Machine learning and Geographic Information Systems (GIS)–based model for road crash severity prediction and behavioural pattern analysis
The proposed hybrid ML-GIS framework offers highly accurate severity prediction and reveals spatial and behavioral patterns critical for targeted safety interventions. Findings highlight the dominant influence of temporal and infrastructural factors over driver characteristics, supporting evidence-based engineering and enforcement strategies in Jordan.
Authors
- Azlan B. Abd Aziz
- Hamza A. Mashagba (ORCID: https://orcid.org/0000-0002-2952-2617)
- Fathiya Al Abri (ORCID: https://orcid.org/0000-0003-0012-5316)
- Lara A. Al-Mashagba
- Putra Sumari
- Mohammadnour Mashagba
- Samir Salem Al-Bawri
Institutions
- Universiti Sains Malaysia (MY)
- Multimedia University (MY)
- Universidad de Granada (ES)
- National University of Malaysia (MY)
Publication Details
- Journal
- Traffic Injury Prevention
- Published
- 2026-02-18
- DOI
- https://doi.org/10.1080/15389588.2025.2610435
- Primary Topic
- Traffic and Road Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00