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首页> 外文期刊>Accident Analysis & Prevention >Prediction of accidents at full green and green arrow traffic lights in Switzerland with the aid of configuration-specific features.
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Prediction of accidents at full green and green arrow traffic lights in Switzerland with the aid of configuration-specific features.

机译:借助特定于配置的功能,可以预测瑞士全绿色和绿色箭头交通信号灯的事故。

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摘要

In this study it was endeavored to predict full green and green arrow accidents at traffic lights, using configuration-specific features. This was done using the statistical method known as Poisson regression. A total of 45 sets of traffic lights (criteria: in an urban area, with four approach roads) with 178 approach roads were investigated (the data from two approach roads was unable to be used). Configuration-specific features were surveyed on all approach roads (characteristics of traffic lanes, road signs, traffic lights, etc.), traffic monitored and accidents (full green and green arrow) recorded over a period of 5 consecutive years. It was demonstrated that only between 23 and 34% of variance could be explained with the models predicting both types of accidents. In green arrow accidents, the approach road topography was found to be the major contributory factor to an accident: if the approach road slopes downwards, the risk of a green arrow accident is approximately five and a half times greater(relative risk, [Formula: see text] ) than on a level or upward sloping approach road. With full green accidents, obstructed vision plays the major role: where vision can be obstructed by vehicles turning off, the accident risk is eight times greater ( [Formula: see text] ) than where no comparable obstructed vision is possible. From the study it emerges that technical features of traffic lights are not able to control a driver's actions in such a way as to eradicate error. Other factors, in particular the personal characteristics of the driver (age, sex, etc.) and accident circumstances (lighting, road conditions, etc.), are likely to make an important contribution to explaining how an accident occurs.
机译:在这项研究中,我们努力使用特定于配置的功能来预测交通信号灯处的绿色和绿色箭头事故。这是使用称为Poisson回归的统计方法完成的。共调查了178条道路的45套交通信号灯(标准:在市区,有4条道路)(无法使用两条道路的数据)。连续5年对所有进场道路(行车道,路标,交通信号灯等的特征),交通监控和事故(全绿色和绿色箭头)记录了特定于配置的特征。结果表明,预测两种事故类型的模型只能解释23%至34%的方差。在绿色箭头事故中,发现进场道路的地形是造成事故的主要因素:如果进场道路向下倾斜,则发生绿色箭头事故的风险大约大五倍半(相对风险,[公式:参见文字]),而不是在水平或向上倾斜的进场道路上。在完全的绿色事故中,视力受阻起主要作用:如果车辆熄火会阻碍视力,则发生事故的风险是无视力障碍时的八倍(公式)。从研究中可以看出,交通信号灯的技术特征不能以消除错误的方式控制驾驶员的动作。其他因素,特别是驾驶员的个人特征(年龄,性别等)和事故情况(照明,道路状况等),可能会对解释事故的发生方式做出重要贡献。

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