GridReaper is a congestion forecaster for commuters. It provides commuters an accurate forecast of congestion in various transportation methods in the following days, weeks, and months.
Starting from available usage data on transportation methods and routes, we applied regression techniques to determine functional relationships with other datasets we considered unusual, like weather time-series.
The resulting regression models are then made available as services for GridReaper to use.
How might we combine data with modern technologies - such as AI/ML, IoT, Analytics or Natural Language interfaces - to better our public transport services. Outcomes could take the form of new commuter experiences, reduced environmental impact, or helping plan for the future.
What are the key levers that can be affected to ease congestion in NSW?
Using open data and other data sources, what can you infer that can be changed by Transport for NSW to help ease congestion? This can be congestion from people, cars, train passengers, on a platform or queuing for a bus or just generally on a road.
What has happened in the past? What information can we provide customers, bus drivers or employers to assist in easing congestion?
Note: this is not just road congestion. It can be viewed holistically or at a microlevel – for say an intersection.
🌟 What's the coolest way to travel across the city?
Using datasets which map urban heat and green cover across Greater Sydney, we challenge you to develop a tool which visualises green routes through the city. Help people avoid urban heat and move across the city in comfort by mapping out green streets and pathways which connect shopping centres, public transport stops and public spaces.