Reward Distribution Using an Anti-Duality Game in a Point Cloud Data Trading Model Based on Collected Area

Digital Twin is expected to be a key technology for realizing the next-generation smart city. It can be applied to social infrastructure, manufacturing, and medical fields. This paper focuses on “Digital Twin City”, which collects all kinds of data in a city and uses it for public services such as transportation, disaster prevention and urban planning, thereby improving the quality of life for residents. Three-dimensional urban landscapes formed by point cloud data are essential for the development of public services and other services in Digital Twin City. However, installing sensors and collecting fresh data from every corner of the city involves high initial and maintenance costs. Therefore, involving residents in data collection is considered a promising option. To create incentives for residents to participate as data providers, we propose a data trading cooperation game based on coalitional game. As a characteristic function of the game, an anti-duality game of airport game that solves the already known cost allocation problem is used, which corresponds to the reward distribution problem in this paper. In the numerical example, the distribution of reward is determined around Nucleolus, which is the allocation that minimizes the maximum excess of data providers.