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strategic transport modelling framework for Active Transport (i.e. cycling and walking modes) as well as emerging micro-mobility modes

License: MIT License

Python 96.60% Batchfile 3.40%
transport transportation transportation-network transportation-planning transportation-problem transportation-simulation traffic-analysis bicycle cycling micromobility

atam's Introduction

{ATAM} Active Transport Analytics Model

Overview of ATAM

  • 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

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

  • Model structure and outputs - key features:

    • Networks – detailed networks, which consider factors such as safety to AT users, are a model input. Networks can be curated from sources including OpenStreetMap and other open data. Future scenario network changes can be tested for project appraisal.
    • Demand – demand matrices are an input and base year demand can be estimated from available sources such as household travel surveys, counts, Strava data, mobility data or other strategic model outputs. Future demand could be estimated based on demographic projections or demand matrices could be re-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”))
  • ATAM is built on open-source tools and does not require proprietary transport

    • The core model functionality uses open-source tools - Python and QGIS (Tableau Public has been used to visualize data as well). No proprietary transport modelling software packages are required.
    • Brisbane POC demo/example model code and data is openly available on GitHub (https://github.com/atam-analytics/atam) and serves as an example to implement the ATAM modelling framework in other regions
  • 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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