Integrating Traffic Datasets for Evaluating Road Networks

Ariel Gupta, Ajay Bansal

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

Abstract

Improving the safety of roads has traditionally been approached by governmental agencies including the National Highway Traffic Safety Administration and State Departments of Transportation. In past literature, automobile crash data is analyzed using time-series prediction techniques to identify road segments and/or intersections likely to experience future crashes. After dangerous zones have been identified road modifications can be implemented improving public safety. This project introduces a historical safety metric for evaluating the relative danger of roads in a road network. The historical safety metric can be used to update routing choices of individual drivers improving public safety by avoiding historically more dangerous routes. The metric is constructed using crash frequency, severity, location and traffic information. An analysis of publicly available crash and traffic data in Allegheny County, Pennsylvania is used to generate the historical safety metric for a specific road network. Applications of this metric include comparison of routes based on the safety metric that begins with summing the danger of each accident on each street.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages411-416
Number of pages6
Volume2018-January
ISBN (Electronic)9781538644072
DOIs
StatePublished - Apr 9 2018
Event12th IEEE International Conference on Semantic Computing, ICSC 2018 - Laguna Hills, United States
Duration: Jan 31 2018Feb 2 2018

Other

Other12th IEEE International Conference on Semantic Computing, ICSC 2018
CountryUnited States
CityLaguna Hills
Period1/31/182/2/18

Fingerprint

Road network
Safety
Automobiles
Time series
Accidents
Crash
Roads
Public safety
Traffic safety
Prediction
Automobile
Severity
Routing

Keywords

  • Data Cleaning
  • Data Extraction
  • Data Integration
  • Statistical Analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems and Management

Cite this

Gupta, A., & Bansal, A. (2018). Integrating Traffic Datasets for Evaluating Road Networks. In Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018 (Vol. 2018-January, pp. 411-416). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSC.2018.00081

Integrating Traffic Datasets for Evaluating Road Networks. / Gupta, Ariel; Bansal, Ajay.

Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 411-416.

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

Gupta, A & Bansal, A 2018, Integrating Traffic Datasets for Evaluating Road Networks. in Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 411-416, 12th IEEE International Conference on Semantic Computing, ICSC 2018, Laguna Hills, United States, 1/31/18. https://doi.org/10.1109/ICSC.2018.00081
Gupta A, Bansal A. Integrating Traffic Datasets for Evaluating Road Networks. In Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 411-416 https://doi.org/10.1109/ICSC.2018.00081
Gupta, Ariel ; Bansal, Ajay. / Integrating Traffic Datasets for Evaluating Road Networks. Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 411-416
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