Abstract <p>Autonomous driving has emerged as a prominent research and application area in recent times. The planning module in autonomous driving systems processes complex data from various modules to generate the driving route planned for a vehicle, which is crucial for the safety and reliability of the system. Therefore, finding suitable evaluation factors to analyze the planning module and the planned route is essential for reflecting the performance of vehicles in autonomous driving. However, due to the diversity of the data and the complexity of evaluation factors and methods, evaluating the planning module has always been a challenge for developing the autonomous driving system. Our research primarily focuses on the planning module, which evaluates its performance in various simulated scenarios based on factors such as comfort, security, stability, reliability, and latency. We analyze the decision-making process and reveal reasons behind the decisions through data flow diagrams of the module, simulated scenario diagrams, overhead views of surrounding obstacles, the overview of planning results, and internal planning diagrams with path and speed details. The system aims to provide developers with a clear understanding of vehicle planning issues and offer suggestions for improvement, thereby enhancing the performance and reliability of autonomous driving systems and advancing the development of autonomous driving technologies.</p> Graphical abstract <p></p>