## 5 Conclusions  
This paper discusses, in detail, the application scenarios and implementation modes of dynamic bus scheduling means represented by stop-skipping control and local path optimization. Based on the organic combination of multiple control strategies, a dynamic optimization model for single-line bus operations is constructed, which makes up for the shortcomings of general scheduling methods and further realizes the dynamic optimization adjustment of the local reasonable amplitude of the vehicle operation path on the basis of the traditional means of crossing stations. The results obtained from this model have a good usability, which can effectively improve the average traveling speed of buses, shorten the overall waiting time of passengers, and enhance the line operation efficiency. The implementation of the model relies on real-time data processing and transmission technologies, therefore requiring a certain level of technological development in the cities where the bus routes are located. Meanwhile, the algorithm comparison experiment shows that the introduction of the simulated annealing idea can make the conventional genetic algorithm obtain a better performance in terms of iteration speed and optimal solution quality, thus verifying the advanced nature of the hybrid algorithm. In addition, the calculation results of the model can also be used as a reference basis for the evaluation and optimization adjustment of bus lines and stations, providing auxiliary judgment for scheduling operators.  
Due to the limitations of the experimental conditions and the researcher's technical level, there are still some problems that need to be improved in further studies in the future:  
1. The dynamic optimization program used in the single-route bus is mainly based on the stop-skipping control strategy. Although the example results prove that this method can effectively reduce the average travel time and waiting time of passengers, the impact of vehicle crossing on individual passengers' willingness to ride is difficult to completely eliminate.
2. The optimization model only considered a single-line bus, but in reality, multiple lines with public routes and stops will have mutual interference with each other, affecting the optimization effect of the scheduling scheme. In the future, the interactions between other lines and this line can be considered to be included in the research scenarios for quantification and modeling, so that the model can be closer to the real operating environment and the applicability of the model can be improved.  
Conceptualization, X.Z. ([PERSON]); methodology, H.G.; software, H.G.; validation, X.Z. ([PERSON]); resources, X.Z. ([PERSON]); data curation, H.G. and B.L.; writing--original draft preparation, H.G.; writing--review and editing, X.Z. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This research was funded by Natural Science Foundation of China (No. 52372318).  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.