公路穿村镇路段交通安全特征及事故预测方法研究
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摘要
随着改革开放的深入进行,我国正处于城镇化的快速发展阶段,其对交通安全产生了巨大的影响。在我国多数城镇沿国道和省道发展起来的特定国情下,公路穿村镇路段的里程日益增多、交通流量和交通干扰增大。在兼有城镇道路功能的过境公路中,过境车辆和当地居民通行混杂是交通事故的诱因,导致公路穿村镇路段交通事故的突出聚集性。交通事故的多发,既造成了社会财富的极大浪费,也造成了巨大的精神损失,并使得很多家庭陷入贫困,在相当程度上延缓了中小城镇经济的发展,直接影响到小城镇的可持续发展。由此,从宏观角度研究快速城镇化过程中的道路交通安全趋势及影响情况,并从微观角度对公路穿村镇路段的安全特征、车辆行驶特征和干扰影响规律进行有效、定量化的研究,构建事故预测和分析模型,可有效改善当前主要以经验指导公路穿村镇路段安全分析的状况,提高安全完善措施的针对性和有效性。
     本文在对国内外公路穿村镇路段相关研究进行系统性分析和总结的基础上,界定了公路穿村镇路段的概念,并从技术等级角度进行了分类和特性描述;分析了公路穿村镇路段的安全影响关键因素,并设计了试验方案。在宏观特性研究方面,进行了基于分数多项式回归的城镇化率对交通事故伤害的影响研究,基于综合因子分析和广义估计模型(GEE)进行了宏观因素的交通安全分析,并以北京地区城镇化率对应的交通事故水平为基准,为公路穿村镇路段的微观事故预测模型建立了城镇化率这个宏观因素的修正系数。从微观特性角度,研究了公路穿村镇路段内相对于普通路段的车辆速度特征、轨迹特征、对驾驶员驾驶负担的影响等,基于实测数据界定了公路穿村镇路段的交通安全影响范围,并应用主成分分析法和动态聚类法综合建立了公路穿村镇路段的交通安全分类方法;建立了基于面板数据事故预测分析模型的公路穿村镇路段的全部事故预测模型和一般事故预测模型,以及路侧、追尾、碰撞等不同事故形态的预测模型,并基于建模结果进行了事故减少因子的分析。为便于模型的实际应用,还提出了基于预测值的公路穿村镇路段安全分级标准。
China is rapidly urbanizing as a result of the process of "Reform and Opening". This influences traffic safety significantly. As most small cities and towns are developed along national or provincial highways, traffic volumes in these areas are increasing and there is a growing incidence of traffic disturbances and crashes. The mixture of vehicles traveling through these areas with those that of local residences is a key cause crashes on such roads.
     Crashes are not only cause a large loss of social wealth, but create deep emotional scars. They often lead families into poverty and slow down the economic development of middle-small-size cities and towns. Therefore, it is important to analyze traffic safety during rapid urbanization, and particularly assess crash distribution characteristics and vehicle travel and disturbance characteristics quantitatively. Crash prediction models can help direct such safety analysis and can also improve the effectiveness of safety countermeasures.
     The main contents of this paper are as follows:(1) defining the concept of "Highway Segments Passing Through Villages" and giving the technical grade classification basing on systemic analysis and a summary of previous research;(2) designing trial plots based on analysis of key factors that influence safety on highways that pass through urban areas;(3) analyzing the influence of urbanization on traffic safety using the'fractional polynomial method'and generalized estimating equations (GEE), and developing urbanization rate Accident Modified Coefficients (AMC) using the safety level of Beijing as a standard;(4) analyzing the crash, speed, orbit and acceleration data, using the classical approach of principal-component factor and dynamic cluster methods;(5) constructing a crash prediction model using panel data for all crashes, fatal crashes, roadside crashes, rear-end crashes and collision crashes; defining a crash reduction factor for key safety countermeasures; and defining the safety classification criterion based on the prediction results.
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