汽车碰撞事故再现估算速度的不确定度分析

不确定度分析是一种考察人试验测量输入值得到计算结果输出之间不确定度传播的数学方法。本文中将不确定度分析方法引入汽车碰撞事故再现的模型算法中，推算碰撞前速度的不确定度，给出了在汽车正面斜碰撞事故再现中的一个应用实例。通过对计算结果的分析，初步得到了不确定度的传播规律，并指出了相关问题和发展方向。     

基于动量定理的汽车碰撞事故再现模型抗扰性分析

基于摄动理论，应用3种常用的数学方法对基于动量定理建立的汽车碰撞事故模型的抗扰性进行分析。结果表明：对于特定模型在复杂的扰动条件下，采用不同的数学方法，处理效果截然不同。通过理论分析，建立了解决此类问题的方法，给出了数学表达式。经过对代表车型的实际分析，验证了该方法的有效性。     

公路平面交叉口驾驶行为研究

面对目前公路平面交叉口交通事故严重的现状,为了公路平面交叉口交通事故致因分析和加深对交叉口驾驶行为的了解程度,探讨了公路平面交叉口驾驶行为理论,总结了目前道路交通系统交通事故原因及其导致事故所占比例,分析了交叉口交通系统,给出了影响交叉口驾驶行为的具体因素。在驾驶行为三阶段基础上,研究了交叉口驾驶行为模型,分析了交叉口驾驶行为特征和交叉口驾驶行为与交通事故发生的一般关系。并针对驾驶失误和不安全驾驶行为给出了防止措施,以减少交叉口交通事故。     

大客车对行人碰撞事故再现研究

利用数值模型仿真试验,研究再现大客车与行人碰撞事故的方法。并将该方法应用到一次真实交通事故中去,初步验证了该模型和方法的可行性。将行人抛距分析方法引入事故再现分析,并结合仿真结果,建立新的适合该类事故的行人抛距与车速关系模型。     

基于能量释放事故致因模型的地铁火灾防治思路

从系统安全原理的角度建立了地铁火灾的能量释放事故致因模型,并在此模型的基础上系统性地提出了地铁火灾的防治思路。事故致因模型中将地铁火灾划分为五个阶段,根据每个阶段的不同特点,提出了相应的防治思路：潜伏期为“管理”、孕育期为“屏蔽”、发生期为“防护”、发展期为“疏导与控制”、灾后为“恢复”。在防治思路的指导下,探讨了地铁火灾不同阶段下的防治途径与措施。     

基于有序聚类分析的高速公路路段长度划分研究

提出了基于F isher有序聚类分析的高速公路路段长度划分方法,以事故数沿每公里的空间分布为聚类指标进行路段长度划分,通过实例验证,一方面发现按照F isher有序聚类分析方法划分路段的结果能够使得分段后的事故频数很好地服从一定的概率分布,有益于模型的构建;另一方面,应用该方法分段能够很好地考虑事故的发生水平,把事故水平相近的邻近路段划分到同一研究样本内,有助于准确地量化影响因素的作用,在样本量不是特别大的情况下,能够突出两者之间的关系.     

“12·7”事故对珠江口区域溢油应急合作的启发

2004年发生于珠江口的“12·7”船舶碰撞溢油事故（以下简称“12·7”事故）被成功处置后,广东海事局在总结该事故处置经验的基础上,于2005年在珠江口开展了代号为“碧洋行动”的溢油应急演练。通过对“碧洋行动”设定的事故场景之一的推演和评估可以看到珠江口区域溢油应急合作对于该区域溢油事故应急处置的重要意义。     

汽车制动防抱死系统(ABS)的使用和检修要点

讨论了ABS系统的使用和检修要点,为ABS系统的使用及检修提供了有利的参考,对保障汽车制动时的安全性有重要意义。     

Strategic planning support for road safety measures based on accident data mining

When actions and measures to increase road safety are to be planned by the police and local authorities, it is necessary to consider the specific accident circumstances as well as their historical, current, and predicted course. In particular, combinations of accident circumstances not contained in existing police statistics are often neglected, but may nevertheless be relevant, e. g., due to an increasing frequency. In order to identify these undiscovered interesting combinations, we propose a framework to support strategic planning of road safety measures based on several consecutive data mining stages. The scope, type, and location of road safety measures must be planned at a strategic level several months in advance to be fully effective. Therefore, it is essential to investigate and predict the accident circumstances and the temporal changes in their frequency comprehensively. Only with the knowledge, e. g., about the temporal pattern, locations, conditions of roads or speeds, meaningful actions can be derived. The embedded data mining approaches, i. e., frequent itemset mining, time series clustering, time series classification, forecasting, and scoring, are carefully selected, coordinated, and aligned. As a result, the framework provides police users with information about circumstances of accidents that are of interest in the future and presents their previous temporal and local patterns in a dashboard. In this study, the framework is applied in four different geographical regions. Thereby, default parameter settings for all approaches are found that are particularly suitable for the framework to investigate novel geographic regions.     

Road pricing for congestion and accident externalities for mixed traffic of motorcycles and automobiles

Motorcycles play an important role in sharing the trip demand with automobiles for commuting, especially in many cities in Asia. However, the accident cost of a trip by motorcycle is higher than that of an automobile. This study analyzes the road pricing for the congestion and accident externalities of mixed traffic of automobiles and motorcycles. A model for equilibrium trips with no taxation and that for optimal trips with taxation are explored. The model is then applied to the Tucheng City–Banciao City–Taipei central business district corridor in Taipei metropolitan area. The findings in this case study show that the tax for accident externality is larger than that for congestion externality.