An automated system for the analysis of road safety and conditions

该项目旨在开发一个自动化系统，用于分析道路安全和状况。数字视频道路数据每年在昆士兰州的每一条州道上收集，并有可能为更安全的道路提供一系列增值产品。该项目将开发基于深度学习的神经网络技术，可以学习和分类路边物体，以便自动分析视频数据，从而估计物体的接近程度，以实现道路安全和评级。预期成果将是新的识别技术和软件，可与道路数据收集系统相结合。

This project aims to develop an automated system for the analysis of road safety and conditions. Digital video road data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project will develop deep learning based neural network techniques which can learn and classify roadside objects so that video data can be automatically analysed allowing the estimation of the proximity of objects for road safety and rating. The expected outcome will be new identification techniques and software which can be incorporated with road data collection systems.