With the rapid and advanced development of high-speed railway (HSR) in China, enhancing the coordinated adaptability of HSR train stop planning and timetabling while improving operational precision has become increasingly critical. To address this, this paper tackles the limitations of existing collaborative optimization approaches. Most conventional methods rely on two-stage models-an approach prone to goal misalignment and local optima. Therefore, this paper resolves the aforementioned issues by integrating the two stages into a single optimization phase. Specifically, it takes into account the impacts of train types and stop-start additional time on the optimization scheme, adopts inter-station origin-destination (OD) accessibility to indirectly characterize the demand for passenger flow exchange, and formulates departure time rules to maintain the stability of the train timetable structure. A multi-objective collaborative optimization model is developed, considering constraints such as station service frequency and safety intervals, with objectives including minimizing total train travel time, total number of stops, and the deviation between actual and expected departure times at the origin station. An empirical study was conducted on the 58 downbound trains of the Wuhan-Guangzhou HSR in June 2025 ,using solver Gurobi Results indicated reductions in total train travel time and total stops by 2.6% and 3.5%, respectively, and a reduction of 13 overtaking events. This optimization improves accessibility between lower-tier nodes while maintaining service stability at higher-tier nodes, leading to enhanced operational efficiency, service quality, and safety. It provides valuable guidance for high-speed railway operators in developing integrated stop plans and timetables.