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Investigating and Facilitating the Transferability of Safety Performance Functions
Title
Investigating and Facilitating the Transferability of Safety Performance Functions.
Creator
Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
Abstract / Description
Safety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public...
Show moreSafety performance functions (SPFs) are essential analytical tools in the road safety field. The SPFs are statistical regression models used to predict crash counts by roadway facility type, crash type and severity. The national Highway Safety Manual (HSM) is a generic guidebook used for road safety evaluation and enhancement. In it, default SPFs, developed using negative binomial (NB) regression, are provided for multiple facility types and crash categories. Roadway agencies, whether public or private, may opt to not invest their resources in data collection and processing to develop own localized SPFs. Instead, the agencies may adopt the HSM's. However, the HSM's SPFs may not necessarily be applicable to any conditions. Hence, this research is focused on SPF transferability, specifically for rural divided multilane highway segments. Use of Bayesian informative priors to aid in the transferability of NB SPFs, developed for Florida, to California's conditions and vice versa is investigated. It is demonstrated that informative priors facilitate SPF transferability. Furthermore, NB SPFs are developed for Florida, Ohio, Illinois, Minnesota, California, Washington and North Carolina. That is to evaluate the transferability of each state's SPFs to the other states' conditions. The results indicate that Ohio, Illinois, Minnesota and California have SPFs that are transferable to conditions of each of the four states. Also, two methods are proposed for calibrating transferred SPFs to the destinations' conditions and are shown to outperform the SPF calibration methods in the road safety literature. Finally, a variety of modeling frameworks are proposed for developing and transferring SPFs of the seven aforementioned states to each state's data. Not a single model exhibits the best fit when transferred in all cases. However, the Tobit model, NB model and a hybrid model that coalesces the results of both perform the best in a substantial number of the transferred SPFs.
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Date Issued
2018
Identifier
CFE0007000, ucf:52054
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007000
Examining Multiple Approaches for the Transferability of Safety Performance Functions
Title
Examining Multiple Approaches for the Transferability of Safety Performance Functions.
Creator
Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
Abstract / Description
Safety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are...
Show moreSafety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are not available, it is custom to adopt nationwide SPFs for crash predictions then apply a calibration factor. Yet, the research is limited regarding the application of national SPFs for local jurisdictions. In this study, the topic of transferability is explored by examining rural multilane highway SPFs from Florida, Ohio, and California. That is for both divided segments and intersections. Traffic, road geometrics and crash data from the three states are collected to develop one-state, two-state and three-state SPFs. The SPFs are negative binomial models taking the form of those of the HSM. Evaluation of the transferability of models is undertaken by calculating a measure known as the transfer index. It is used to explain which SPFs may be transferred tolerably to other jurisdictions. According to the results, the transferability of rural divided segments' SPFs of Florida to California and vice versa is superior to that of Ohio's SPFs. For four-leg signalized intersections, neither state's models are transferable to any state. Also, the transfer index indicates improved transferability when using pooled data from multiple states. Furthermore, a modified version of the Empirical Bayes method that is responsible for segment specific adjustment factors is proposed as an alternative to the HSM calibration method. It is used to adjust crash frequencies predicted by the SPFs being transferred to the jurisdiction of interest. The modified method, proposed, outperforms the HSM calibration method as per the analysis results.
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Date Issued
2015
Identifier
CFE0006298, ucf:51604
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006298