## 1 Introduction  
The priority development of public transportation as an important way to alleviate urban traffic congestion has long been a consensus, however, with the continuous development of the transportation industry, the complexity of the urban road traffic operating environment is not what it used to be, so traditional macro-regulation methods have not been able to solve the existing urban road space-time resource supply and demand contradiction. The current methods for public transportation scheduling can be divided into static scheduling and dynamic scheduling. Static scheduling refers to the layout planning and scheduling program of bus routes based on the historical passenger flows of routes, the capacity resources of bus-operating companies, etc., and its execution time is usually annual, quarterly, monthly, etc. [1]. Vehicle departure intervals, via paths and stops, strictly adhere to a pre-established plan and do not consider temporary passenger flow changes or road traffic information changes [2]. Dynamic scheduling is the adjustment of static scheduling during actual operation. It uses a new generation of information technologies, such as vehicle networking and big data, to obtain the real-time situation of passenger flow, road network conditions, and control information and make targeted adjustments to the pre-established scheduling plan. Dynamic scheduling is an important supplement to the traditional static scheduling methods, and when used properly, can effectively improve the level of bus intelligence and service level, so that passengers enjoy a more convenient bus travel experience. Common dynamic scheduling methods include the intelligent optimization of departure time, real-time operation control, and multi-mode combined operation,etc. [3]. Among them, the real-time operation control strategy is an important method for improving the efficiency of vehicle operations and turnover efficiency, which can be divided into the two categories of inter-station control and station control according to the different scope of the influence of the method of implementation. Inter-station control strategies refer to the regulation of the driving process of buses in the zones between stations [4], including interval speed induction, signal priority, etc. [PERSON] and [PERSON] analyzed the mode of action and the improvement effect of traditional control methods on the phenomenon of bus crosstown, and proposed a control scheme that can adaptively improve the cruising speed of this vehicle according to its front and rear speeds, which can automatically compensate for the driver's driving behavior and the effects of traffic delays on the route and has low data requirements [5]. [PERSON] and [PERSON] proposed a bus speed induction method based on a dynamic headway deviation threshold by analyzing vehicle GPS data, which can suppress the increasing trend of headway deviation and improve the reliability of line operations [6]. They proposed a control strategy with two-layer control coefficients, which takes the nonlinear characteristics of the boarding process into consideration and establishes a combined regulation scheme for speed induction in the bus zoning section [7]. [PERSON] et al. theoretically calculated the high and low impacts of individual disturbances and changes in operating status on the stability of the whole bus line, determining the optimal speed control in signalized sections after comparing the optimization effects of multiple strategies [8]. [PERSON] et al. proposed a BRT-applicable rapid pre-detection signal prioritization strategy in order to address the shortcomings of the traditional transit signal priority, and the four simulation scenarios from their experimental results showed that the pre-detection signal prioritization approach with intersection coordination had the best utility, reducing 67.4% of intersection delays and more than 40% of transit delays, with the intersection congestion time for private vehicles being similarly reduced [9].