Data visualization tool for monitoring transit operation and performance

Abdullah Kurkcu, Fabio Miranda, Kaan Ozbay, Claudio Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Using the automated vehicle location data combined with other technologies such as automated incident reporting, transit decision makers can now execute a variety of real-time strategies and performance evaluations. In this study, we show that it is possible to develop an easy to use but powerful web-based tool which acquires, stores, processes, and visualizes bus trajectory data. The developed web-based tool makes it easy for the end users to access stored data and to query it without any delay or external help. Moreover, the tool allows the users to conduct a series of data visualization and analysis operations demonstrating the potential of a such web-based tool for future applications.

Original languageEnglish (US)
Title of host publication5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages598-603
Number of pages6
ISBN (Electronic)9781509064847
DOIs
StatePublished - Aug 8 2017
Event5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Naples, Italy
Duration: Jun 26 2017Jun 28 2017

Other

Other5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017
CountryItaly
CityNaples
Period6/26/176/28/17

Fingerprint

Data visualization
Data Visualization
visualization
Monitoring
Web-based
monitoring
performance
data access
Performance Evaluation
decision maker
Data analysis
incident
Trajectories
Trajectory
Query
Real-time
Series
evaluation

Keywords

  • data analysis
  • GPS bus data
  • performance measures
  • travel time
  • visualization
  • web-based tools

ASJC Scopus subject areas

  • Modeling and Simulation
  • Transportation
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Kurkcu, A., Miranda, F., Ozbay, K., & Silva, C. (2017). Data visualization tool for monitoring transit operation and performance. In 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings (pp. 598-603). [8005584] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MTITS.2017.8005584

Data visualization tool for monitoring transit operation and performance. / Kurkcu, Abdullah; Miranda, Fabio; Ozbay, Kaan; Silva, Claudio.

5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 598-603 8005584.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kurkcu, A, Miranda, F, Ozbay, K & Silva, C 2017, Data visualization tool for monitoring transit operation and performance. in 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings., 8005584, Institute of Electrical and Electronics Engineers Inc., pp. 598-603, 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017, Naples, Italy, 6/26/17. https://doi.org/10.1109/MTITS.2017.8005584
Kurkcu A, Miranda F, Ozbay K, Silva C. Data visualization tool for monitoring transit operation and performance. In 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 598-603. 8005584 https://doi.org/10.1109/MTITS.2017.8005584
Kurkcu, Abdullah ; Miranda, Fabio ; Ozbay, Kaan ; Silva, Claudio. / Data visualization tool for monitoring transit operation and performance. 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 598-603
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