trajdata：多個人類軌跡數據集的統一接口

摘要

近年來，軌跡預測領域有了顯著的增長，部分原因是由於釋出了許多大規模、真實世界的人類軌跡數據集，用於自動駕駛車輛（AVs）和行人運動跟踪。儘管這些數據集對社群來說是一大福音，但它們各自使用自定義和獨特的數據格式和應用程序接口（API），使研究人員在多個數據集上訓練和評估方法變得繁瑣。為了解決這個問題，我們提出了trajdata：一個統一的接口，用於多個人類軌跡數據集。在其核心，trajdata提供了一個簡單、統一和高效的軌跡和地圖數據表示和應用程序接口。作為其功能的展示，在這項工作中，我們對現有的軌跡數據集進行了全面的實證評估，為用戶提供了對支撐當前大部分行人和AV運動預測研究的數據有豐富理解，並根據這些見解提出了未來數據集的建議。trajdata採用寬鬆的許可（Apache 2.0），可在線上訪問https://github.com/NVlabs/trajdata。

English

The field of trajectory forecasting has grown significantly in recent years, partially owing to the release of numerous large-scale, real-world human trajectory datasets for autonomous vehicles (AVs) and pedestrian motion tracking. While such datasets have been a boon for the community, they each use custom and unique data formats and APIs, making it cumbersome for researchers to train and evaluate methods across multiple datasets. To remedy this, we present trajdata: a unified interface to multiple human trajectory datasets. At its core, trajdata provides a simple, uniform, and efficient representation and API for trajectory and map data. As a demonstration of its capabilities, in this work we conduct a comprehensive empirical evaluation of existing trajectory datasets, providing users with a rich understanding of the data underpinning much of current pedestrian and AV motion forecasting research, and proposing suggestions for future datasets from these insights. trajdata is permissively licensed (Apache 2.0) and can be accessed online at https://github.com/NVlabs/trajdata

trajdata：多個人類軌跡數據集的統一接口

trajdata: A Unified Interface to Multiple Human Trajectory Datasets

摘要

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