城市驶过感知综述：优化视角
A survey of urban drive-by sensing: An optimization perspective
AI总结：
本文从优化视角综述了城市驶过感知，提出量化感知质量、评估车队感知力、传感器部署和车辆机动四步框架，为配置基于车辆的城市感知系统提供实用指南。
摘要：
普适与移动感知是智能交通和智慧城市应用的重要组成部分。基于车辆的移动感知，或称驶过感知（DS），在学术研究和现场实践中日益受到欢迎。DS范式具有内在的交通属性，因为传感器的时空分布与其宿主的移动模式密切相关，这些宿主可能包括第三方（如出租车、公交车）或租赁（如无人机和专用车辆）车辆。因此，在广泛的城市感知场景下理解、评估和优化车队感知能力至关重要。为此，本文从优化导向对近期文献进行了总结，提出了四步讨论：(1)量化感知质量（目标）；(2)评估各类车队的感知能力（战略）；(3)传感器部署（战略/战术）；(4)车辆机动（战术/操作）。通过这种方式汇编研究发现和实践见解，本综述不仅突出了驶过感知的优化方面，也为配置和部署基于车辆的城市感知系统提供了实用指南。
英文摘要：
Pervasive and mobile sensing is an integral part of smart transport and smart city applications. Vehicle-based mobile sensing, or drive-by sensing (DS), is gaining popularity in both academic research and field practice. The DS paradigm has an inherent transport component, as the spatial-temporal distribution of the sensors are closely related to the mobility patterns of their hosts, which may include third-party (e.g. taxis, buses) or for-hire (e.g. unmanned aerial vehicles and dedicated vehicles) vehicles. It is therefore essential to understand, assess and optimize the sensing power of vehicle fleets under a wide range of urban sensing scenarios. To this end, this paper offers an optimization-oriented summary of recent literature by presenting a four-step discussion, namely (1) quantifying the sensing quality (objective); (2) assessing the sensing power of various fleets (strategic); (3) sensor deployment (strategic/tactical); and (4) vehicle maneuvers (tactical/operational). By compiling research findings and practical insights in this way, this review article not only highlights the optimization aspect of drive-by sensing, but also serves as a practical guide for configuring and deploying vehicle-based urban sensing systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
