Spatio-temporal pattern estimation in urban and traffic planning:

Abstract

Dette speciale præsenterer udarbejdelsen af et eksplorativt analyseværktøj til at undersøge spatiotemporale mønstre i et givent interesseområde for by- og trafikplanlægning. Ved at kombinere udelukkende Open Source-teknologier til at udvikle et brugervenligt analytisk værktøj, kan planlæggere let justere værktøjet til flere formål, såsom at følge op på tiltag mod at nå FN's verdensmål eller finde områder med køddannelse. Det sidstnævnte er blevet udført i dette studie ved hjælp af et stort Origin-Destination datasæt, indsamlet fra biler i Danmark i løbet af 2019. I casestudiet sammenlignes morgen- og eftermiddagstrafikken internt i København og Frederiksberg kommuner med undersøgelse af, om flowet af biler er anderledes om morgenen end om eftermiddagen, samt for at undersøge, om der er nogen områder der er mere hyppige som destinationer. Det ser ud til, at der er nogle områder, hvor flere biler slutter deres rejse, både i morgen- og eftermiddagmyldretiden, hvilket kan forårsage mere overbelastning i disse timer. Sammenligning med den eksisterende infrastruktur for offentlig transport og cykelstier viser ingen sammenhæng mellem manglende infrastruktur og endepunkter.

This dissertation proposes an exploratory analytical tool for examining spatio-temporal pat-terns in any area of interest for urban and traffic planning. By combining solely Open-Source technologies to create a user-friendly analytical tool, planners can easily adjust the tool to fit multiple purposes, such as keeping track of the improvements towards reaching UN's Sustainable Development Goals or finding congested areas in urban areas. The latter has been done throughout this study, using a large set of Origin-Destination pairs, collected from cars in Denmark during 2019. For the case study, the morning and afternoon traffic internally in Copenhagen and Frederiksberg municipalities are compared, to examine whether the flow of cars is different in the morning than in the afternoon, as well as to examine if there are any areas that are more common as destinations. It seems that there are some areas, where more cars end their trip, both during the morning and afternoon peak hours, which might cause more congestion during these hours. Comparison with the existing infrastructure of public transport and bike lanes shows no coherence between poor infrastructure for transportation alternatives and common destinations.

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A master thesis from Aalborg University

Spatio-temporal pattern estimation in urban and traffic planning: - An exploratory analytical tool

[Spatiotemporal analyse af mønstre i by- og trafikplanlægning: - Et eksplorativt analyseværktøj]