At present, unmanned vehicle (UV) to provide the accurate navigation under motion are in majority cases depended on GPS, what makes the access to the Network of importance for correct performance in the smart city environment. To implement the smart city conception, the search of alternative techniques of UV localization is vital, since in real conditions GPS signal may be either absent, or its accuracy may be found insufficient to move over a route or to implement maneuvers. One should note that there exist problems for putting in operation the UV technologies: ethical (confidentiality and trust) and cybersecurity. Since in the smart city environment all UVs are to be connected to the Network, then cybersecurity issues also require an additional attention. Cyber threats can provoke violations in both individual UVs and the transportation system as a whole. The paper emphasizes three main categories of UV program systems providing, correspondingly, sampling and processing data, planning, and control. An approach to the UV performance architecture is presented, based on the sampling and processing data, decision making, network and computational multi-level analytics. To increase the UV security in a smart city, the paper proposes to utilize a safety management system based on the factor analysis and risks calculation techniques. To increase the UV security in the part of unobstructed motion, local positioning network models are proposed enabling to work out motion schemes.