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LibCity: An Open Library for Traffic Prediction

  • Peng Cheng Laboratory
  • Beihang University
  • Gaoling School of Artificial Intelligence

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the increase of traffic prediction models, there has become an urgent need to develop a standardized framework to implement and evaluate these methods. This paper presents LibCity, a unified, comprehensive, and extensible library for traffic prediction, which provides researchers with a credible experimental tool and a convenient development framework. In this library, we reproduce 42 traffic prediction models and collect 29 spatial-temporal datasets, which allows researchers to conduct comprehensive experiments in a convenient way. To accelerate the development of new models, we design unified model interfaces based on unified data formats, which effectively encapsulate the details of the implementation. To verify the effectiveness of our implementations, we also report the reproducibility comparison results of LibCity, and set up a performance leaderboard for the four kinds of traffic prediction tasks. Our library will contribute to the standardization and reproducibility in the field of traffic prediction. The open source link of LibCity is https://github.com/LibCity/Bigscity-LibCity.

Original languageEnglish
Title of host publication29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
EditorsXiaofeng Meng, Fusheng Wang, Chang-Tien Lu, Yan Huang, Shashi Shekhar, Xing Xie
PublisherAssociation for Computing Machinery
Pages145-148
Number of pages4
ISBN (Electronic)9781450386647
DOIs
StatePublished - 2 Nov 2021
Event29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021 - Virtual, Online, China
Duration: 2 Nov 20215 Nov 2021

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Conference

Conference29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
Country/TerritoryChina
CityVirtual, Online
Period2/11/215/11/21

Keywords

  • Reproducibility
  • Spatial-temporal System
  • Traffic Prediction

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