Shaping the future through Artificial Intelligent technologies to reduce vehicle accidents in Abu Dhabi
type: CreativeWork
description: Traffic accidents (TAs) constitute one of the top killers in the United Arab Emirates (UAE). Without practical approaches to address the TAs in Abu Dhabi, the region is likely to experience continued economic losses and health burden to the affected families and country. This study identified interventions and solutions for mitigating TAs in Abu Dhabi. The study was guided by research questions that focused on the causes of accidents and how to mitigate TA. The study was based on descriptive observational methodology where quantitative data was collected using a detailed survey questionnaire (n= 300) that assessed various aspects relating to the driver’s behaviour. The 2007 to 2017 MVC injuries baseline data were also analyzed. Data on TAs control strategies from existing studies were used to assess the artificial intelligent approaches in road safety management. The quantitative data analysis was carried out using SPSS software and Microsoft Excel software. The study findings showed that the most common traffic problems on Abu Dhabi's roads include driver-related factors, vehicular factors, and road condition-related factors. Risky overtaking, violation of the need to keep a safe distance and violation of speed limits were noted as the significant violations associated with the traffic problems on Abu Dhabi’s roads. The baseline data analysis findings indicated that the three regions in Abu Dhabi registered a general reduction in TAs over the 10 years (2007 to 2017). However, the reduction in Al Ain was minimal over the study period. The study’s findings relating to the forecasting of the accident trends showed that the Western region and Abu Dhabi would continue to experience a reduction in TAs in the future while the frequency of accidents in Al Ain will increase between 2017 and 2024. Most of the accidents in Abu Dhabi are associated with driver behaviour. The identified risky driver behaviours include the failure to keep adequate distance, maintain recommended …
abstract: Traffic accidents (TAs) constitute one of the top killers in the United Arab Emirates (UAE). Without practical approaches to address the TAs in Abu Dhabi, the region is likely to experience continued economic losses and health burden to the affected families and country. This study identified interventions and solutions for mitigating TAs in Abu Dhabi. The study was guided by research questions that focused on the causes of accidents and how to mitigate TA. The study was based on descriptive observational methodology where quantitative data was collected using a detailed survey questionnaire (n= 300) that assessed various aspects relating to the driver’s behaviour. The 2007 to 2017 MVC injuries baseline data were also analyzed. Data on TAs control strategies from existing studies were used to assess the artificial intelligent approaches in road safety management. The quantitative data analysis was carried out using SPSS software and Microsoft Excel software. The study findings showed that the most common traffic problems on Abu Dhabi's roads include driver-related factors, vehicular factors, and road condition-related factors. Risky overtaking, violation of the need to keep a safe distance and violation of speed limits were noted as the significant violations associated with the traffic problems on Abu Dhabi’s roads. The baseline data analysis findings indicated that the three regions in Abu Dhabi registered a general reduction in TAs over the 10 years (2007 to 2017). However, the reduction in Al Ain was minimal over the study period. The study’s findings relating to the forecasting of the accident trends showed that the Western region and Abu Dhabi would continue to experience a reduction in TAs in the future while the frequency of accidents in Al Ain will increase between 2017 and 2024. Most of the accidents in Abu Dhabi are associated with driver behaviour. The identified risky driver behaviours include the failure to keep adequate distance, maintain recommended …
author: Alshamsi, I
language: en
date published: 2021
date modified: 2026-07-24T04:26:14Z
provider: U. of Salford
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: U. of Salford