Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.
Accid Anal Prev. 2016 Jul;92:245-55. doi: 10.1016/j.aap.2016.04.017. Epub 2016 Apr 22.
This research evaluates the safety effectiveness of multiple roadway cross-section elements on urban arterials for different crash types and severity levels. In order to consider the nonlinearity of predictors and obtain more reliable estimates, the generalized nonlinear models (GNMs) were developed using 5-years of crash records and roadway characteristics data for urban roadways in Florida. The generalized linear models (GLMs) were also developed to compare model performance. The cross-sectional method was used to develop crash modification factors (CMFs) for various safety treatments. The results from this paper indicated that increasing lane, bike lane, median, and shoulder widths were safety effective to reduce crash frequency. In particular, the CMFs for changes in median and shoulder widths consistently decreased as their widths increased. On the other hand, the safety effects of increasing lane and bike lane widths showed nonlinear variations. It was found that crash rates decrease as the lane width increases until 12ft width and it increases as the lane width exceeds 12ft. The crash rates start to decrease again after 13ft. It was also found that crash rates decreases as the bike lane width increases until 6ft width and it increases as the bike lane width exceeds 6ft. This paper demonstrated that the GNMs clearly captured the nonlinear relationship between crashes and multiple roadway cross-sectional features, which cannot be reflected by the estimated CMFs from the GLMs. Moreover, the GNMs showed better model fitness than GLMs in general. Therefore, in order to estimate more accurate CMFs, the proposed methodology of utilizing the GNMs in the cross-sectional method is recommended over using conventional GLMs when there are nonlinear relationships between the crash rate and roadway characteristics.
本研究评估了城市干道多种横断面要素对不同碰撞类型和严重程度的安全效果。为了考虑预测变量的非线性，并获得更可靠的估计，使用佛罗里达州城市道路 5 年的碰撞记录和道路特征数据，开发了广义非线性模型（GNM）。还开发了广义线性模型（GLM）来比较模型性能。使用横断面方法为各种安全处理开发了碰撞修正因子（CMF）。本文的结果表明，增加车道、自行车道、中央分隔带和路肩的宽度可有效减少碰撞频率。特别是，中央分隔带和路肩宽度变化的 CMF 随着其宽度的增加而持续减小。另一方面，增加车道和自行车道宽度的安全效果表现出非线性变化。发现碰撞率随着车道宽度的增加而减小，直到 12 英尺宽，超过 12 英尺宽时则增加。当车道宽度超过 13 英尺时，碰撞率再次开始下降。还发现，随着自行车道宽度的增加，碰撞率会降低，直到 6 英尺宽，超过 6 英尺宽时会增加。本文表明，GNM 清楚地捕捉到了碰撞与多种道路横断面特征之间的非线性关系，这是 GLM 估计的 CMF 无法反映的。此外，GNM 通常比 GLM 具有更好的模型拟合度。因此，为了估计更准确的 CMF，建议在横断面方法中利用 GNM 而不是传统的 GLM，当碰撞率与道路特征之间存在非线性关系时。
