Bridging the Data Gap: AI-powered Insights for Active Transport
Transforming active transport planning, footpath.ai, commissioned by Transport for NSW and in collaboration with the University of New South Wales, utilises AI to fill critical data gaps in walking and cycling across NSW Six Cities Region. This innovative solution integrates diverse data sources, empowering data-driven decisions for healthier, more sustainable communities. Up-to-date insights provide a dynamic perspective on active transport behaviours, setting an Australian first example for AI-powered active transport planning.
While active transport is gaining recognition as a key element for healthier and more sustainable cities, there exists a substantial data gap that impedes the ability of governments to efficiently plan and prioritise investments in walking and cycling infrastructure. The absence of detailed information hampers the development of data-driven policies and strategies essential for building pedestrian-friendly streets and bicycle infrastructure that truly enhance community well-being.
footpath.ai, in partnership with Transport for NSW and the University of New South Wales, has pioneered a groundbreaking AI-powered solution. This innovative tool marks an Australian first, merging multiple big and small data sources including crowdsourced data, mobile phone data, walking and cycling counts, population statistics, land-use information, transport infrastructure data, topographical data, climate data, and air quality data. The result offers a comprehensive, fine-grained understanding of walking and cycling patterns across the expansive NSW Six Cities Region.
Powered by cutting-edge machine learning algorithms and hosted on the cloud with frequent data updates, the solution has revolutionised the way Transport for NSW perceives and manages walking and cycling data. It offers both link-level and aggregated estimates, encompassing walking and cycling volumes, trip counts, and kilometers traveled. The dynamic, up-to-date data stream empowers Transport for NSW to maintain a high-resolution view of active transport behaviours across the region and to monitor changes in active transport trips over time and space.
The initiative sets a precedent for data-driven planning and decision-making in the active transport domain, not only in the NSW Six Cities Region but potentially for regions and cities worldwide. The AI-powered insights serve as a model for leveraging big and small data sources to promote sustainable, healthier, and more efficient urban environments, bridging the data gap and paving the way for a more sustainable and active future for the NSW community.
