Dept. of Civil Engineering, University of British Columbia, Vancouver, BC, Canada V6T 1Z4.
Accid Anal Prev. 2011 Jan;43(1):87-94. doi: 10.1016/j.aap.2010.07.015. Epub 2010 Oct 23.
The objective of this study is to evaluate the safety performance of a sample of intersections that have been improved with the implementation of certain safety countermeasures in the Greater Vancouver area. A full Bayes approach is utilized to determine the effectiveness of the improvements using a before-after design with matched (yoked) comparison groups. A multivariate Poisson-lognormal intervention model is used for the analysis of crash counts by severity levels. The model is extended to incorporate random parameters to account for the correlation between sites within comparison-treatment pairs. The full Bayes analysis revealed that incorporating such design features as matched comparison groups in the specification of safety performance functions can significantly improve the fit, while reducing the estimates of the extra-Poisson variation. As well, such extended models can be used to account for heterogeneity due to unobserved road geometrics, traffic characteristics, environmental factors and driver behavior. The results showed that the overall odds ratios for injuries and fatalities (I+F) and property damage only (PDO) imply significant reductions in predicted crash counts of 23% and 15%, respectively. The corresponding credible intervals were (12%, 33%) and (6%, 24%) at the 0.95 confidence level. The majority of the site-level odds ratio exhibited reductions in both I+F and PDO predicted crash counts. However, only some of these reductions were significant. As well, the effectiveness of the treatment seems to vary by severity level from one location to another. For I+F, the crash reduction factors were 29%, 15% and 21% for improving signal visibility, left turn phase improvement and left turn lane installation, respectively. The corresponding crash reduction factors for PDO were 21%, 4% and 20%, respectively.
本研究旨在评估大温哥华地区实施某些安全措施后改善的交叉口的安全性能。采用贝叶斯全模型，使用前后配对设计和匹配（yoked）对照组来确定改进措施的效果。使用多元泊松对数正态干预模型分析严重程度的碰撞次数。该模型扩展到纳入随机参数，以考虑比较治疗对内部站点之间的相关性。全贝叶斯分析表明，在指定安全性能函数时纳入匹配对照组等设计特征可以显著提高拟合度，同时减少额外泊松变异的估计值。此外，此类扩展模型可用于解释由于未观察到的道路几何形状、交通特征、环境因素和驾驶员行为引起的异质性。结果表明，受伤和死亡（I+F）和仅财产损失（PDO）的整体优势比表明，预测碰撞次数分别减少了 23%和 15%。在 0.95 的置信水平下，相应的可信区间分别为（12%，33%）和（6%，24%）。大多数站点级别的优势比都表明，I+F 和 PDO 的预测碰撞次数都有所减少。然而，只有其中一些减少是显著的。此外，治疗的效果似乎因严重程度的不同而在不同地点有所不同。对于 I+F，改善信号可见度、左转相位改善和左转车道安装的碰撞减少因素分别为 29%、15%和 21%。PDO 的相应碰撞减少因素分别为 21%、4%和 20%。
