TY - JOUR
T1 - Development of a partial proportional odds model for pedestrian injury severity at intersections
AU - Lu, Xi
AU - Ma, Zhuanglin
AU - Chien, Steven I.Jy
AU - Xiong, Ying
N1 - Funding Information:
This paper was supported by the research projects sponsored by the Humanities and Social Science Research Project of the Ministry of Education (No. 18YJCZH130), National Key Research and Development Program of China (No. 2018YFB1600900), the Postdoctoral Innovative Talent Support Program of China (No. BX20180268), and the Fundamental Research Funds for the Central University, CHD (No. 300102228202, 300102229666, 300102228101).
Publisher Copyright:
© 2020, Faculty of Transport and Traffic Engineering. All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - 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-signal-ized 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 quan-tify 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 intersec-tions, 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 in-tersections. The proposed PPO model has demonstrated its effectiveness in identifying the effects of contributing factors on the PIS.
AB - 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-signal-ized 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 quan-tify 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 intersec-tions, 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 in-tersections. The proposed PPO model has demonstrated its effectiveness in identifying the effects of contributing factors on the PIS.
KW - Crash injury severity
KW - Intersection
KW - Partial proportional odds model
KW - Pedestrian
KW - Safety
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U2 - 10.7307/ptt.v32i4.3428
DO - 10.7307/ptt.v32i4.3428
M3 - Article
AN - SCOPUS:85089376610
SN - 0353-5320
VL - 32
SP - 559
EP - 571
JO - Promet - Traffic - Traffico
JF - Promet - Traffic - Traffico
IS - 4
ER -