轨迹计算是一个关键研究领域，涵盖轨迹数据管理与挖掘，在位置服务、城市交通和公共安全等实际应用中具有重要作用，因而受到广泛关注。传统方法主要依赖简单的时空特征，面临计算复杂、可扩展性有限以及难以适应现实世界复杂性等挑战。本文全面综述了轨迹计算从深度学习到近期大语言模型（LLM）阶段的发展脉络与最新进展。首先，我们定义轨迹数据，并简要介绍常用的深度学习模型；继而系统梳理深度学习在轨迹管理（预处理、存储、分析与可视化）与轨迹挖掘（轨迹相关预测、轨迹相关推荐、轨迹分类、行程时间估计、异常检测及移动性生成）中的应用。此外，我们探讨了以基础模型（foundation models）和大语言模型为代表的大型模型在轨迹计算中的新兴研究方向与最新进展，这些进展有望重塑下一代轨迹计算范式。文中还总结了典型应用场景、公开数据集及工具包。最后，我们归纳了当前轨迹计算研究面临的主要挑战，并提出未来研究方向。相关论文与开源资源已整理汇总，并持续更新于：https://github.com/yoshall/Awesome-Trajectory-Computing。

Trajectory computing is a pivotal domain encompassing trajectory data management and mining, garnering widespread attention due to its crucial role in various practical applications such as location services, urban traffic, and public safety. Traditional methods, focusing on simplistic spatio-temporal features, face challenges of complex calculations, limited scalability, and inadequate adaptability to real-world complexities. In this paper, we present a comprehensive review of the development and recent advances in trajectory computing, from deep learning to the more recent large language models. We first define trajectory data and provide a brief overview of widely-used deep learning models. Systematically, we explore deep learning applications in trajectory management (pre-processing, storage, analysis, and visualization) and mining (trajectory-related forecasting, trajectory-related recommendation, trajectory classification, travel time estimation, anomaly detection, and mobility generation). Furthermore, we discuss emerging research directions and recent advancements in large models (represented by foundation models and large language models) for trajectory computing, which promise to reshape the next generation of trajectory computing. Additionally, we summarize application scenarios, public datasets, and toolkits. Finally, we outline current challenges in trajectory computing research and propose future directions. Relevant papers and open-source resources have been collated and are continuously updated at: https://github.com/yoshall/Awesome-Trajectory-Computing.