Systemic safety evaluation of two lane rural roads using United States road assessment program methodology

dc.contributor.advisor Omar Smadi
dc.contributor.author Parvinashtiani, Zahra
dc.contributor.department Department of Civil, Construction and Environmental Engineering
dc.date 2019-12-10T22:30:12.000
dc.date.accessioned 2020-06-30T03:17:18Z
dc.date.available 2020-06-30T03:17:18Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2019-07-20
dc.date.issued 2017-01-01
dc.description.abstract <p>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 StreetView imagery. Some of the challenges that are associated with usRAP data collection protocols are human error, inaccurate measurements, and the coder’s subjectivity. To examine the effects of these errors on Star Rating results, this study has leveraged the Second Strategic Highway Research Program Roadway (SHRP 2) 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.</p> <p>usRAP uses the risk-based non-crash measure of Road Protection Score (RPS) for assessing the level of safety of the roads by a 1-5 Star Rating scale. The previous validation studies have been mostly limited to the comparison of crash rate and Star Rating averages and have failed to establish a comprehensive statistical relationship. In order to investigate such relationship, this study develops a crash prediction model using a sample of two lane rural roads in North Carolina. The crash frequency was estimated as a function of Road Protection Score and Annual Average Daily Traffic using a negative binomial model. The results of this study showed that the crash frequency consistently increases with Road Protection Score. The safety performance function showed that moving from a 3-star road to a 2-star road would result in 47% more crashes. These findings confirm that Star Rating is a valid risk measure for crash frequency on two lane rural roads.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/17284/
dc.identifier.articleid 8291
dc.identifier.contextkey 15016502
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/17284
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/31467
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/17284/Parvinashtiani_iastate_0097M_16770.pdf|||Fri Jan 14 21:19:43 UTC 2022
dc.subject.disciplines Transportation
dc.subject.keywords Data collection practices
dc.subject.keywords Star Rating Assessment
dc.subject.keywords Systemic safety evaluation
dc.subject.keywords United States road assessment program (usRAP)
dc.title Systemic safety evaluation of two lane rural roads using United States road assessment program methodology
dc.type thesis
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication 933e9c94-323c-4da9-9e8e-861692825f91
thesis.degree.discipline Civil Engineering
thesis.degree.level thesis
thesis.degree.name Master of Science
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