OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION

This study investigates the application of Geographic Information Systems (GIS) in traffic accident analysis and prediction. By integrating GIS with deep learning techniques, the research highlights how spatial data management and analysis can enhance road safety. Key objectives include identifying...

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Main Authors: Mohammed Shukur Alfaras, Oğuz Karan, Sefer Kurnaz
Format: Article
Language:English
Published: University of Kragujevac 2025-03-01
Series:Proceedings on Engineering Sciences
Subjects:
Online Access:https://pesjournal.net/journal/v7-n1/5.pdf
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author Mohammed Shukur Alfaras
Oğuz Karan
Sefer Kurnaz
author_facet Mohammed Shukur Alfaras
Oğuz Karan
Sefer Kurnaz
author_sort Mohammed Shukur Alfaras
collection DOAJ
description This study investigates the application of Geographic Information Systems (GIS) in traffic accident analysis and prediction. By integrating GIS with deep learning techniques, the research highlights how spatial data management and analysis can enhance road safety. Key objectives include identifying accident hotspots, optimizing traffic control systems, and improving emergency response. The methodology involves a comprehensive review of existing literature, emphasizing GIS's role in data integration, spatial analysis, and predictive modeling. Findings demonstrate that GIS significantly contributes to understanding traffic patterns, predicting accidents, and formulating targeted safety interventions. Challenges such as data complexity, real-time processing, and model interpretability are addressed, offering future directions for leveraging GIS in road safety management. The study concludes that GIS, combined with advanced analytics, presents a powerful tool for reducing traffic accidents and enhancing overall traffic safety.
format Article
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institution OA Journals
issn 2620-2832
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language English
publishDate 2025-03-01
publisher University of Kragujevac
record_format Article
series Proceedings on Engineering Sciences
spelling doaj-art-40e52cdfaf1b4706936f83c49e2199702025-08-20T01:57:49ZengUniversity of KragujevacProceedings on Engineering Sciences2620-28322683-41112025-03-0171334210.24874/PES07.01.005OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTIONMohammed Shukur Alfaras 0Oğuz Karan 1https://orcid.org/0000-0003-2962-4653Sefer Kurnaz 2https://orcid.org/0000-0002-7666-2639Electrical and Computer Engineering. Institute of Graduate Programs, Altinbas University, Istanbul, 34315 Turkiye Electrical and Computer Engineering. Institute of Graduate Programs, Altinbas University, Istanbul, 34315 Turkiye Electrical and Computer Engineering. Institute of Graduate Programs, Altinbas University, Istanbul, 34315 Turkiye This study investigates the application of Geographic Information Systems (GIS) in traffic accident analysis and prediction. By integrating GIS with deep learning techniques, the research highlights how spatial data management and analysis can enhance road safety. Key objectives include identifying accident hotspots, optimizing traffic control systems, and improving emergency response. The methodology involves a comprehensive review of existing literature, emphasizing GIS's role in data integration, spatial analysis, and predictive modeling. Findings demonstrate that GIS significantly contributes to understanding traffic patterns, predicting accidents, and formulating targeted safety interventions. Challenges such as data complexity, real-time processing, and model interpretability are addressed, offering future directions for leveraging GIS in road safety management. The study concludes that GIS, combined with advanced analytics, presents a powerful tool for reducing traffic accidents and enhancing overall traffic safety.https://pesjournal.net/journal/v7-n1/5.pdftraffic accident analysisgeographic information systems (gis)road safetyspatial data managementpredictive modelingemergency response optimizationtraffic control systemsdeep learning integration
spellingShingle Mohammed Shukur Alfaras
Oğuz Karan
Sefer Kurnaz
OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
Proceedings on Engineering Sciences
traffic accident analysis
geographic information systems (gis)
road safety
spatial data management
predictive modeling
emergency response optimization
traffic control systems
deep learning integration
title OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
title_full OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
title_fullStr OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
title_full_unstemmed OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
title_short OPTIMIZING ROAD SAFETY: THE ROLE OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN TRAFFIC ACCIDENT ANALYSIS AND PREDICTION
title_sort optimizing road safety the role of geographic information systems gis in traffic accident analysis and prediction
topic traffic accident analysis
geographic information systems (gis)
road safety
spatial data management
predictive modeling
emergency response optimization
traffic control systems
deep learning integration
url https://pesjournal.net/journal/v7-n1/5.pdf
work_keys_str_mv AT mohammedshukuralfaras optimizingroadsafetytheroleofgeographicinformationsystemsgisintrafficaccidentanalysisandprediction
AT oguzkaran optimizingroadsafetytheroleofgeographicinformationsystemsgisintrafficaccidentanalysisandprediction
AT seferkurnaz optimizingroadsafetytheroleofgeographicinformationsystemsgisintrafficaccidentanalysisandprediction