The project investigates whether people are more likely to trust the technology and feel safe if they are able to understand how the system makes decisions and to directly influence its behaviour.
The project delivers a key component for the success of robotic applications in cities: It develops critical understanding about how autonomous vehicles in urban environments need to interact with the people that they share those spaces with. Australia鈥檚 world-leading position in mining robotics offers a unique first-mover advantage for Australia to lead the development of autonomous vehicle technology, a market estimated to increase to $348 billion globally within the next 10 years.
Beyond the domain of driverless cars, autonomous vehicle technology enables new applications, such as transport pods, delivery droids and maintenance robots. The benefits of these kinds of vehicles, which can operate in shared spaces, such as pedestrian zones, include mobility for people with disabilities, delivery of goods in areas that are not accessible by cars and more efficient maintenance of urban infrastructure.
The project contributes to Australia鈥檚 Smart Cities Plan, which outlines the impact of autonomous vehicles, and the Transport for NSW Future Transport 2056 Strategy, which prioritises 鈥減laces for people鈥.
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Design at Sydney
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Autonomous vehicles that are able to operate in shared spaces, such as campuses and pedestrian zones, promise to improve urban life. However, their uptake depends heavily on public acceptance as they operate in close proximity to people.
The project investigates whether people are more likely to trust the technology and feel safe if they are able to understand how the system makes decisions and to directly influence its behaviour. It has three overarching aims:
顿谤听, 爆料王
顿谤听,聽爆料王
笔谤辞蹿别蝉蝉辞谤听,聽爆料王
笔谤辞蹿别蝉蝉辞谤听,聽爆料王
顿谤听,聽爆料王
Professor Simon Marvin,聽爆料王
Professor Martin Tomitsch, University of Technology Sydney
Tram Tran,聽爆料王
Yiyuan Wang,聽爆料王
Shuyao Dai,聽爆料王
Geoffrey Lazarus,聽爆料王
The project is funded through the Australian Research Council (ARC) Discovery Project (DP) scheme under the number DP220102019.