## 1 Introduction  
With the development and application of advanced technologies such as communication and microelectronics, the concept of smart city arises at the right moment. Smart city has a much broader definition, which includes almost every aspect in human beings' life, e.g., smart medical, smart energy, smart traffic, and smart home. As a form of intelligent transport, the shared bicycle, also known in some references as bicycle-sharing [1; 2; 3; 4], is about 55 years old and has four generations. The shared bicycle is thriving in smart cities especially in recent years and most of them have been successful. There are three clear benefits on the shared bicycle [5], as follows:  
* It is an utter green path that can reduce environmental effects, regulate air pollution, and effectively save money. There are no exhaust emissions that are dangerous for the atmosphere without fossil fuel consumption. Since cycling is a form of physical practice, both the community and users benefit from the shared bicycle. * For the last mile journey, it provides the perfect solution. Actually, on long-distance journeys, many citizens do not prefer cycling today. However, given that, in most instances, the range of metro or bus stations and commercial or residential communities is not that long, shared bicycles are most cost-efficient and suitable for people for short distances. * The urban market is a typical example of public resource-shared operation, capable of improving the cycling usage rate. Today, increasing numbers of people favor shared bicycles than their conventional private bicycles. The traffic pressure will, therefore, be helpful. Referring to [5], [PERSON] et al. first divided the development process of the shared bicycle into four phases, and suggested the Internet of Shared Bicycle (IoSB) concept. With the advent of many new technologies such as QR Code or LTE, the fourth-generation connected bicycle [6; 7], called one form of intelligent hardware, has evolved so rapidly over the past few years. Most significantly, the change from the pile-parking mode to the pile-less parking mode of shared bicycles is a new attempt and also a double-edged sword. Great convenience comes at the expense of unnecessary supply of shared bicycles which usually manifests as too many bicycles being left unused or too few bicycles to meet demands. Insufficient timely and reasonable bicycle scheduling trigger two extreme situations above and may affect the social order. To address and resolve the above-mentioned problems, this paper proposed a hybrid dispatch scheme based on demand forecasting data. This hybrid dispatch system combines manual dispatch and user reward dispatch. Firstly, according to the travel records of Mobike, we divided the city into many travel zones. Afterward, we pick one of the travel areas for study in this paper and choose a certain number of bicycle travel points in the research area using the clustering technique. Instead, at the next time of the mutual bicycle travel point, we use Autoregressive Moving Average (ARMA) to predict bicycle demand. Subsequently, referring to the travel point forecast data, we established the manual and user incentive hybrid dispatch strategy based on the greedy strategy to ensure the lowest degree of equilibrium of all bicycle travel points in the study area after each dispatch. Finally, we take user satisfaction and total revenues of shared bicycle operators as evaluation indicators and carry out a simulation analysis of the hybrid dispatching strategy proposed in this paper. The key contents of this paper are structured as follows: Section 2 presents some study directions concerning the shared bicycle at home and abroad; Section 3 illustrates the entire shared bicycle dispatching scenario and framework; Section 4 introduces the concept of manual dispatch and user incentive dispatching suggested in this paper respectively. Section 5 describes the setting of experimental parameters, input data, and experimental methods, and analyzes the results of the experiment.