Ranking cities for safety investigation by potential for safety improvement

Wen Cheng, Wei Hua Lin, Xudong Jia, Xinkai Wu, Jiao Zhou

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The authors performed a city-level hot-spot identification by using the 4-year data of 265 cities in California. It is intended to equip road safety professionals with more useful information to compare the safety performance of city as a whole. Potential for safety improvement (PSI) was adopted as a measure of crash risk to compare alternate identification of hot spot (HSID) methods, including the Empirical Bayes (EB) and three full Bayesian (FB) alternatives, negative binomial, Poisson log-normal, and the Poisson temporal random effect, for ranking the safety performance of cities. Five evaluation tests which contain the Site Consistency Test, the Method Consistency Test, the Total Rank Difference Test, the Total Performance Difference Test, and the Total Score Test were applied to evaluate the performance of the four HSID methods. Moreover, two cutoff levels, top 5% and 10% cities, were employed for more reliable results. Overall, the study results are consistent with the results of previous quantitative evaluations focused on micro-level HSID. The three FB approaches significantly outperform the EB counterpart. The method accounting for temporal random effect produces more reliable HSID results than those without considering the serial correlations in collision counts.

Original languageEnglish (US)
Pages (from-to)345-366
Number of pages22
JournalJournal of Transportation Safety and Security
Issue number4
StatePublished - Jul 4 2018


  • city level
  • hot spot identification
  • the Empirical Bayes
  • the full Bayesian

ASJC Scopus subject areas

  • Transportation
  • Safety Research


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