臺北市號誌化路口肇事嚴重性影響因素之分析

Abstract

以往對於雙方車輛肇事的研究大部分只考慮到較為嚴重的一方，或是將雙方 視為整體來探討。然而，在同一事故中，由於不同的駕駛特性、車輛種類、交通 環境或是其他潛在因素，雙方所受到的嚴重程度往往有其差異性。為了要從事故 資料中獲得更多資訊，若能進一步分析比較雙方的差異性，將有助於提出更為有 效的安全改善策略。 雙方的嚴重程度及其相對應的事故因素經常是相互關聯的。有鑑於此，本研 究運用雙變量一般化依序普羅比模式(Bivariate Generalized Ordered Probit, BGOP) 模化雙方肇事嚴重程度，同時納入雙方重要的相關肇事資訊。此外，在模式校估 過程中，由於BGOP 的門檻函數放寬嚴重程度之固定門檻值假設，具有更佳的 解釋異質性功效，並可以提供受傷嚴重程度分類中更詳細的解釋資訊。 本研究以民國97年到98年間臺北市號誌化路口交通事故作為分析對象，共收 集2661筆案件資料，並將肇事嚴重程度分為「死亡或骨折以上」、「人員受傷」 及「單純車輛損壞」3 類。每一件案例係將主要的違規者列為第一方，並依文獻 回顧及實務上所能取得的資料，蒐集「人」、「車」、「路」及「環境」等可能 影響因素；先構建單變量依序普羅比與雙變量依序普羅比，比較其差異性，再構 建雙變量一般化依序普羅比模式探討異質性，做為研擬改善策略之參考。 研究結果顯示雙方肇事嚴重程度具有正向相關性。依模式校估結果，共計有 25個顯著影響變數，以及9個門檻變數，其中以「騎乘機車」、「酒駕行為」及 「路口附近燈光微弱」對當事人嚴重程度影響最大。在改善策略研擬部分，交通 工程建議從提升路口能見度；交通執法則建議應強化取締酒駕行為；在教育宣導 則建議加強將交通安全納入學校課程，培養學生良好的行車觀念。 關鍵字：號誌化路口、肇事嚴重程度、雙變量一般化依序普羅比模式

For two-vehicle crash accidents, one of the parties involved in an accident with more serious violation is termed as the first party. Most of the previous studies only consider the severity levels of the first party or combine the two parties in a whole. However, the severity levels of two parties involved in the same accident might be rather different, contributed by different driving behaviors, vehicle characteristics, traffic environment and other risk factors of both parties. Undoubtedly, to consider the severity levels of two parties along with corresponding factors is imperative for obtaining more insights from crash data and proposing more effective safety improvement strategies accordingly. The severity levels of two parties along with corresponding contributory factors can not be separately modeled, since these factors are usually closely correlated. In view of this, this study employs bivariate generalized ordered probit (BGOP) model to modeling the severity levels of both parties simultaneously without losing important relevant crash information of both parties. In addition, the threshold function of BGOP can be calibrated during the model estimation process to depict model heterogeneity and to provide more insights for severity classification. To validate the applicability of the BGOP to severity modeling of two parties and to investigate their contributory factors, a total of 2,661 two-vehicle accidents at signalized intersections in Taipei City during 2008 and 2009 were collected for model estimation, in which the first party was identified as the major traffic regulation violator in comparing to another party. The estimated results show that the BGOP model, which relaxes the assumption with fixed threshold values of severity levels, can not only perform better in terms of log-likelihood values and prediction errors, but also consider the effects of the risk factors to the severity levels of two parties. Moreover, significant and positive correlation coefficients for both parties are also found, suggesting the necessity of simultaneous modeling of the severity levels of both parties. It is also interesting to note that the illegal driving behaviors (e.g. drunk driving) of the first party significantly contribute to the severity level of the second party. Some corresponding safety improvement strategies are then proposed accordingly. Keywords: Signalized intersections, Severity level, Bivariate generalized ordered probit