Određivanje energetskog profila prometnice na temelju povijesnih zapisa o kretanju vozila

undergraduate thesis

• Title (english): Determination of Road Energy Profile Based on Historical Records of Vehicle Trajectories
• Author: Nikola Mardešić
• Mentor: Hrvoje Gold (mentor)
• Committee member: Mario Muštra (predsjednik povjerenstva)
• Committee member: Edouard Ivanjko (član povjerenstva)
• Committee member: Pero Škorput (član povjerenstva)
• Granter: University of Zagreb; Faculty of Transport and Traffic Sciences; (Division of Intelligent Transport Systems and Logistics); (Department of Intelligent Transport Systems); Zagreb
• Defense date and country: 2019-09-17, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Traffic and Transport Technology; Intelligent Transport Systems and Logistics

Abstract

Udjel električnih vozila postepeno se povećava na globalnom tržištu. Uz sve svoje prednosti električna vozila su karakterizirana relativno malim dosegom vožnje. Kako optimalno iskoristiti kapacitet baterije predstavlja nezaobilazno pitanje. Praćenje putanje vozila na prometnoj mreži rezultira akumuliranjem velike količine podataka. Ti povijesni podaci mogu se koristiti kao višestruki izvor dodatnih informacija tijekom prometne analize te su glavni izvor podataka korištenih u ovom radu. Cilj ovog rada je prostorno-vremenska analiza energetskih profila mreže prometnica unutar šire okolice Grada Zagreba te razvijanje grafičkog korisničkog sučelja za integraciju i ilustraciju dobivenih rezultata za krajnje korisnike. U svrhu postizanja ovih ciljeva primijenjena je metodologija izračuna energetskih profila temeljena na povijesnim podacima kretanja vozila. U radu je obrazložen model izračuna električne energije vozila na razmatranom prometnom segmentu. Budući da se vrijednosti energetskog profila prometnice mijenjaju tijekom dana dizajnirano je interaktivno grafičko korisničko sučelje u kojem se vizualno prikazuju energetski profili mreže prometnica u danom trenutku. U radu je također primijenjen algoritam grupiranja prometnica na temelju sličnih karakteristika te razvijen algoritam rutiranja električnih vozila na temelju izračunatih energetskih profila prometnica. Prostorno-vremenska analiza razvijena u okviru ovog rada proizvela je rezultate sukladne s prostornom logikom područja istraživanja unutar šire okolice Grada Zagreba. Rezultati istraživanja nude praktičan uvid u energetsku učinkovitost prometnih segmenata urbanog prostora na temelju kojeg je moguća izvedba planiranja ruta flote električnih vozila.

Abstract (english)

The share of electric vehicles is gradually increasing in the global vehicle market. Although electric vehicles have several advantages, they are characterised by relatively low cruising range (autonomy). Therefore, optimal battery utilization is a crucial question and challenge. Road traffic monitoring produces vast quantities of real time and historical data. Historical traffic data is a valuable resource in the field of traffic analysis and it constitutes the primary data used in this research. The aim of this research is to analyse road energy profiles from a spatio-temporal aspect and to develop a graphical user interface for integrating and illustrating the results of the research for end users. To achieve these aims we have implemented a methodology for estimating road energy profiles based on historical traffic data analysis. Furthermore, we have developed an approach for computing electric vehicle electricity consumption (or generation) on individual road segments. However, the values of the road’s energy profile change in the course of a day. Thus we have created an graphical user interface through which we can observe road energy profile values at a given time of day. We have also implemented an algorithm for clustering road segments based on similar energy profiles. Finally, we have developed an modified vehicle routing algorithm which dynamically calculates optimal routes based on road energy profiles at a given time of day. The results of this research can help inform policy makers on the given situation for electric vehicles implementation and proliferation in the larger urban area of Zagreb city. More importantly, combined with the graphical user interface and custom routing algorithm, the outcomes of this research could provide electric vehicle users a valuable tool for optimizing their vehicle utilization.

• Keywords: NoSQL; C#; veliki skupovi podataka; obrada i pohrana prometnih podataka; energetski profil prometnica; rutiranje vozila; grupiranje prometnica; električna vozila
• Keywords (english): NoSQL; C#; large datasets; traffic data analysis; road energy profiles; vehicle routing; road clustering; electric vehicles
• Language: croatian
• URN:NBN: urn:nbn:hr:119:199795
• Study programme: Title: Intelligent Transport Systems and Logistics; specializations in: Intelligent Transport Systems, Logistics; Course: Intelligent Transport Systems; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka prometa (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka prometa)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2020-01-14 11:16:29