Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling
Road crashes have been increasing in the last decade in the Kingdom of Saudi Arabia (KSA). The aim of this study was to investigate the role of factors affecting the consequences of traffic crashes in the KSA. A retrospective study was conducted of crash data available from the KSA national e-govern...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Australasian College of Road Safety
2025-02-01
|
| Series: | Journal of Road Safety |
| Online Access: | https://doi.org/10.33492/JRS-D-25-1-2442769 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849722688294092800 |
|---|---|
| author | Saleh Al Sulaie |
| author_facet | Saleh Al Sulaie |
| author_sort | Saleh Al Sulaie |
| collection | DOAJ |
| description | Road crashes have been increasing in the last decade in the Kingdom of Saudi Arabia (KSA). The aim of this study was to investigate the role of factors affecting the consequences of traffic crashes in the KSA. A retrospective study was conducted of crash data available from the KSA national e-government open data portal. Crash data were extracted from the database including: crash details (location, time, consequence) and factors related to the involved road users (age, gender, education level, violation if related to the crash event). The modelling was performed using Bayesian Networks (BN). From 2019 to 2020, a total of 68,843 people were involved in traffic crashes in KSA. This included 58,471 cases with a crash outcome of damages and injuries and 10,372 cases with fatal outcomes. Multivariate analysis identified the highest probability of mortalities from traffic crashes (increased 15%) was related to males, low education level (illiterate), younger than 30 years of age and crashes occurring outside the city at night. These findings provide a clear direction and need to be the focus of preventive policies and action in the KSA. |
| format | Article |
| id | doaj-art-3e8806e462464ceeb71a138e6d803833 |
| institution | DOAJ |
| issn | 2652-4260 2652-4252 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Australasian College of Road Safety |
| record_format | Article |
| series | Journal of Road Safety |
| spelling | doaj-art-3e8806e462464ceeb71a138e6d8038332025-08-20T03:11:15ZengAustralasian College of Road SafetyJournal of Road Safety2652-42602652-42522025-02-0136110.33492/JRS-D-25-1-2442769Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network ModellingSaleh Al SulaieRoad crashes have been increasing in the last decade in the Kingdom of Saudi Arabia (KSA). The aim of this study was to investigate the role of factors affecting the consequences of traffic crashes in the KSA. A retrospective study was conducted of crash data available from the KSA national e-government open data portal. Crash data were extracted from the database including: crash details (location, time, consequence) and factors related to the involved road users (age, gender, education level, violation if related to the crash event). The modelling was performed using Bayesian Networks (BN). From 2019 to 2020, a total of 68,843 people were involved in traffic crashes in KSA. This included 58,471 cases with a crash outcome of damages and injuries and 10,372 cases with fatal outcomes. Multivariate analysis identified the highest probability of mortalities from traffic crashes (increased 15%) was related to males, low education level (illiterate), younger than 30 years of age and crashes occurring outside the city at night. These findings provide a clear direction and need to be the focus of preventive policies and action in the KSA.https://doi.org/10.33492/JRS-D-25-1-2442769 |
| spellingShingle | Saleh Al Sulaie Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling Journal of Road Safety |
| title | Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling |
| title_full | Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling |
| title_fullStr | Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling |
| title_full_unstemmed | Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling |
| title_short | Sensitivity Analysis of Factors Affecting Consequences Due to Traffic Crashes: A Bayesian Network Modelling |
| title_sort | sensitivity analysis of factors affecting consequences due to traffic crashes a bayesian network modelling |
| url | https://doi.org/10.33492/JRS-D-25-1-2442769 |
| work_keys_str_mv | AT salehalsulaie sensitivityanalysisoffactorsaffectingconsequencesduetotrafficcrashesabayesiannetworkmodelling |