Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach

Ali J. Ghandour, Huda Hammoud and Samar Al-Hajj
Additional contact information
Ali J. Ghandour: National Council for Scientific Research (CNRS), Beirut 11-8281, Lebanon
Huda Hammoud: Faculty of Engineering and Architecture, American University of Beirut, Beirut 1072020, Lebanon
Samar Al-Hajj: Faculty of Health Sciences, American University of Beirut, Beirut 1072020, Lebanon

IJERPH, 2020, vol. 17, issue 11, 1-13

Abstract: Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance. In this study, we proposed a model that adopts a hybrid ensemble machine learning classifier structured from sequential minimal optimization and decision trees to identify risk factors contributing to fatal road injuries. The model was constructed, trained, tested, and validated using the Lebanese Road Accidents Platform (LRAP) database of 8482 road crash incidents, with fatality occurrence as the outcome variable. A sensitivity analysis was conducted to examine the influence of multiple factors on fatality occurrence. Seven out of the nine selected independent variables were significantly associated with fatality occurrence, namely, crash type, injury severity, spatial cluster-ID, and crash time (hour). Evidence gained from the model data analysis will be adopted by policymakers and key stakeholders to gain insights into major contributing factors associated with fatal road crashes and to translate knowledge into safety programs and enhanced road policies.

Keywords: fatal crashes; road fatality factors; machine learning; classifier ensemble (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/11/4111/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/11/4111/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:11:p:4111-:d:369177

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().