CSIRO launches a new lunar test bed – OpenGov Asia

In a study, Transport for NSW is using AI, Wi-Fi, and edge computing on Pitt St, near Central Station, to collect real-time data and identify high-risk events. Road users’ movements are also tracked at several intersections in Newcastle, using smart sensors to improve overall road safety. In a further experiment, several buses, ferries and light rail vehicles are connected with one another and then possibilities for improving the services are determined with the help of real-time data. The minister noted that buses equipped with this technology can also monitor facility and road conditions and provide us with real-time information about vehicles.

The network hardware company provides several technologies for the test, including IoT, edge computing, AI, and other functions. Transport for NSW and the company have an existing partnership that aims to use technology to solve urgent and common transportation problems. TfNSW is also working on the project with the University of Technology Sydney and geospatial experts, an NSW software company. The local company previously partnered with the consumer electronics company to extract more than 50 road assets and safety features such as road markings, safety barriers and trees from LiDAR data.

MN-R is the model the consumer electronics company uses to keep its map data up to date. It combines several levels of data acquisition techniques, including the use of its navigation systems and sensors. In addition to understanding road conditions and hazards, TfNSW hopes that the project could also lead to the development of prediction algorithms for injuries and fatalities in the future. The project will feed into a global “AiRAP” initiative of a non-profit road assessment agency, the International Road Assessment Program (iRAP). IRAP’s global innovation manager, who oversees the project, said AI has the “potential to reduce costs and increase the frequency and accuracy of data”. She pointed out that faster and cheaper data collection enables annual safety assessments to be carried out across the road network.

Currently, in collaboration with the iMOVE Cooperative Research Center (CRC), the agency is relying on video captured by crews for safety assessments, from which certain road attributes are extracted. However, TfNSW would like to accelerate the process and has started a project to “convert raw data … into an international standard five-star rating system”. The project will provide 20,000 km of road attributes in NSW using TomTom’s MN-R map data, as well as demonstrate feature extraction and machine learning techniques for LiDAR data. According to a previous OpenGov Asia article, Transport for NSW hopes that aggregated data collected by a Dutch consumer electronics company and LiDAR systems could give them a more timely insight into the conditions and hazards on the state’s road network.

The project comes at a time when the federal government is planning to tie infrastructure financing to “measurable improvements in safety”, according to the draft of the National Road Safety Strategy 2021-30. Canberra previously set targets for 90% of national highways and 80% of federal highways to meet a safety standard of three stars or better.

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  • Headline: CSIRO Launches New Moon Test Stand – OpenGov Asia
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