TY - JOUR
T1 - Determinant contributing variables to severity levels of pedestrian crossed the road crashes in three cities in Indonesia
AU - Tjahjono, Tri
AU - Swantika, Bhidara
AU - Kusuma, Andyka
AU - Purnomo, Robby
AU - Tambun, Grace Helen
N1 - Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - Objective: The study has two objectives: (1) to determine the factors on severity levels of pedestrian crossed the road crashes in three cities in Indonesia, (2) to suggest countermeasures at the most crash-prone areas in each city. Methods: Study areas are chosen based on the highest pedestrian fatality rate in Central Java Province. The determinant severity levels are based on 19 variables categorized into the pedestrian, road, environment, vehicle, and drivers’ characteristics. The crash data was collected from Indonesia Traffic Corps’ (Korlantas) database and site visits to all crash locations. The data was processed using the Ordered Probit Model (OPM) Method to find the contributing variables to determine Pedestrian Crossing Road crash severity level. Results: The significant variables are different in each city; Tegal is Crash location (0.296) and Type of Vehicle (0.176), Salatiga are Pedestrian age (0.484) and type of vehicle (0.472), Magelang are Road hierarchy (–0.582) and Driving license ownership (–0.262). Conclusions: Each city has unique variables to determine the severity level. Therefore, treatments and countermeasures must be specific to each city based on study findings.
AB - Objective: The study has two objectives: (1) to determine the factors on severity levels of pedestrian crossed the road crashes in three cities in Indonesia, (2) to suggest countermeasures at the most crash-prone areas in each city. Methods: Study areas are chosen based on the highest pedestrian fatality rate in Central Java Province. The determinant severity levels are based on 19 variables categorized into the pedestrian, road, environment, vehicle, and drivers’ characteristics. The crash data was collected from Indonesia Traffic Corps’ (Korlantas) database and site visits to all crash locations. The data was processed using the Ordered Probit Model (OPM) Method to find the contributing variables to determine Pedestrian Crossing Road crash severity level. Results: The significant variables are different in each city; Tegal is Crash location (0.296) and Type of Vehicle (0.176), Salatiga are Pedestrian age (0.484) and type of vehicle (0.472), Magelang are Road hierarchy (–0.582) and Driving license ownership (–0.262). Conclusions: Each city has unique variables to determine the severity level. Therefore, treatments and countermeasures must be specific to each city based on study findings.
KW - fatal crash
KW - level of severity
KW - ordered probit model
KW - Pedestrian crossed the road
UR - http://www.scopus.com/inward/record.url?scp=85102955752&partnerID=8YFLogxK
U2 - 10.1080/15389588.2021.1872065
DO - 10.1080/15389588.2021.1872065
M3 - Article
AN - SCOPUS:85102955752
SN - 1538-9588
VL - 22
SP - 318
EP - 323
JO - Traffic Injury Prevention
JF - Traffic Injury Prevention
IS - 4
ER -