What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model

Luciano Lalika; Angela E. Kitali; Henrick J. Haule; Emmanuel Kidando; Thobias Sando; Priyanka Alluri

doi:10.1016/j.jsr.2021.12.011

What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model

Luciano Lalika
, Angela E. Kitali
, Henrick J. Haule
, Emmanuel Kidando
, Thobias Sando
, Priyanka Alluri

School of Engineering

University of North Florida
Florida International University

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	281-292
Number of pages	12
Journal	Journal of Safety Research
Volume	80
DOIs	https://doi.org/10.1016/j.jsr.2021.12.011
State	Published - Feb 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 11 Sustainable Cities and Communities

ASJC Scopus Subject Areas

Safety, Risk, Reliability and Quality

Keywords

Bayesian Logistic Regression
Bayesian Network
Crash severity
Older pedestrians
Pedestrian-vehicle crashes

Access to Document

10.1016/j.jsr.2021.12.011

Cite this

@article{6e607ceee232417ca3444aa0d32620f3,

title = "What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model",

keywords = "Bayesian Logistic Regression, Bayesian Network, Crash severity, Older pedestrians, Pedestrian-vehicle crashes",

author = "Luciano Lalika and Kitali, \{Angela E.\} and Haule, \{Henrick J.\} and Emmanuel Kidando and Thobias Sando and Priyanka Alluri",

note = "Publisher Copyright: {\textcopyright} 2021",

year = "2022",

month = feb,

doi = "10.1016/j.jsr.2021.12.011",

language = "English",

volume = "80",

pages = "281--292",

}

TY - JOUR

T1 - What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model

AU - Lalika, Luciano

AU - Kitali, Angela E.

AU - Haule, Henrick J.

AU - Kidando, Emmanuel

AU - Sando, Thobias

AU - Alluri, Priyanka

PY - 2022/2

Y1 - 2022/2

KW - Bayesian Logistic Regression

KW - Bayesian Network

KW - Crash severity

KW - Older pedestrians

KW - Pedestrian-vehicle crashes

UR - https://www.scopus.com/pages/publications/85122954225

UR - https://www.scopus.com/pages/publications/85122954225#tab=citedBy

U2 - 10.1016/j.jsr.2021.12.011

DO - 10.1016/j.jsr.2021.12.011

M3 - Article

C2 - 35249608

AN - SCOPUS:85122954225

SN - 0022-4375

VL - 80

SP - 281

EP - 292

JO - Journal of Safety Research

JF - Journal of Safety Research

ER -

What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model

UN SDGs

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this