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.

翻译：普及化移动感知是智慧交通与智慧城市应用的核心组成部分。基于车辆移动的感知技术（即车载感知）正逐渐成为学术研究与实际应用中的热点。该感知范式天然包含交通成分，因为传感器的时空分布与其载体（可能包括第三方车辆如出租车、公交车，或雇佣车辆如无人机与专用车辆）的移动模式密切相关。因此，理解、评估并优化车辆车队在多类城市感知场景下的感知能力至关重要。为此，本文通过四步讨论框架，从优化视角总结已有文献：（1）量化感知质量（目标层）；（2）评估不同车队的感知能力（战略层）；（3）传感器部署（战略/战术层）；（4）车辆机动控制（战术/操作层）。通过系统整合研究成果与实践经验，本综述不仅凸显了车载感知的优化维度，更为配置与部署基于车辆的城市感知系统提供了实用指南。