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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| Format: | Article |
| Language: | English |
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University of Kragujevac
2025-03-01
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| Series: | Proceedings on Engineering Sciences |
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| 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 |
| id | doaj-art-40e52cdfaf1b4706936f83c49e219970 |
| institution | OA Journals |
| issn | 2620-2832 2683-4111 |
| 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 |