Validation of Urban Freeway Models

Hranac, Rob; Barkley, Tiffany; Sambana, Kavya; Derstine, Brian; Mirchandani, Pitu; Zhou, Zhuoyang; Ahn, Soyoung; Iteris, Inc.; Arizona State University; University of Wisconsin--Madison; Second Strategic Highway Research Program (U.S.)

doi:10.17226/22282

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Validation of Urban Freeway Models

2015-01-01
By Hranac, Rob ; Barkley, Tiffany ; Sambana, Kavya ; ...

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Details:

Alternative Title:

SHRP 2 report S2-L33-RW-1.
Creators:

Hranac, Rob ; Barkley, Tiffany ; Sambana, Kavya ; Derstine, Brian ; Mirchandani, Pitu ; ... More +

Hranac, Rob ; Barkley, Tiffany ; Sambana, Kavya ; Derstine, Brian ; Mirchandani, Pitu ; Zhou, Zhuoyang ; Ahn, Soyoung Less -
Corporate Creators:

Iteris, Inc. ; Arizona State University ; University of Wisconsin--Madison ; Second Strategic Highway Research Program (U.S.)

Iteris, Inc. ; Arizona State University ; University of Wisconsin--Madison ; Second Strategic Highway Research Program (U.S.) Less -
Corporate Contributors:

National Research Council (U.S.). Transportation Research Board ; United States. Federal Highway Administration ; American Association of State Highway and Transportation Officials

National Research Council (U.S.). Transportation Research Board ; United States. Federal Highway Administration ; American Association of State Highway and Transportation Officials Less -
Subject/TRT Terms:

[+]

Freeways Intelligent Transportation Systems Traffic Data Traffic Models Travel Time Travel Time Reliability Urban Highways Validation
Publication/ Report Number:

SHRP 2 Report S2-L33-RW-1
DOI:

https://doi.org/10.17226/22282
Resource Type:

Tech Report
Right Statement:

National Academy of Sciences
Geographical Coverage:

United States
ISBN:

9780309274241
Corporate Publisher:

National Research Council (U.S.). Transportation Research Board
NTL Classification:

NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION;NTL-OPERATIONS AND TRAFFIC CONTROLS-OPERATIONS AND TRAFFIC CONTROLS;NTL-PLANNING AND POLICY-PLANNING AND POLICY;
Abstract:

This report describes the methodology, data, conclusions, and enhanced models regarding the validation of two sets of models developed in the Strategic Highway Research Program 2 (SHRP 2) Reliability Project L03, Analytical Procedures for Determining the Impacts of Reliability Mitigation Strategies. The significance of the L03 models is they were among the first models that could be used to predict travel time reliability. Two sets of models were developed in Project L03, the data-poor and the data-rich models. The data-poor models predict a measure of reliability as a function of just the mean Travel Time Index, except for on-time measures. The data-rich models predict a measure of the variability of travel time as a function of a number of explanatory variables: the demand-to-capacity ratio, lane-hours lost (due to traffic incidents or work zones), and rainfall. Both the data-poor and data-rich models were estimated from data collected over a year from a subset of urban freeway segments in seven cities. The data-poor models apply to all time slices throughout a day, whereas four sets of data-rich models concerning different moments of the TTI distribution were estimated for the peak hour, the peak period, the midday, and weekdays. Validation data totaled 323 segment-years covering both midday and peak periods. In conducting the validation, the research team was prohibited from using data that were used to estimate the data-poor and data-rich models. The project used two criteria for assessing the validity of the L03 models. The first was the difference between the predicted and measured values of the dependent variable. The second was whether the estimated models satisfied the assumptions of linear regression. This report describes the degree to which the different models perform well in terms of prediction and satisfying regression assumptions. The data-poor models predicted acceptably well but had some shortcomings in terms of satisfying the regression assumptions. Three sets of enhanced models were developed. The research team could not find satisfactory enhancements to the data-rich models. The degree to which the data-rich models predict well and satisfy the assumptions of linear regression is also described in the report.
Format:

PDF
Collection(s):

ITSJPO Digital Library
Main Document Checksum:

[+]

urn:sha256:46a7ad85952d1f0712701fb346f6763f76ee1c5d447c11825609fd034bc93b91
Download URL:

https://rosap.ntl.bts.gov/view/dot/3604/dot_3604_DS1.pdf
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Validation of Urban Freeway Models [supporting datasets]

[PDF - 369.09 KB]

:

Hranac, Rob ;

Barkley, Tiffany
...

2015-01-01

Abstract:

Source: Provided by ITS DataHub (its.dot.gov/data) through the National Transportation Library.The goal of the SHRP 2 Project L33 Validation of Urban ...

File Type:

[PDF - 369.09 KB]

File Type:

[PDF - 369.09 KB]

Validation of Urban Freeway Models

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