发表机构
Department of Electrical and Computer Engineering, University of Patras（帕特雷大学电气与计算机工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对城市危机与出行场景中数据碎片化、态势感知不足的问题，提出一种AI驱动XR平台，融合多源数据并通过AR仪表板实现实时监控与交互，提升决策、协调与安全。
AI 中文摘要
城市环境日益面临复杂、动态且相互依存的风险，从交通事件和基础设施故障，到极端天气事件和应急响应场景等大规模危机。在此类条件下，决策者和操作人员必须在时间紧迫的约束下行动，同时依赖零散、异构且往往不完整的信息。缺乏统一的态势感知，加之可见性有限和系统相互孤立，显著影响了响应时间、协调效率和整体运营效能。与此同时，现代城市已部署了广泛的基础设施传感网络，包括监控摄像头网络、物联网设备、联网车辆和基于卫星的观测系统。尽管这些技术产生了海量数据，但由于缺乏能够实现实时数据融合、智能解读和直观可视化的集成平台，其利用仍然有限。因此，在数据可用性与可操作情报之间，尤其是在安全关键和危机管理应用中，仍存在显著差距。为解决这一挑战，本文提出了一种面向城市危机管理与智能出行运营的AI驱动XR态势感知与操作平台。该系统集成了来自城市基础设施、联网车辆和弱势道路使用者（VRUs）的数据，能够全面实时地理解城市环境。通过统一的操作仪表板和增强现实（AR）界面，该平台支持集中监控和现场级交互。通过增强感知、实现协作感知并提供情境感知信息，所提方法改善了多样化城市场景中的决策、协调与安全性。
英文摘要
Urban environments are increasingly exposed to complex, dynamic, and interdependent risks, ranging from traffic incidents and infrastructure failures to large-scale crises such as extreme weather events and emergency response scenarios. In such conditions, decision-makers and operators are required to act under time-critical constraints while relying on fragmented, heterogeneous, and often incomplete information. The lack of unified situational awareness, combined with limited visibility and disconnected systems, significantly affects response time, coordination efficiency, and overall operational effectiveness. In parallel, modern cities have deployed extensive sensing infrastructures, including surveillance camera networks, IoT devices, connected vehicles, and satellite-based observation systems. Although these technologies generate vast amounts of data, their exploitation remains limited due to the absence of integrated platforms capable of real time data fusion, intelligent interpretation, and intuitive visualization. As a result, a substantial gap persists between data availability and actionable intelligence, particularly in safety-critical and crisis management applications. To address this challenge, this paper presents an AI-driven XR situational awareness and operational platform designed for urban crisis management and smart mobility operations. The proposed system integrates data from city infrastructure, connected vehicles, and VRUs, enabling a comprehensive and real-time understanding of the urban environment. Through a unified operational dashboard and AR interfaces, the platform supports both centralized monitoring and field-level interaction. By enhancing perception, enabling cooperative awareness, and delivering context-aware information, the proposed approach improves decision-making, coordination, and safety across diverse urban scenarios.
