The autonomous vehicles (AVs) in smart city, as intelligent mobile robots, are expected to provide diversified services to facilitate the life of citizens. However, the attributes of the services requested by users are different and the statuses of the AVs managed by different central servers are dynamically changed. To execute the services with the minimum cost based on the requirements of users and the statuses of AVs therefore becomes a challenge. In this article, we establish an intelligent multi-attribute service response framework in smart city based on the request of users and the response of AVs. In the first phase of the framework, each central server decides the minimum service execution cost (SEC) to respond to the user's service by considering the available resources of its AVs, where the minimization problems are formulated for the services with one attribute and the services with multiple attributes, respectively. To address the problems, the optimal AV selection (OAVS) algorithm for the services with one attribute and the OAVS-M algorithm for the services with multiple attributes are designed. In the second phase, based on the SEC of each central server, an auction game is developed to model the competition among the central servers to help the user select the optimal one to execute the service with the lowest service transaction price (STP). By achieving the Nash equilibrium of the game, the optimal strategy of each central server to win the chance for executing the service is obtained. The simulation results show that the designed framework can reduce the STP compared with the conventional schemes.