Information Fusion for Tracking Objects in Large-Scale Sensor Network

该项目旨在开发一个数学框架来结合来自多个传感器的多模态信息。这些移动传感器将在空间上分布在一个大范围的区域，以实现多目标跟踪。该框架的主要应用是智能决策的协同感知。预期的结果包括一种新的技术，可以整合来自多个移动代理（例如车辆）的接收信息，以增强它们在动态环境中预测情况的能力，并有效地采取行动以提高安全性。这将为合作式自动驾驶的发展带来好处，以提高道路安全。

This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.