Active Transport Analytics Model: A new strategic transport modelling and data visualization framework

Related tags

Miscellaneouspythondata-sciencetransportationbicycletraffic-analysisdata-visualizationtransportcyclingtransportation-simulationgis-datatransportation-networktransportation-planningtransportation-proble
Overview

{ATAM} Active Transport Analytics Model

  • Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framework for Active Transport (“AT”) (i.e. cycling and walking modes) as well as emerging micro-mobility modes

  • Open / open-source modelling philosophy

    • Core model uses open-source tools, mainly Python and Jupyter notebooks and QGIS
    • Demo/example model code and data is available freely on GitHub here
    • Demos are provided to serve as examples to implement the modelling framework in other cities

  • Model structure and outputs.

    • Networks – detailed networks that can be built from many sources including OpenStreetMap (“OSM”) are a model input, and which consider factors such as safety to AT users. Future network changes can be tested for project appraisal.
    • Demand – base year demand matrices are an input and are ‘matrix estimated’ from multiple sources. Future demand is ‘growthed’ up based on demographics projections etc. Demand could be assigned from other strategic modelling tools.
    • Outputs – key outputs that ATAM can produce include: (i) volumes by link, (ii) journey times (by route and Origin-Destination (“OD”) matrix), (iii) analysis of trips using a particular link (i.e. Select Link Analysis (“SLA”))

  • Proof of Concept (“POC”) model developed for cycling in Brisbane, QLD Australia

  • Next steps – improvements to the Brisbane POC model, develop POC models for other cities globally, build awareness and example use cases, feedback & improvement

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ATAM Analytics
Active Transport Analytics Model
ATAM Analytics
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