Towards in-vehicle situation awareness using visual and audio sensors

该项目旨在利用内部安装的传感器的视觉和音频线索来表征司机的意识、活动以及与其他车辆乘员的互动。据估计，交通事故每年给澳大利亚造成300亿美元的损失，并造成数千人悲惨的生命损失，但绝大多数严重的车祸都与司机疲劳或分心有关。预期的项目成果包括先进的人工智能，以推断和预测危险的司机和乘客行为。这有可能极大地造福社会，因为它提高了自动驾驶能力，减少了司机引发的事故和死亡，确保每一位司机、乘客和行人在一天结束时都能安全到达家。

This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.