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Team Name:

Flowcation


Team Members:


Evidence of Work

Flowcation – Dynamic route optimization system

Project Info

Flowcation thumbnail

Team Name


Flowcation


Team Members


Karl , Katrina , Quentin and 4 other members with unpublished profiles.

Project Description


Project Title: Flowcation – Simulating the Ripple Effects of Urban Infrastructure

Project Summary

Flowcation is a data-driven visualization and simulation tool designed to help city planners assess the ripple effects of infrastructure changes on accessibility, equity, and transport efficiency. Built as an open-source extension, Flowcation empowers planners to model how modifications—such as adding a school, clinic, bus route, or cycle path—impact the reachability of essential services within a 20-minute travel window.

By integrating transport data, demographic indicators, and predictive algorithms, Flowcation supports smarter, more inclusive urban planning decisions aligned with Victoria’s 20-Minute Neighbourhood vision.

Challenges Addressed

Delivering the 20-Minute Neighbourhood Plan

Enabling Better Community Housing and Infrastructure Planning

Optimising Transport Networks for School Kids

Problem Statement

Infrastructure changes—no matter how small—create cascading effects across transport networks, service access, and community wellbeing. Yet planners lack tools to simulate these ripple effects before implementation. This gap leads to missed opportunities, especially in low-income suburbs where transport inequity is most severe.

What We Built

  • Travel Ring Generator

Calculates 20-minute reach zones from key locations (schools, clinics, etc.) by transport mode: walk, bike, bus, car.

  • Scenario Simulator

Allows planners to add/remove infrastructure elements (e.g. bus routes, cycle paths) and see how travel rings expand or contract.

Data Sources

  • OpenStreetMap: Road and transport network topology

  • VicRoads: SCATS Traffic signal volume and congestion data

  • VicRoads: Traffic Signal Geo Data

Research References

  • VISTA: Travel by time of day, journey to work, trip purpose

  • VCOSS: Mapping poverty in Victoria

  • ABS Census: Demographic and housing data

  • Infrastructure Australia: Ring classification and transport access

Algorithms & Technical Architecture

Graph-based search using OSM nodes and edges

Shapely and GeoPandas to create the transport access rings.

Matplotlib for map rendering

Future Features

Real-time traffic signal priority modeling (e.g. SCATS/SPE/PTIPS)

Community feedback layer for participatory planning

Prophet ML for predictive congestion and travel time adjustments based on weather, roadworks, and seasonality (e.g. school holidays)

Impact

Flowcation isn’t just a visualization tool — it’s a planning companion that helps governments build equitable, resilient, and accessible cities. Simulating infrastructure ripple effects enables smarter investment, reduces transport inequality, and brings the State governments closer to its urban plan vision.

Demo & Screenshots

Please watch our video for more details


#city planning #data visualization #public transporation #delivering the 20-minute neighbourhood plan

Data Story


Intro

Public transport across Greater Melbourne (Inner, Middle, and Outer) takes up the longest travel time among all transport modes.

The further you go out of central Melbourne, the longer public transport takes on weekdays and weekends. This trend pervades year over year, based on data from 2007 to 2024.

This transportation inequity reflects an underlying socio-economic disparity. Outer Melbourne has a larger proportion of economically disadvantaged areas compared to Inner and Middle Melbourne. What’s more - a smaller share of economically disadvantaged areas is concentrated within central Melbourne.

Patterns of disadvantages like these must inform our urban planning. To address these gaps in transportation, the Victorian Government’s urban planning strategy includes a plan for 20-minute neighbourhoods.

The 20-minute neighbourhood policy seeks to establish livable and inclusive neighbourhoods where people are able to access their daily needs within a 20-minute return walk.

The long-term plan includes a sustainable vision for transport: safe cycling networks, walkable streets, and public transport connections.

The Problem

Changes to existing transport systems - no matter how small - have ripple effects.

How can we predict the impact of planned modifications? What are the possible outcomes of these infrastructure changes?

More importantly, how can we assess if low-income suburbs are at a disadvantage compared to high-income suburbs when it comes to urban planning?

Introducing Flowcation

Flowcation is a visualisation tool that simulates the potential impact of changes to transport infrastructure, built to support urban planners in making data-backed decisions.

How It Works

Flowcation visualises targeted locations, calculating how far you can travel within a 20-minute return walk. This area will be visually represented by a travel ring.

You can filter by transportation method: by active transport (walking or cycling), public transport, or private transport.

Features

  • Travel Ring Generator
    Calculates 20-minute reach zones from key locations (schools, clinics, etc.) by mode: walk, bike, bus, car.

  • Scenario Simulator
    Where you can simulate adding or removing new bus routes, cycle paths, or service locations.
    You can see how travel rings expand or contract.

Use Case: Identifying Gaps in Existing Transport Design

Building new travel routes requires planners to consider: how many schools are within a 20-minute vicinity? Hospitals? Shopping centres?

Flowcation lets you see all locations of interest accessible within a 20-minute radius.

This helps:
- Visualise shortfalls in 20-minute accessible zones
- Simulate how proposed routes or changes affect accessibility
- Discover areas where new connections could be implemented

Use Case: Measuring Travel Efficiency and Accessibility

Traffic intersections can handle roughly 500 cars per hour at 60km/h, but peak-hour traffic contributes to a surge of up to 800 cars. This creates congestion, limiting the speed of travel.

Flowcation has a built-in feature that shows intersections where congestion is concentrated.

This helps:
- Plan new public transportation routes to diversify existing pathways
- Reduce traffic at intersections during peak hours by limiting private transport vehicles
- Widen the travel ring, helping meet the 20-minute neighbourhood goal

Use Case: Assessing Potentially Disadvantaged Neighbourhoods

Flowcation allows urban planners to focus on specific locations within neighbourhoods to illustrate how wide the 20-minute radius is.

This can be used to discover the disparity in travel time within neighbourhoods of economically disadvantaged areas.

This poses opportunities to:

  • Explore improvements in economically disadvantaged neighbourhoods
  • Compare the impact of infrastructure changes in low-income areas vs. high-income areas
  • Predict how route modifications influence activity in these neighbourhoods

Scalability

Our MVP presents a high-level overview of the potential impact of infrastructure modifications. In the future, we can implement a version powered by Prophet, a forecasting algorithm that accounts for seasonality and external factors like weather conditions and road works.

Flowcation isn’t just a visual tool. It’s one step closer to sustainable and equitable living for all Victorians, helping urban planners design with data-driven solutions.


Evidence of Work

Video

Team DataSets

Ring classification for 5 largest capital cities in 2021

Description of Use Contextual Zoning: Use the Inner/Middle/Outer ring classifications to analyze and compare accessibility disparities across different urban zones. For example, visual travel rings may vary significantly between dense inner-city SA2s and less connected outer rings. Targeted Simulation: Tailor travel-ring simulations and transport scenario modeling within each ring—enabling planners to identify where improvements (e.g., new bus routes or cycling paths) are most critical based on location-specific needs. Benchmarking and Visual Clarity: Overlay BCARR ring boundaries on your accessibility maps to clearly illustrate geographic zones and highlight where 20-minute access goals are strongest or weakest.

Data Set

Mapping Poverty in Victoria

Description of Use Contextual Insight: Gain a clearer understanding of communities experiencing economic hardship—critical for prioritizing areas where improved transport access could have the greatest social impact. Equity-Driven Planning: Use demographic overlays (e.g., high rates of disability or low-income households) to guide the allocation of transport interventions, ensuring that travel accessibility improvements address local vulnerability profiles. Scenario Targeting: Tailor simulations to reflect community-specific needs—for example, improving access to schools or services in areas with elevated child poverty.

Data Set

VISTA - Trips

Description of Use Mode Share Calibration We use realistic proportions of travel modes—derived from the dataset—to calibrate our travel-ring simulations and reflect actual behavior in model parameters. Trip Timing & Distance Insights The detailed data on departure/arrival times and distances helps fine-tune routing algorithms, especially under varying traffic volumes and congestion conditions. Validation of Simulated Accessibility By comparing simulated travel rings with observed trip patterns, we ensure our accessibility visualisations are grounded in real-world evidence.

Data Set

VISTA - Journey to work

Description of Use We apply this dataset to: Define realistic travel mode shares, informing our travel-ring simulations by accurately reflecting the proportion of users traveling by car, bus, bike, or walking during different times of day. Calibrate congestion modeling, using average travel times and distances to estimate typical traffic volumes and speeds in specific corridors. Validate simulation outputs, ensuring generated accessibility rings reflect actual commuting behaviors and regional travel patterns.

Data Set

Victorian Integrated Survey of Travel & Activity (VISTA)

Description of Use We leverage the VISTA dataset to: Calibrate travel behaviour models, helping determine mode shares (car, public transport, cycling) and peak usage times. Inform traffic volume inputs by understanding typical trip distributions throughout the day. Validate our simulation outputs, ensuring our accessibility “travel rings” reflect real-world travel patterns and constraints.

Data Set

20 Minute Neighbourhood Research and Resources

Description of Use We leverage these insights and resources to: Inform our simulation parameters, particularly the “hallmarks” of 20-Minute Neighbourhoods, ensuring our visualizations align with established liveability standards. Benchmark improvements, enabling us to compare current travel-accessibility ring outputs against recognized criteria and flag shortfalls clearly. Validate interventions, by mapping simulated changes (like adding bus routes or cycling paths) against policy-backed guidelines and case evidence, strengthening the relevance of our tool for urban planning contexts.

Data Set

Challenge Entries

Delivering the 20-Minute Neighbourhood Plan

How might we use open data to understand and improve the ways people move, work, and access services — creating neighbourhoods that are more liveable, inclusive, and resilient?

#Accessible-communities

Eligibility: Open to all, but preference given to teams with a lead in VIC. At least one dataset from data.vic.gov.au must be used. Open data on transport networks, amenities, planning permits, green spaces, demographics, and mobility patterns is suggested but creativity in dataset usage and sourcing is strongly encouraged.

Go to Challenge | 11 teams have entered this challenge.

Enabling Better Community Housing and Infrastructure Planning

How might we use multiple public datasets, including building permits, to guide communities in planning for housing and services in their local communities— from understanding areas of housing stress to anticipating the impact of future developments on community access, services, and social connection?

#Building-Victoria's-future

Eligibility: Open to all, but preference given to teams with a lead in VIC. At least one dataset from data.vic.gov.au must be used.

Go to Challenge | 7 teams have entered this challenge.

Optimising Transport Networks for School Kids

How can we leverage graph analytics, generative AI and other data approaches to optimise public school transport networks to make it simple to get the next generation of students to school with less hassle?

#Reimagining-school-transport-networks

Eligibility: Open to all, although special consideration will be given to teams with a lead based in ACT. Contestants are strongly encouraged to use multiple sources of data including datasets outside of those listed below.

Go to Challenge | 13 teams have entered this challenge.