Categorical principal component analysis (CATPCA) of pedestrian crashes in Central Florida

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
Hatem Abou-Senna, E. Radwan, H. Abdelwahab
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引用次数: 2

Abstract

Abstract This research investigates the characteristics and contributing causes of pedestrian crashes that occurred in Central Florida over a 5 year-period at intersections and mid-block crossings along roadway segments. The factors contributing to pedestrian crashes were classified into four main categories: location characteristics, pedestrian factors, driver/vehicle characteristics, and environmental-related factors along with their corresponding crash characteristics. Categorical Principal Components Analysis (CATPCA) was applied to understand the structure of a set of variables and to reduce the dimensionality of the dataset to a predefined number of dimensions and components. CATPCA analysis revealed that four dimensions accounted for almost 50% of the model indicating strong positive relationships between datasets with driver and pedestrian characteristics along with their corresponding crash characteristics relatively significant than the location and the environmental characteristics. The analysis showed that majority of the intersection crashes were during nighttime with pedestrians under influence and failing to yield to the right of way (ROW). They included mainly left-turn and right-turn crashes. In addition, drivers were also found at fault due to vision issues resulting from absence of lighting at intersections and categorized as failure to yield to the ROW. At midblock locations, major crash types were through moving vehicles hitting pedestrians crossing and walking along the roadway especially during nighttime conditions. However, majority of the crashes were at locations away from the designated crossings likely due to the long distances between legal crossing locations and pedestrian’s failure to utilize them. The findings of this research and examining the factors affecting pedestrians’ crash likelihood and injury severity can lead to better crash mitigation strategies, countermeasures and policies that would alleviate this growing problem in Central Florida.
佛罗里达州中部行人交通事故的分类主成分分析(CATPCA)
摘要:本研究调查了5年来发生在佛罗里达州中部的十字路口和沿道路分段的中间街区交叉路口的行人碰撞的特征和原因。将导致行人碰撞的因素分为四大类:位置特征、行人特征、驾驶员/车辆特征和环境相关因素及其相应的碰撞特征。分类主成分分析(CATPCA)用于理解一组变量的结构,并将数据集的维数降低到预定义的维数和分量。CATPCA分析显示,四个维度占模型的近50%,表明驾驶员和行人特征之间的数据集具有很强的正相关关系,其相应的碰撞特征相对于位置和环境特征相对显著。分析表明,大多数路口交通事故发生在夜间,行人在醉酒的情况下没有让行权(ROW)。这些事故主要包括左转和右转事故。此外,由于十字路口没有照明而导致视力问题,司机也被发现有过错,并被归类为未能向ROW让步。在街区中间的位置,主要的撞车类型是移动的车辆撞到过马路和沿着道路行走的行人,尤其是在夜间。然而,大多数事故发生在远离指定人行横道的地方,这可能是由于合法人行横道的地点距离太远,而行人没有利用它们。这项研究的结果以及对影响行人碰撞可能性和受伤严重程度的因素的研究,可以导致更好的碰撞缓解战略、对策和政策,从而缓解佛罗里达州中部这一日益严重的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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