Identifying Black Spots Using Property Damage Only Equivalency (PDOE) Factors

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Samuel Washington
Mazharul Haque
Jutaek Oh
Dongmin Lee

Methodologies for identifying ‘sites with promise’ have received considerable attention in the transportation safety literature. Robust hot spot identification (HSID) methodologies are vital as errors result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative) misuse of public funds and lead to poor investment decisions and inefficient risk management. The historical pursuit of HSID methods development has lead to important insights; however, there remain at least several critical impediments to further progress: 1) a significant proportion of property damage only (PDO) and minor injury crashes are underreported (approximately 40%), affecting the reliability of count based models; 2) most methods ignore crash severity and costs; and 3) expected safety performance functions are heavily skewed by a preponderance of zeroes. This paper argues that it is possible and indeed desirable to incorporate crash costs into HSID. Moreover, a straightforward method is proposed whereby crashes are intelligently weighted using property damage only equivalent (PDOE) crashes. The use of PDOEs enables identification of a set of high-risk sites that reflect the true safety costs to society and simultaneously reduces the influence of under-reported PDO crashes, thereby addressing impediments 1 and 2. Non-parametric Quantile regression is used to overcome the preponderance of zeroes problem (impediment 3). The proposed procedure is illustrated using rural road segment data from Korea.

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