Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections

Pedestrian injury in crashes at intersections often results from complex interaction among various factors. The factor identification is a critical task for understanding the causes and improving the pedestrian safety. A total of 2,614 crash records at signalized and non-signalized intersections wer...

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Main Authors: Xi Lu, Zhuanglin Ma, Steven I-Jy Chien, Ying Xiong
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2020-07-01
Series:Promet (Zagreb)
Subjects:
Online Access:https://traffic.fpz.hr/index.php/PROMTT/article/view/3428
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spelling doaj-e5915b87fb474771bda4171f3cade41e2020-11-25T03:25:53ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692020-07-0132455957110.7307/ptt.v32i4.34283428Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at IntersectionsXi Lu0Zhuanglin Ma1Steven I-Jy Chien2Ying Xiong3China Academy of Transportation Science, MOTChang’an University, College of Transportation EngineeringNew Jersey Institute of Technology, Chang'an UniversityXi’an Traffic Information CenterPedestrian injury in crashes at intersections often results from complex interaction among various factors. The factor identification is a critical task for understanding the causes and improving the pedestrian safety. A total of 2,614 crash records at signalized and non-signalized intersections were applied. A Partial Proportional Odds (PPO) model was developed to examine the factors influencing Pedestrian Injury Severity (PIS) because it can accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of contributing factors on the likelihood of PIS. For signalized intersections, seven explanatory variables significantly affect the likelihood of PIS, in which five explanatory variables violate the Proportional Odds Assumption (POA). Local driver, truck, holiday, clear weather, and hit-and-run lead to higher likelihood of severer PIS. For non-signalized intersections, six explanatory variables were found significant to the PIS, in which three explanatory variables violate the POA. Young and adult drivers, senior pedestrian, bus/van, divided road, holiday, and darkness tend to increase the likelihood of severer PIS. The vehicles of large size and heavy weight (e.g. truck, bus/van) are significant factors to the PIS at both signalized and non-signalized intersections. The proposed PPO model has demonstrated its effectiveness in identifying the effects of contributing factors on the PIS.https://traffic.fpz.hr/index.php/PROMTT/article/view/3428pedestriansafetycrash injury severityintersectionpartial proportional odds model
collection DOAJ
language English
format Article
sources DOAJ
author Xi Lu
Zhuanglin Ma
Steven I-Jy Chien
Ying Xiong
spellingShingle Xi Lu
Zhuanglin Ma
Steven I-Jy Chien
Ying Xiong
Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
Promet (Zagreb)
pedestrian
safety
crash injury severity
intersection
partial proportional odds model
author_facet Xi Lu
Zhuanglin Ma
Steven I-Jy Chien
Ying Xiong
author_sort Xi Lu
title Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
title_short Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
title_full Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
title_fullStr Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
title_full_unstemmed Development of a Partial Proportional Odds Model for Pedestrian Injury Severity at Intersections
title_sort development of a partial proportional odds model for pedestrian injury severity at intersections
publisher University of Zagreb, Faculty of Transport and Traffic Sciences
series Promet (Zagreb)
issn 0353-5320
1848-4069
publishDate 2020-07-01
description Pedestrian injury in crashes at intersections often results from complex interaction among various factors. The factor identification is a critical task for understanding the causes and improving the pedestrian safety. A total of 2,614 crash records at signalized and non-signalized intersections were applied. A Partial Proportional Odds (PPO) model was developed to examine the factors influencing Pedestrian Injury Severity (PIS) because it can accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of contributing factors on the likelihood of PIS. For signalized intersections, seven explanatory variables significantly affect the likelihood of PIS, in which five explanatory variables violate the Proportional Odds Assumption (POA). Local driver, truck, holiday, clear weather, and hit-and-run lead to higher likelihood of severer PIS. For non-signalized intersections, six explanatory variables were found significant to the PIS, in which three explanatory variables violate the POA. Young and adult drivers, senior pedestrian, bus/van, divided road, holiday, and darkness tend to increase the likelihood of severer PIS. The vehicles of large size and heavy weight (e.g. truck, bus/van) are significant factors to the PIS at both signalized and non-signalized intersections. The proposed PPO model has demonstrated its effectiveness in identifying the effects of contributing factors on the PIS.
topic pedestrian
safety
crash injury severity
intersection
partial proportional odds model
url https://traffic.fpz.hr/index.php/PROMTT/article/view/3428
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