Citation

Ma Z, Lu X, Chien SIJ, Hu D. Traffic Injury Prev. 2018; 19(2): 159-164.

Affiliation

School of Automobile, Chang'an University , Xi'an, Shaanxi , China.

Copyright

(Copyright © 2018, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2017.1354371

PMID

28737957

Abstract

OBJECTIVE: Vehicle crashes which involved pedestrian at intersections have been reported occasionally. The injury severity of pedestrians in these crashes seems significantly related to driver and pedestrian attributes, vehicle characteristics, and the geometry of intersections. Identifying factors associated with pedestrian injury severity (PIS) is critical for reducing crashes and improving safety. For developing the proposed probit models, drivers who involved crashes are classified into three groups: young drivers (16 ≤ age ≤ 24); middle-aged drivers (25 ≤ age ≤ 64); older drivers (age ≥ 65). This study explores that PIS is significantly but differently affected by these grouped drivers with different sets of explanatory variables.

METHODS: A total of 2,614 crash records (2011∼2012) at intersections in Cook County, Illinois of the US were collected. An ordered probit modeling approach was employed to develop the proposed model and examine factors influencing PIS. The likelihood ratio test was used to assess the model performance. Elasticity analysis was conducted to interpret the marginal effect of contributing factors on PIS associated with different drivers' groups by age.

RESULTS: The results show that four independent variables, including Pedestrian Age, Vehicle Type, Point of First Contact, and Weather Condition, significantly affect PIS at intersections for all drivers. Two additional independent variables (i.e. Number of Vehicles and Traffic Type) affect PIS for young and middle-aged drivers, while two other variables (i.e. Divided Type and Hit-and-run Related) are significant to PIS for both young and older drivers.

CONCLUSIONS: The independent variables significant to PIS at intersections for young, middle-aged, and older driver groups were identified; while the marginal effect of each variable to the likelihood of PIS were assessed.

Language: en

Keywords

age; driver; elasticity analysis; intersection; ordered probit model; pedestrian injury severity; safety