Methodology for Predicting MAP-21 Interstate Travel Time Reliability Measure Target in Virginia

Author:

Babiceanu Simona1ORCID,Lahiri Sanhita1ORCID

Affiliation:

1. Traffic Engineering Division, Virginia Department of Transportation, Richmond, VA

Abstract

This study develops a target setting methodology for the (Moving Ahead for Progress) MAP-21 Interstate Travel Time Reliability Measure of “Percent of the Person-Miles Traveled on the Interstate that are Reliable” (PMTR-IS). The study uses data specific to Virginia for a set of independent variables (Hourly Volume, and Volume/Capacity Ratio, Truck Percentage, Equivalent Property Damage Only Rate, Lane Impacting Incident Rate, Number of Lanes, Presence of Safety Service Patrol, Terrain, Urban Designation) to predict whether a MAP-21 reporting segment is reliable. This is used to estimate predicted PMTR-IS with the MAP-21 specified formula. CART (classification and regression trees) models were used with 1,536 different configurations. Of the four best performing models, one was selected using engineering judgement. Datasets from 2017 and 2018 were used for training, and from 2019 and 2020 for testing. The predicted and calculated PMTR-IS were compared, and the error percentage was lower than 1% for 2019, which can be considered negligible. The 2020 error rate was higher and can perhaps be attributed to unusual reliability because of the impacts of the pandemic on travel. Sensitivity analyses revealed that the predicted PMTR-IS is reactive to capacity increase in unreliable sections at a local level, slower to respond to local AADT (annual average daily traffic) increase, and stable to small statewide AADT oscillations. The authors recommend using this methodology for target setting, taking into consideration the state authorities’ other strategic priorities.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference26 articles.

1. US Congress. Public Law 112-141—July 6, 2012. https://www.govinfo.gov/content/pkg/PLAW-112publ141/pdf/PLAW-112publ141.pdf.

2. Code of Federal Regulations. Title 23. https://www.ecfr.gov/cgi-bin/retrieveECFR?gp=&SID=7c955ec3c47ba5f35529b89f21c02213&mc=true&n=pt23.1.490&r=PART&ty=HTML.

3. National Academies of Sciences, Engineering, and Medicine. Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies - Volume I: Research Report, and Volume II: Guide for Target Setting and Data Management. The National Academies Press, Washington, D.C., 2010. https://doi.org/10.17226/14429.

4. FHWA. Transportation Performance Management / Performance-Based Planning and Programming Implementation Workshop Series. May 2020. https://www.fhwa.dot.gov/planning/performance_based_planning/workshops/tpm_interim_report/index.cfm#toc34041056. Accessed July 30, 2021.

5. Georgia DOT Research Project #19-25: Transportation Performance Management for System Operations: Development of Processes, Tools, Measures and Targets. GDOT, Office of Performance-Based Management and Research, Atlanta, GA, October 2020. http://g92018.eos-intl.net/eLibSQL14_G92018_Documents/19-25.pdf. Accessed July 30, 2021.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Travel Time Reliability Prediction Using Random Forests;Transportation Research Record: Journal of the Transportation Research Board;2023-07-20

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