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Investigation of pedestrian crashes using multiple correspondence analysis in India

机译:使用印度多函数分析的行人崩溃调查

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摘要

Pedestrian safety is of growing concern with an increasing number of traffic accidents, especially in developing economies like India. In 2017, there were 20,457 pedestrian fatalities in India. Pedestrian crashes have also become a key concern in the state of Tamilnadu, India, due to the high percentage of deaths. If the available datasets are large and complex, identifying key factors is a challenging task. In this study, Multiple Correspondence Analysis (MCA), an exploratory data analysis technique was used to explore the roadway, traffic, crash, and pedestrian-related variables influencing pedestrian crashes. This study used the data from Government of Tamilnadu Road Accident Traffic Management System (RADMS) database, to analyse accident data of nine years (2009-2017) related to pedestrian crashes. The results of the study show that crashes occurring on the express highways on a multilane road are often associated with hit-and-run behaviour among drivers. Factors such as lighting conditions, location, pedestrian behaviour, crossings, and physical separation are also significantly contributing to pedestrian crashes. The key advantage of MCA is that it identifies a possible association between various contributing factors. The findings from this study will be useful for state transport authorities to improve countermeasures for mitigating pedestrian crashes and fatalities.
机译:行人安全性越来越受到越来越多的交通事故,特别是在印度发展中经济体。 2017年,印度有20,457个行人死亡。由于死亡人数高,行人坠毁也成为印度塔米尔纳德邦州的关键问题。如果可用的数据集很大且复杂,则识别关键因素是一个具有挑战性的任务。在本研究中,多个对应分析(MCA),用于探索巷道,交通,崩溃和与行人崩溃的行人相关的变量。本研究利用了Tamilnadu Road Exceive Commery Management System(RADMS)数据库政府的数据,分析了与行人坠毁相关的九年(2009-2017)的事故数据。研究结果表明,在多层道路上的快速高速公路上发生的崩溃通常与司机之间的命中行为相关。照明条件,位置,行人行为,交叉和物理分离等因素也有显着贡献行人崩溃。 MCA的关键优势在于它识别各种贡献因素之间的可能关联。本研究的调查结果将对国家运输当局有用,以改善减轻行人崩溃和死亡的对策。

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