论文标题
应用关联规则挖掘以调查不同照明条件下的行人致命和伤害崩溃模式
Applying Association Rules Mining to Investigate Pedestrian Fatal and Injury Crash Patterns Under Different Lighting Conditions
论文作者
论文摘要
行人碰撞的模式取决于照明情况，强调需要在各种照明条件下检查行人撞车事故。本研究使用路易斯安那州行人致命和伤害崩溃数据（2010-2019），应用了关联规则挖掘（ARM），以根据三种不同的照明条件（日光，深色 - 隔离街灯和黑暗 - 毫无意义的街头灯）确定碰撞风险因素的隐藏模式。根据生成的规则，结果表明，日光行人撞车事故与儿童（不到15岁），高级行人（大于64岁），年长的驾驶员（> 64岁）以及其他驾驶行为（例如失败/分心/分心，疾病/疲劳/疲劳/睡眠）相关。此外，在日光条件下，年轻的驾驶员（15-24岁）卷入了严重的行人撞车事故。这项研究还发现，在黑暗街头条件下，行人酒精/药物参与是最常见的项目。这种崩溃类型特别与行人行动（越过交叉路口/中间机），驾驶员年龄（55-64岁），速度限制（30-35 mph）和特定区域类型（具有混合住宅区域的业务）有关。在黑暗中没有路灯条件的情况下，发现致命的行人撞车与高速极限（> 50 mph）的道路有关。与高速极限有关的其他一些风险因素是行人与交通交通，行人深色衣服的存在，行人酒精/毒品参与。预计研究结果将对行人崩溃风险因素与特定照明条件之间的潜在关系有了深刻的了解。高速公路安全专家可以利用这些发现来进行决策过程，以选择有效的对策，以减少行人策略性的崩溃。
The pattern of pedestrian crashes varies greatly depending on lighting circumstances, emphasizing the need of examining pedestrian crashes in various lighting conditions. Using Louisiana pedestrian fatal and injury crash data (2010-2019), this study applied Association Rules Mining (ARM) to identify the hidden pattern of crash risk factors according to three different lighting conditions (daylight, dark-with-streetlight, and dark-no-streetlight). Based on the generated rules, the results show that daylight pedestrian crashes are associated with children (less than 15 years), senior pedestrians (greater than 64 years), older drivers (>64 years), and other driving behaviors such as failure to yield, inattentive/distracted, illness/fatigue/asleep. Additionally, young drivers (15-24 years) are involved in severe pedestrian crashes in daylight conditions. This study also found pedestrian alcohol/drug involvement as the most frequent item in the dark-with-streetlight condition. This crash type is particularly associated with pedestrian action (crossing intersection/midblock), driver age (55-64 years), speed limit (30-35 mph), and specific area type (business with mixed residential area). Fatal pedestrian crashes are found to be associated with roadways with high-speed limits (>50 mph) during the dark without streetlight condition. Some other risk factors linked with high-speed limit related crashes are pedestrians walking with/against the traffic, presence of pedestrian dark clothing, pedestrian alcohol/drug involvement. The research findings are expected to provide an improved understanding of the underlying relationships between pedestrian crash risk factors and specific lighting conditions. Highway safety experts can utilize these findings to conduct a decision-making process for selecting effective countermeasures to reduce pedestrian crashes strategically.
