Published on September 10th 2021 in

Transport for NSW launches AI data mining project to rate roads for safety and lower death toll

In a world where people  are embracing domestic road trips due to the impact of the pandemic, a recently launched initiative in NSW aims to use artificial intelligence (AI) to make our road travel safer.

Transport for NSW (TfNSW) has established a timely project using cutting-edge AI to convert raw data from our roads into an international standard five-star ratings systems, as well as to potentially develop predictive algorithms for fatality and injury outcomes. The project is supported by the iMOVE CRC and is being led by TfNSW and partners, including the University of Technology Sydney, the International Road Assessment Programme (iRAP) and geospatial data experts, Anditi.

The project will deliver up usable data for 20,000km of NSW roads to the state government using TomTom’s MN-R next generation map data, as well as prove feature extraction techniques and machine learning for LiDAR data.

The project aims to prove rapid, scalable and repeatable methods for road data extraction as part of iRAP’s global AiRAP initiative (accelerated and intelligent RAP data collection). The initiative will ultimately open up existing and emerging data sources for network-level road safety assessments throughout Australia and the world.

iRAP is a registered charity dedicated to saving lives by eliminating high risk roads throughout the world. It assesses roads all over the world and aims to significantly reduce road casualties by improving the safety of road infrastructure. The Federal Government is linking infrastructure funding to “measurable improvements in safety” and state agencies are setting network and project-level star ratings before greenlighting public spending.

The 2018-2020 National Road Safety Action Plan set targets for 90% of travel on national highways and 80% of travel on state highways to meet a 3-star or better safety standard. To date, more than 280,000km of Australian roads have been star rated.

The assessments involved identifying and recording more than 50 road attributes to the iRAP global standard every 100 metres. However, these assessments have been painstakingly done using video survey footage and manual recording methods.

Project manager, iRAP’s Global Innovation Manager and Cities Specialist, Monica Olyslagers said the use of AI and machine-learning would significantly speed up the task of star-rating roads to enhance public safety. “Raising the standard of the world’s roads to a 3-star or better standard for all road users will help to focus policy and investment. With crash costs typically halving with each incremental improvement in star rating the potential for 3-star or better roads to save lives is significant.”

In recent years, between 1,100 and 1,200 people lose their lives to road crashes on Australian roads each year, and more than 40,000 suffer lifelong, debilitating injuries.

“The use of AI and machine learning techniques to collect the data has potential to reduce costs and increase the frequency and accuracy of data. Making faster and more affordable data collection possible means that safety assessments can be done on an annual basis across the whole road network,” added Olyslagers.

IMOVE CRC managing director Ian Christensen said improving road safety performance is a priority for all levels of government in Australia. “Using technologies such as AI to enhance in our suite of safety policy tools is a great step forward. These powerful and insightful tools can inform sound investment by government that saves lives and unlock significant benefits to families, communities, business and health systems through reduced road trauma.”

For more information on the iMOVE iRAP project, visit:

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