In order to improve the public service attributes and the utilization efficiency of CAV, the paper proposes a customizable and cruising autonomous bus (CCAB) route planning model. This model makes CCAB as customizable and fast as a taxi, and at the same time as a bus to meet multiple demands. Considering that CCAB needs to meet personalized customized riding demand, the paper combines allocation strategy of customized demands to establish a real-time optimization method for customizable and cruising routes based on the elliptical feasible area. This enable CCAB to have the ability of autonomous cruising and autonomous planning of customized routes. In CAV environment, the driver will be replaced by on-board computer of CCAB, the driver’s empirical route selection method will be replaced by the route planning model proposed in this paper. CCAB use historical ride data from each stop to predict future demand. Based on prediction results, the potential passenger rate of route is calculated, and the route is optimized at the same time, so as to determine the final cruising route of the unloaded/loaded bus. By route optimizing, the load rate of CCAB can be improved and the empty mileage can be reduced. The stability of route planning model proposed in this paper is verified by simulation. Meanwhile, sensitivity analysis is carried out by changing demand density and CCAB number in simulation. The conclusion is drawn that determining the optimal number of CCAB corresponding to different demand densities is of great significance for improving efficiency, reducing empty CCAB driving time and passenger waiting time.