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Title:

Comparing Objective and Subjective Roadway Data Collection Methods Using the United States Road Assessment Program

Accession Number:

01664166

Record Type:

Component

Abstract:

The United States Road Assessment Program (usRAP) is a powerful tool for conducting Systemic Safety evaluations. The level of safety of the roads can be assessed through the usRAP Star Rating method, giving one star to least safe and five stars to safest roads. As part of the Star Rating data collection process, a comprehensive list of 40 road attributes are recorded for each 100-meter segment using Google StreetView and Aerial imagery. Several challenges are associated with usRAP data collection protocols and extensive quality assurance processes are required to ensure data quality. The sources of error are human error, inaccurate measurements/estimations, and the coder’s subjectivity in the data collection. To examine the effects of these errors on Star Rating results, this study has leveraged the Second Strategic Highway Research Program (SHRP 2) Roadway Information Database (RID) to complement the existing dataset. The RID includes a variety of safety-related roadway attributes collected by a mobile data collection vendor and meets high accuracy requirements by implementing a quality assurance plan. Using benefit-cost analysis, this study aims to compare the objective data collection approach of utilizing a mobile data collection vendor with high quality assurance processes versus the subjective approach of coding data manually. Star Ratings are calculated for a sample of two lane rural roads in North Carolina using the RID and the manually coded dataset. The study results showed that the dataset with more accurate input data resulted in more valid Star Rating results and more detailed safety countermeasure suggestions from the Road Assessment Program tool.

Supplemental Notes:

This paper was sponsored by TRB committee ANB10 Standing Committee on Transportation Safety Management.

Report/Paper Numbers:

18-05919

Language:

English

Authors:

Parvinashtiani, Niloo
Smadi, Omar

Pagination:

4p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Tables (2)

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-05919

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 11:31AM