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Data Driven Identification of Candidates for Operational Improvement

Project Details
STATUS

Completed

PROJECT NUMBER

19-716

START DATE

07/01/19

END DATE

10/31/21

SPONSORS

Iowa Department of Transportation

Researchers
Principal Investigator
Christopher Day

Affiliate Researcher, CTRE

Co-Principal Investigator
Skylar Knickerbocker

Research Engineer, REACTOR

About the research

In Iowa, the safety improvement candidate list has been used for about 20 years to identify roadway locations having disproportionate crash rates or severities. Recent federal rulemaking on the travel-time reliability measurement requires a push toward greater accountability for operational performance. In response to this guidance, the present study explores the development of an operational improvement candidate list (OICL) by using data that were available at the time of the study.

A survey of the available data is presented. Two data sets were selected on the basis of their availability to facilitate quantitative research during the study period: automated traffic signal performance measures (ATSPMs) and probe vehicle data. Performance measures for corridor ranking were developed independently from the ATSPM and probe vehicle data, and the two data sets were ultimately combined  to develop a methodology for creating an OICL. The methodology was confirmed using the Cedar Rapids, Iowa area as a case study. In addition, data from Dubuque, Iowa were used to compare the ATSPM and probe vehicle data for corridor performance measures, which found a correlation between average segment speeds and intersection performance measures. The report concludes with a discussion of the scalability of the method and potential future research.

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