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Title	A Survey Of Urban Drive-By Sensing: An Optimization Perspective
ID_Doc	5200
Authors	Ji W.; Han K.; Liu T.
Year	2023
Published	Sustainable Cities and Society, 99
DOI	http://dx.doi.org/10.1016/j.scs.2023.104874
Abstract	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. © 2023 Elsevier Ltd
Author Keywords	Crowdsensing; Drive-by sensing; Optimization; Smart cities; Vehicle mobility

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