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<p>Road crashes cause 1.2 million deaths and over 50 million injuries annually, making them a significant public health issue. To improve road safety, various traffic calming measures are evaluated for their effectiveness in reducing crashes. This research evaluates the impact of speed humps, median refuges, and traffic signs in Tehran using simple before-and-after and empirical Bayes methods, constructing Safety Performance Functions (SPFs) and calculating crash modification factors (CMFs). The simple before-and-after study shows different percentages of changes in crash types for each intervention. Speed humps have the highest percentage change in injured crashes (36.38 ± 4.6%), while traffic signs have the lowest percentage change in total crashes (16 ± 5.9%). The empirical Bayes method, which required developing specific SPFs, confirmed the negative binomial distribution's validity over the Poisson distribution. Speed humps and traffic signs show significant changes in injured crashes (28.3 ± 2% and 13.0 ± 4.1%, respectively), and median refuges have the highest change in damaged crashes (30.28 ± 2.7%). CMF values for speed humps using the simple before-and-after and empirical Bayes methods are 0.64 and 0.72 for injury crashes, 0.73 and 0.75 for property damage crashes, and 0.71 and 0.73 for total crashes, respectively. For median refuges, CMF values are 0.67 and 0.80 for injury crashes, 0.64 and 0.70 for property damage crashes, and 0.65 and 0.70 for total crashes. For traffic signs, CMF values are 0.82 and 0.87 for injury crashes, 0.85 and 0.89 for property damage crashes, and 0.84 and 0.88 for total crashes. These results help authorities make informed decisions based on the rate of return, considering the limited annual budget for road maintenance and improvements.</p>

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Evaluating Traffic Calming Measures in Tehran: A Before–After Study with Simple and Empirical Bayes Methods

  • 期刊论文

  • 发表日期：

    2025年7月28日

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  • Sepehr Golrokh Amin,
  • Ali Tavakoli Kashani,
  • Matin Shahri

摘要

Road crashes cause 1.2 million deaths and over 50 million injuries annually, making them a significant public health issue. To improve road safety, various traffic calming measures are evaluated for their effectiveness in reducing crashes. This research evaluates the impact of speed humps, median refuges, and traffic signs in Tehran using simple before-and-after and empirical Bayes methods, constructing Safety Performance Functions (SPFs) and calculating crash modification factors (CMFs). The simple before-and-after study shows different percentages of changes in crash types for each intervention. Speed humps have the highest percentage change in injured crashes (36.38 ± 4.6%), while traffic signs have the lowest percentage change in total crashes (16 ± 5.9%). The empirical Bayes method, which required developing specific SPFs, confirmed the negative binomial distribution's validity over the Poisson distribution. Speed humps and traffic signs show significant changes in injured crashes (28.3 ± 2% and 13.0 ± 4.1%, respectively), and median refuges have the highest change in damaged crashes (30.28 ± 2.7%). CMF values for speed humps using the simple before-and-after and empirical Bayes methods are 0.64 and 0.72 for injury crashes, 0.73 and 0.75 for property damage crashes, and 0.71 and 0.73 for total crashes, respectively. For median refuges, CMF values are 0.67 and 0.80 for injury crashes, 0.64 and 0.70 for property damage crashes, and 0.65 and 0.70 for total crashes. For traffic signs, CMF values are 0.82 and 0.87 for injury crashes, 0.85 and 0.89 for property damage crashes, and 0.84 and 0.88 for total crashes. These results help authorities make informed decisions based on the rate of return, considering the limited annual budget for road maintenance and improvements.