The field of autonomous driving and urban mobility is rapidly evolving, with a focus on developing more sophisticated and safety-critical systems. Recent research has emphasized the importance of evaluating prediction models under complex, interactive, and safety-critical driving scenarios, highlighting the need for more comprehensive evaluation frameworks. Additionally, there is a growing interest in simulating realistic mobility and traffic patterns, with a focus on capturing cross-modal dynamics and developing unified frameworks for joint simulation of mobile traffic and user trajectories. Noteworthy papers in this area include Beyond ADE and FDE: A Comprehensive Evaluation Framework for Safety-Critical Prediction in Multi-Agent Autonomous Driving Scenarios, which proposes a novel testing framework for evaluating prediction performance under diverse scene structures, and Multi-Scale Diffusion Transformer for Jointly Simulating User Mobility and Mobile Traffic Pattern, which introduces a Multi-Scale Diffusion Transformer for joint simulation of mobile traffic and user trajectories. Other notable papers, such as Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling and Future-Aware End-to-End Driving: Bidirectional Modeling of Trajectory Planning and Scene Evolution, demonstrate significant advancements in autonomous driving planning and end-to-end driving methods.