Los angeles metro bus data analysis using GPS trajectory and schedule data

Kien Nguyen; Jingyun Yang; Yijun Lin; Jianfa Lin; Yao Yi Chiang; Cyrus Shahabi

doi:10.1145/3274895.3274911

Los angeles metro bus data analysis using GPS trajectory and schedule data

Kien Nguyen, Jingyun Yang, Yijun Lin, Jianfa Lin, Yao Yi Chiang, Cyrus Shahabi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

With the widespread installation of location-enabled devices on public transportation, public vehicles are generating massive amounts of trajectory data in real time. However, using these trajectory data for meaningful analysis requires careful considerations in storing, managing, processing, and visualizing the data. Using the location data of the Los Angeles Metro bus system, along with publicly available bus schedule data, we conduct a data processing and analyses study to measure the performance of the public transportation system in Los Angeles utilizing a number of metrics including travel-time reliability, on-time performance, bus bunching, and travel-time estimation. We demonstrate the visualization of the data analysis results through an interactive web-based application. The developed algorithms and system provide powerful tools to detect issues and improve the efficiency of public transportation systems.

Original language	English (US)
Title of host publication	26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018
Editors	Li Xiong, Roberto Tamassia, Kashani Farnoush Banaei, Ralf Hartmut Guting, Erik Hoel
Publisher	Association for Computing Machinery
Pages	560-563
Number of pages	4
ISBN (Electronic)	9781450358897
DOIs	https://doi.org/10.1145/3274895.3274911
State	Published - Nov 6 2018
Externally published	Yes
Event	26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018 - Seattle, United States Duration: Nov 6 2018 → Nov 9 2018

Publication series

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

Other

Other	26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018
Country/Territory	United States
City	Seattle
Period	11/6/18 → 11/9/18

Bibliographical note

Publisher Copyright:
© 2018 held by the owner/author(s).

Keywords

GPS bus
GPS trajectory
Map matching
Public transportation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1145/3274895.3274911

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Cite this

Nguyen, K., Yang, J., Lin, Y., Lin, J., Chiang, Y. Y., & Shahabi, C. (2018). Los angeles metro bus data analysis using GPS trajectory and schedule data. In L. Xiong, R. Tamassia, K. F. Banaei, R. H. Guting, & E. Hoel (Eds.), 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018 (pp. 560-563). (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). Association for Computing Machinery. https://doi.org/10.1145/3274895.3274911

Los angeles metro bus data analysis using GPS trajectory and schedule data. / Nguyen, Kien; Yang, Jingyun; Lin, Yijun et al.
26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018. ed. / Li Xiong; Roberto Tamassia; Kashani Farnoush Banaei; Ralf Hartmut Guting; Erik Hoel. Association for Computing Machinery, 2018. p. 560-563 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nguyen, K, Yang, J, Lin, Y, Lin, J, Chiang, YY & Shahabi, C 2018, Los angeles metro bus data analysis using GPS trajectory and schedule data. in L Xiong, R Tamassia, KF Banaei, RH Guting & E Hoel (eds), 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, Association for Computing Machinery, pp. 560-563, 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018, Seattle, United States, 11/6/18. https://doi.org/10.1145/3274895.3274911

Nguyen K, Yang J, Lin Y, Lin J, Chiang YY, Shahabi C. Los angeles metro bus data analysis using GPS trajectory and schedule data. In Xiong L, Tamassia R, Banaei KF, Guting RH, Hoel E, editors, 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018. Association for Computing Machinery. 2018. p. 560-563. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). doi: 10.1145/3274895.3274911

Nguyen, Kien ; Yang, Jingyun ; Lin, Yijun et al. / Los angeles metro bus data analysis using GPS trajectory and schedule data. 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2018. editor / Li Xiong ; Roberto Tamassia ; Kashani Farnoush Banaei ; Ralf Hartmut Guting ; Erik Hoel. Association for Computing Machinery, 2018. pp. 560-563 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).

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abstract = "With the widespread installation of location-enabled devices on public transportation, public vehicles are generating massive amounts of trajectory data in real time. However, using these trajectory data for meaningful analysis requires careful considerations in storing, managing, processing, and visualizing the data. Using the location data of the Los Angeles Metro bus system, along with publicly available bus schedule data, we conduct a data processing and analyses study to measure the performance of the public transportation system in Los Angeles utilizing a number of metrics including travel-time reliability, on-time performance, bus bunching, and travel-time estimation. We demonstrate the visualization of the data analysis results through an interactive web-based application. The developed algorithms and system provide powerful tools to detect issues and improve the efficiency of public transportation systems.",

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AU - Shahabi, Cyrus

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AB - With the widespread installation of location-enabled devices on public transportation, public vehicles are generating massive amounts of trajectory data in real time. However, using these trajectory data for meaningful analysis requires careful considerations in storing, managing, processing, and visualizing the data. Using the location data of the Los Angeles Metro bus system, along with publicly available bus schedule data, we conduct a data processing and analyses study to measure the performance of the public transportation system in Los Angeles utilizing a number of metrics including travel-time reliability, on-time performance, bus bunching, and travel-time estimation. We demonstrate the visualization of the data analysis results through an interactive web-based application. The developed algorithms and system provide powerful tools to detect issues and improve the efficiency of public transportation systems.

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ER -

Los angeles metro bus data analysis using GPS trajectory and schedule data

Abstract

Publication series

Other

Bibliographical note

Keywords

UN SDGs

Publisher link

Find It

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