| Title |
Dynamic Pricing For Parking Facility |
| ID_Doc |
21353 |
| Authors |
Deng D.; Leung C.K.; Pazdor A.G.M. |
| Year |
2023 |
| Published |
Lecture Notes on Data Engineering and Communications Technologies, 182 |
| DOI |
http://dx.doi.org/10.1007/978-3-031-40971-4_13 |
| Abstract |
Urbanization benefits residents of urban cities and the modern society. However, public resources—such as parking facility—can be limited. A solution is to make good use of dynamic pricing, which can help adjust the available resources. For instance, dynamic pricing for parking facility helps maximize parking resource utilization and optimize the parking revenue. In this paper, we present a dynamic pricing solution for parking facility. It utilizes available public resources and optimizes revenue with predefined restrictions. This solution that adapts reinforcement learning in predicting pricing. It also handles price restrictions. Evaluation results show the effectiveness and practicality of our solution in dynamic pricing for parking facility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| Author Keywords |
big data; collaborative systems; constraints; data analytics; data mining; data science; dynamic pricing; Intelligent networking; machine learning; parking; prediction; reinforcement learning; smart city |
