kar potencialnim uporabnikom predstavlja veliko nevšečnost – pomanjkanje učinkovitega načrtovanja potovanja "od praga do praga", dinamičnih podatkov o zamudah avtobusov in vlakov ter enostavnega nakupa vozovnic. V tej nalogi smo razvili integriran sistem, ki združuje napovedovanje zamud in načrtovanje poti. Sistem temelji na sodobnih pristopih in tehnologijah, kot sta Kalmanov filter za napovedovanje zamud in algoritem RAPTOR za načrtovanje poti. Postavili smo strežnika TheTransitClock in OpenTripPlanner, ki omogočata napovedovanje prihodov vozil in načrtovanje poti v realnem času. Poleg tega smo razvili uporabniško aplikacijo in zaledni API, ki omogočata uporabnikom enostavno načrtovanje poti in spremljanje prihodov.

Language:Slovenian
Keywords:multimodalni načrtovalnik poti, integracija podatkov v realnem času, GTFS, GTFS-RT, NETeX, SIRI, GBFS
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2025
PID:20.500.12556/RUL-167702 This link opens in a new window
COBISS.SI-ID:230008835 This link opens in a new window
Publication date in RUL:07.03.2025
Views:779
Downloads:125
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Secondary language

Language:English
Title:Multimodal trip planner with real-time data integration
Abstract:
Given the growing importance of public transport and shared services of micromobility over individual transport and the general shift towards more sustainable modes of transport, the thesis aims to fill an existing gap in the Slovenian market, which is a major inconvenience for potential users - the lack of efficient ``door-to-door'' journey planning, dynamic information on bus and train delays and easy ticket purchase. In this thesis, we have developed an integrated system that combines delay prediction and journey planning. The system is based on state-of-the-art approaches and technologies such as the Kalman filter for delay prediction and the RAPTOR algorithm for route planning. We have deployed TheTransitClock and OpenTripPlanner servers, which allow real-time forecasting of vehicle arrivals and route planning. In addition, we have developed a user application and a backend API that allow users to easily plan routes and monitor arrivals.

Keywords:multimodal trip planner, real-time data integration, GTFS, GTFS-RT, NETeX, SIRI, GBFS

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