The increasing availability of vehicular trajectory data is at the core of smart mobility solutions. Such data offer us unprecedented information for the development of trajectory data mining-based applications. An essential task of trajectory analysis is the employment of efficient and accurate methods to compare trajectories. This work presents a systematic survey of vehicular trajectory similarity measures and provides a panorama of the research field. First, we show an overview of vehicle trajectory data, including the models and some preprocessing techniques. Then, we give a comprehensive review of methods to compare trajectories and their intrinsic properties. We classify the methods according to the trajectory representation and features such as metricity, computational complexity, and robustness to noise and local time shift. Last, we discuss the applications of vehicular trajectory similarity measures and some open research problems.

中文翻译：

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车辆轨迹相似度

越来越多的车辆轨迹数据可用性是智能移动解决方案的核心。这些数据为我们开发基于轨迹数据挖掘的应用程序提供了前所未有的信息。轨迹分析的一项基本任务是使用有效和准确的方法来比较轨迹。这项工作对车辆轨迹相似性度量进行了系统调查，并提供了研究领域的全景。首先，我们展示了车辆轨迹数据的概述，包括模型和一些预处理技术。然后，我们全面回顾了比较轨迹及其内在特性的方法。我们根据轨迹表示和特征对方法进行分类，例如度量、计算复杂性以及对噪声和局部时移的鲁棒性。最后的，