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Smart city article details
| Title | Design Of Parking Resource Intensive Management System In Smart City |
|---|---|
| ID_Doc | 18909 |
| Authors | Zhou S.; Liu X.; Cheng X.; Zhao Z.; Wang J.; Wei R.; Xiao T. |
| Year | 2025 |
| Published | Lecture Notes in Electrical Engineering, 1411 LNEE |
| DOI | http://dx.doi.org/10.1007/978-981-96-4967-9_147 |
| Abstract | Due to the outdated management methods of the existing parking lots in many cities, the turnover efficiency of parking spaces is very low, and unified coordination and overall planning cannot be carried out. Although some parking lots through intelligent upgrade means to achieve automatic charging, parking guidance and other functions, but it can not fundamentally solve the problem of inefficient parking lot operation. On the other hand, with the rapid development of internet of vehicles, assisted driving, automated parking, unmanned driving and other technologies are gradually becoming the standard equipment of vehicles, which can provide high-level parking services in closed roads or closed stations and other scenarios. It will change the future parking methods, improve the city's intelligent service level. Therefore, combined with the new technologies including big data, fifth-generation mobile communication (5G), IoT, and IoV, this paper proposes the parking resource intensive management system (PRIMS).Through the “city-level” intelligent parking management platform system, it carries and integrates dynamic and static data of multiple parking lots in the city, analyzes and schedules various parking resources, and realizes unified planning and reasonable scheduling, defines different levels of intelligent standards, and gradually realizes fully automated, intelligent and unmanned parking management, becoming a part of future travel services. At the same time, it provides auxiliary support for urban development planning and improves the smart level of cities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. |
| Author Keywords | Automated parking; Parking management; Smart city |
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