Self-driving tour market has become an important part of China's domestic tourism market. It is of great theoretical significance to study the spatial extent and structure of urban self-driving tourists' tourism space for enriching and deepening the research on the spatial structure of self-driving tourism. Besides, it has practical value to the tourism destination management organizations' (DMOs) works of marketing, development of self-driving tourism products and implementation of self-driving tourism development strategies. This paper explores the characteristics of tourism space structure of Chinese urban self-driving tourists by analyzing their visits to target scenic spots, based on data of more than 4000 questionnaires obtained from three representative case cities of Beijing, Xi'an and Wuhan, and methods of mathematical statistics, mapping and spatial analysis. The results showed that: (1) The self-driving visiting rate decreases exponentially with the increase of travel distance, and it decreases fast within a range of 400 km. (2) Self-driving tourism space centered on origin city can be divided into three types of zones from the nearby to the distance, which are center zone, diffusion zone and edge zone. Among them, center and diffusion zones are self-driving tourism space with important tourism market value. (3) The size of self-driving tourism space varies in different origin cities. Self-driving tourism space radiuses of Beijing, Xi'an and Wuhan measured by travel distance are respectively 1665 km, 1196 km, and 1176 km. The radius of self-driving tourism center zone in all the three cities is about 400 km. (4) With 4 h and 6 h as the time threshold, self-driving tourism space can be divided into comfort space (within 4 h) and fatigue space (over 4 h), which can be further divided into mild fatigue space (4-6 h) and severe fatigue space (over 6 h). The comfort space corresponds to the center zone while the fatigue space corresponds to the diffusion zone, and the mild fatigue space corresponds to the transitional belt between the center and the diffusion zones. In this study, the tourism space structure of urban self-driving tourists is summarized as a “wheel hub” model, which provides a cognitive framework for studying the spatial structure of self-driving tourism.