Safety After Dark Innovation Challenge for Transport for NSW
Elizabeth Muscat
Cardno, New South Wales
This presentation was delivered at the 2021 Online Conference Series and until October 2022 is only available to registered delegates and Content Access Pass holders via Interchange. For information on accessing this and other presentations please review the Content Access Pass options.
ABSTRACT
In 2020, Cardno partnered with UNSW to deliver a data-based solution to Transport for New South Wales’ Safety After Dark Innovation Challenge, which explored innovative and data-driven solutions that focused on improving safety for women travelling at night.
The partnership developed a proof of concept for a Passive Surveillance Index (PSI) for streets. Passive surveillance reduces opportunities for crimes to occur and improves the perception of personal safety. The PSI used experiential data obtained from women who regularly use the study area to feed into a machine learning model that predicted the level of passive surveillance for urban streets. The application of the data set is extensive, with two key functions:
- To inform personalised wayfinding for safer/ evening friendly walking routes; and
- A powerful tool for city planners to inform investment and policy decisions.
This tool provides benefits for communities as a whole. Having the knowledge of areas that have higher passive surveillance will allow individuals to more freely participate in the community at night, and provides decision makers greater understanding of the transport network.
A forest based regression model was used to develop the index, which involved training a model with known data to predict perceived passive safety at any location.
This presentation will outline the development of the index and the considerations for place making and transport planning at night for women.
Author
Elizabeth Muscat | Cardno
Elizabeth Muscat is a Transport Planner at Cardno with over five years’ of experience in transport planning and infrastructure projects from rural town active transport plans to regional strategic planning. She does this while utilising her GIS skills to communicate ideas, clarify complex analytics and improve decision making.
In 2020, Elizabeth successfully delivered a proof of concept for an innovative dataset that aimed at improving safety after dark for women, particularly in catchments served by public transport.
