Estimation of Metro Freeway System Reliability and Resilience

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Estimation of Metro Freeway System Reliability and Resilience

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2022-02

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Minnesota Department of Transportation

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Report

Abstract

This study has estimated and analyzed the travel-time reliability and traffic-flow performance trends of the freeway corridors in the Twin Cities metro area of Minnesota. First, TeTRES (Travel-Time Reliability Estimation System), developed in the previous study, was enhanced by adding the estimation module of the traffic-flow performance measures for selected routes. Next, the TeTRES database was populated with the external-operating condition data collected from 2010 to 2020. The enhanced TeTRES was then applied to a total of 48 directional corridors in the metro freeway network and the travel-time reliability for each corridor under different operating conditions was estimated and analyzed along with the traffic-flow performance measures for 2016-2020 period. In particular, a newly developed vulnerability index, which combines 95th percentile buffer index and 95th percentile travel rate of each route, was applied to determine yearly-reliability trends under different operating conditions for each corridor. The vulnerability index was also applied to identify the most vulnerable bottleneck section within each directional corridor using the 2019 data under all conditions. Finally, a preliminary study to assess the operational resilience of freeway corridors was conducted in this study by formulating the corridor-wide operational resilience with data from a total of six directional corridor routes in the metro freeway network.

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Appendices (in separate PDF) include Appendix A: Travel-Time Reliability Trends Analysis for Individual Corridors Under Different Operational Condition (A-1 - A-245) and Appendix B: Code Snippets for Calculating Traffic-Flow Measures of Effectiveness (B-1 - B-11).

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Kwon, Eil; Jurrens, Chet; Wright, Cole; Mahmud, Asif. (2022). Estimation of Metro Freeway System Reliability and Resilience. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/227024.

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