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Utilizing GIS and Machine Learning for Traffic Accident Prediction in Urban Environment

Atif Ali Khan, Jawad Hussain

Abstract


Traffic accident prediction is crucial to preventive measures against accidents and effective traffic management. Identifying hotspots can facilitate the selection of the most critical survey points to note the contributing features. In this research, an effort has been made to identify hotspots and predict traffic accident occurrences in an urban area. Accident data was obtained from the Rescue 1122 Emergency Services of Faisalabad, and hotspots were identified using Moran’s I in ArcGIS. Results showed that most hotspots were located around the General Transport Stand (GTS) area due to the maximum number of road users. The temporal investigations showed that the accident occurrence was significant from 1 to 2 p.m. The identified hotspots were further investigated by conducting a field survey. Essential features such as road geometric features, road furniture, and traffic data were used for developing Machine Learning Algorithms for accident prediction. Using Computer Vision, traffic data was extracted from recorded videos. Random forest, linear regression, and Decision tree algorithms were developed using Python in the Jupyter Notebook environment. The decision tree algorithm showed a maximum accuracy of 84.4%. The analysis of contributing factors revealed that road measurements had the maximum effect on accident occurrence.

 

Doi: 10.28991/CEJ-2024-010-06-013

Full Text: PDF


Keywords


ArcGIS; Hotspots Analysis; Local Moran’s I Static; Spatial Analysis; Road Traffic Accidents; Machine Learning; Traffic Accident Prediction.

References


WHO. (2022). Road traffic injuries. World Health Organization (WHO), Geneva, Switzerland. Available online: https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries (accessed on May 2024).

PBS. (2023). Announcement of Results of 7th Population and Housing Census-2023 ‘The Digital Census’. Pakistan Bureau of Statistics, Islamabad, Pakistan. Available online: https://www.pbs.gov.pk/content/announcement-results-7th-population-and-housing-census-2023-digital-census (accessed on March 2024).

World Life Expectancy. (2023). World health rankings. Available online: https://www.worldlifeexpectancy.com/cause-of-death/road-traffic-accidents/by-country/ (accessed on May 2024).

Rais, R. B. (2023). Road safety in Pakistan is the not-so-silent killer everybody is ignoring. ARAB NEWS, Riyadh, Saudi Arabia.

Pusuluri, V. L., & Dangeti, M. R. (2024). Applications of QGIS and machine learning for road crash spot identification. Earth Science Informatics, 17(3), 2331–2346. doi:10.1007/s12145-024-01271-0.

Khatun, M. S., Hossain, M. A., Kabir, M. A., & Rahman, M. A. (2024). Identification and analysis of accident black spots using Geographic Information System (GIS): A study on Kushtia-Jhenaidah national highway (N704), Bangladesh. Heliyon, 10(3), e25952. doi:10.1016/j.heliyon.2024.e25952.

Chun, U., Lim, J., & Kim, H. (2024). Analysis of Hotspots in and outside School Zones: A Case Study of Seoul. Journal of Advanced Transportation, 2024, 1–13. doi:10.1155/2024/6613603.

Hammas, M., & Al-Modayan, A. (2022). Spatial Analysis of Traffic Accidents in the City of Medina Using GIS. Journal of Geographic Information System, 14(05), 462–477. doi:10.4236/jgis.2022.145025.

Feizizadeh, B., Omarzadeh, D., Sharifi, A., Rahmani, A., Lakes, T., & Blaschke, T. (2022). A GIS-Based Spatiotemporal Modelling of Urban Traffic Accidents in Tabriz City during the COVID-19 Pandemic. Sustainability (Switzerland), 14(12), 7468. doi:10.3390/su14127468.

Rahman, M. T., Jamal, A., & Al-Ahmadi, H. M. (2020). Examining hotspots of traffic collisions and their spatial relationships with land use: A GIS-based geographically weighted regression approach for Dammam, Saudi Arabia. ISPRS International Journal of Geo-Information, 9(9), 540. doi:10.3390/ijgi9090540.

ESRI. (2024). Geographic Information System. Geographic information system company (ESRI), Redlands, United States. Available online: https://www.esri.com/en-us/what-is-gis/overview (accessed on May 2024).

Le, K. G., Liu, P., & Lin, L.-T. (2020). Traffic accident hotspot identification by integrating kernel density estimation and spatial autocorrelation analysis: a case study. International Journal of Crashworthiness, 27(2), 543–553. doi:10.1080/13588265.2020.1826800.

Zahran, E.-S. M. M., Tan, S. J., Tan, E. H. A., Mohamad ’Asri Putra, N. A. ’Atiqah B., Yap, Y. H., & Abdul Rahman, E. K. (2019). Spatial analysis of road traffic accident hotspots: evaluation and validation of recent approaches using road safety audit. Journal of Transportation Safety & Security, 13(6), 575–604. doi:10.1080/19439962.2019.1658673.

Al-Aamri, A. K., Hornby, G., Zhang, L.-C., Al-Maniri, A. A., & Padmadas, S. S. (2021). Mapping road traffic crash hotspots using GIS-based methods: A case study of Muscat Governorate in the Sultanate of Oman. Spatial Statistics, 42, 100458. doi:10.1016/j.spasta.2020.100458.

Srikanth, Dr. L., Srikanth, I., & Arockiasamy, Dr. M. (2019). Identification of Traffic Accident Hotspots using Geographical Information System (GIS). International Journal of Engineering and Advanced Technology, 9(2), 4429–4438. doi:10.35940/ijeat.b3848.129219.

Afolayan, A., Easa, S. M., Abiola, O. S., Alayaki, F. M., & Folorunso, O. (2022). GIS-Based Spatial Analysis of Accident Hotspots: A Nigerian Case Study. Infrastructures, 7(8), 103. doi:10.3390/infrastructures7080103.

Kričković, E., Lukić, T., Srejić, T., Stojšić-Milosavljević, A., Stojanović, V., & Kričković, Z. (2024). Spatial-temporal and trend analysis of traffic accidents in AP Vojvodina (North Serbia). Open Geosciences, 16(1), 20220630. doi:10.1515/geo-2022-0630.

Umair, M., Rana, I. A., & Lodhi, R. H. (2022). The impact of urban design and the built environment on road traffic crashes: A case study of Rawalpindi, Pakistan. Case Studies on Transport Policy, 10(1), 417–426. doi:10.1016/j.cstp.2022.01.002.

Maurya, R. K., & Swain, J. B. (2022). Modeling and Analysis of Accident in an Urban Area (No. 9009). EasyChair, Wythenshawe, United Kingdom.

Srikanth, L., & Srikanth, I. (2020). A Case Study on Kernel Density Estimation and Hotspot Analysis Methods in Traffic Safety Management. 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), Bengaluru, India. doi:10.1109/comsnets48256.2020.9027448.

Ahmad, A., Hossain, K., & Hossain, M. (2020). Identification of Urban Traffic Accident Hotspot Zones Using GIS: A Case Study of Dhaka Metropolitan Area. Journal of Geographical Studies, 3(1), 36–42. doi:10.21523/gcj5.19030104.

Alam, M. S., & Tabassum, N. J. (2023). Spatial pattern identification and crash severity analysis of road traffic crash hot spots in Ohio. Heliyon, 9(5), e16303. doi:10.1016/j.heliyon.2023.e16303.

Mekonnen, A. A., Sipos, T., & Krizsik, N. (2023). Identifying Hazardous Crash Locations Using Empirical Bayes and Spatial Autocorrelation. ISPRS International Journal of Geo-Information, 12(3), 85. doi:10.3390/ijgi12030085.

Lee, A. S., Lin, W. H., Gill, G. S., & Cheng, W. (2019). An enhanced empirical bayesian method for identifying road hotspots and predicting number of crashes. Journal of Transportation Safety & Security, 11(5), 562-578. doi:10.1080/19439962.2018.1450314.

arirforoush, H., Bellalite, L., & Bénié, G. B. (2019). Spatial and Temporal Analysis of Seasonal Traffic Accidents. American Journal of Traffic and Transportation Engineering, 4(1), 7. doi:10.11648/j.ajtte.20190401.12.

Hovenden, E., & Liu, G.-J. (2020). Use of Spatial Analysis Techniques to Identify Statistically Significant Crash Hot Spots in Metropolitan Melbourne. Journal of Road Safety, 31(4), 36–58. doi:10.33492/jrs-d-19-00249.

Qalb, A., Arshad, H. S. H., Nawaz, M. S., & Hafeez, A. (2023). Risk reduction via spatial and temporal visualization of road accidents: a way forward for emergency response optimization in developing countries. International Journal of Injury Control and Safety Promotion, 30(2), 310–320. doi:10.1080/17457300.2022.2164312.

Erenler, A. K., & Gümüş, B. (2019). Analysis of road traffic accidents in Turkey between 2013 and 2017. Medicina (Lithuania), 55(10), 679. doi:10.3390/medicina55100679.

Alkhadour, W., Zraqou, J., Al-Helali, A., & Al-Ghananeem, S. (2021). Traffic Accidents Detection using Geographic Information Systems (GIS). International Journal of Advanced Computer Science and Applications, 12(4), 484-494. doi:10.14569/ijacsa.2021.0120462.

Hazaymeh, K., Almagbile, A., & Alomari, A. H. (2022). Spatiotemporal Analysis of Traffic Accidents Hotspots Based on Geospatial Techniques. ISPRS International Journal of Geo-Information, 11(4), 260. doi:10.3390/ijgi11040260.

Wang, Z. Z., Lu, Y. N., Zou, Z. H., Ma, Y. H., & Wang, T. (2022). Applying OHSA to Detect Road Accident Blackspots. International Journal of Environmental Research and Public Health, 19(24), 16970. doi:10.3390/ijerph192416970.

Unsar, S., & Sut, N. (2009). General assessment of the occupational accidents that occurred in Turkey between the years 2000 and 2005. Safety Science, 47(5), 614-619. doi:10.1016/j.ssci.2008.08.001.

Le, K. G., Liu, P., & Lin, L. T. (2020). Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam. Geo-spatial Information Science, 23(2), 153-164. doi:10.1080/10095020.2019.1683437.

Vyshnavi, K. G., & Nalini, V. K. (2022). Machine Learning Algorithms for Road Accident Analysis and Forecasting. International Journal of Research in Engineering and Science, 10, 283–288.

Venkat, A., Vijey, G. K., & Susan Thomas, I. (2020). Machine Learning Based Analysis for Road Accident Prediction. International Journal of Emerging Technology and Innovative Engineering, 6(2), 2394–6598.

Megibaru, L., & Atnafu, B. (2019). Design a Machine Learning Model to Identify and Predict the Cause of Vehicle Accidents in East Gojjam, Amhara, Ethiopia. International Journal of Innovative Research in Science, Engineering and Technology, 8(12), 11856–11863.

Guerra, A., Gadhiya, V., & Srisurin, P. (2022). Crash Prediction on Road Segments Using Machine Learning Methods. ASEAN Engineering Journal, 12(3), 27–37. doi:10.11113/AEJ.V12.17601.

Dogru, N., & Subasi, A. (2018). Traffic accident detection using random forest classifier. 2018 15th Learning and Technology Conference (L&T). doi:10.1109/lt.2018.8368509.

Sripuram, A., Jayasree., T., Vaishnavi, T., Reddy, V. R., & Mtech, P. C. (2022). Road Accident Analysis using Machine Learning. International Research Journal of Modernization in Engineering Technology and Science, 4(3), 1364-1371.

Ulu, M., Kilic, E., & Türkan, Y. S. (2024). Prediction of Traffic Incident Locations with a Geohash-Based Model Using Machine Learning Algorithms. Applied Sciences, 14(2), 725. doi:10.3390/app14020725.

Sridevi, N., Keerthana, M. V., Pal, M. V., Nikshitha, T. R., & Jyothi, P. (2020). Road accident analysis using machine learning. International Journal of Research in Engineering, Science and Management, 3(5), 859-861.

Azimjonov, J., Özmen, A., & Varan, M. (2023). A vision-based real-time traffic flow monitoring system for road intersections. Multimedia Tools and Applications, 82(16), 25155–25174. doi:10.1007/s11042-023-14418-w.

Torres, K. A. R., & Asor, J. R. (2021). Machine learning approach on road accidents analysis in Calabarzon, Philippines: An input to road safety management. Indonesian Journal of Electrical Engineering and Computer Science, 24(2), 993–1000. doi:10.11591/ijeecs.v24.i2.pp993-1000.

Růžička, J., Bělinová, Z., Korec, V., Cikhardtová, K., & Tichý, T. (2019). Prediction of traffic accidents by using neural network. Archives of Transport System Telematics, 12(4), 22-26.

Jadhav, A., Jadhav, S., Jalke, A., & Suryavanshi, K. (2020). Road accident analysis and prediction of accident severity using machine learning. International Research Journal of Engineering and Technology (IRJET), 7(12), 740-747.

Santos, D., Saias, J., Quaresma, P., & Nogueira, V. B. (2021). Machine learning approaches to traffic accident analysis and hotspot prediction. Computers, 10(12), 157. doi:10.3390/computers10120157.

Candefjord, S., Muhammad, A. S., Bangalore, P., & Buendia, R. (2021). On Scene Injury Severity Prediction (OSISP) machine learning algorithms for motor vehicle crash occupants in US. Journal of Transport and Health, 22. doi:10.1016/j.jth.2021.101124.

Najafi Moghaddam Gilani, V., Hosseinian, S. M., Ghasedi, M., & Nikookar, M. (2021). Data-Driven Urban Traffic Accident Analysis and Prediction Using Logit and Machine Learning-Based Pattern Recognition Models. Mathematical Problems in Engineering, 2021, 1–11. doi:10.1155/2021/9974219.

Yassin, S. S., & Pooja. (2020). Road accident prediction and model interpretation using a hybrid K-means and random forest algorithm approach. SN Applied Sciences, 2(9). doi:10.1007/s42452-020-3125-1.

Rana, V., Joshi, H., Parmar, D., Jadhav, P., & Kanojiya, M. (2019). Road accident prediction using machine learning algorithm. International Research Journal of Engineering and Technology, 6(3), 3934-3496.

ESRI. (2023). ArcGIS: Geographic Information System Company (ESRI), Redlands, United States. Available online: https://www.esri.com/en-us/arcgis/about-arcgis/overview (accessed on March 2024).

Harirforoush, H., & Bellalite, L. (2019). A new integrated GIS-based analysis to detect hotspots: A case study of the city of Sherbrooke. Accident Analysis and Prevention, 130, 62–74. doi:10.1016/j.aap.2016.08.015.

Aghasi, N. H. M. (2019). Application of GIS for Urban Traffic Accidents: A Critical Review. Journal of Geographic Information System, 11(01), 82–96. doi:10.4236/jgis.2019.111007.

Gedamu, W. T., Plank-Wiedenbeck, U., & Wodajo, B. T. (2024). A spatial autocorrelation analysis of road traffic crash by severity using Moran’s I spatial statistics: A comparative study of Addis Ababa and Berlin cities. Accident Analysis & Prevention, 200, 107535. doi:10.1016/j.aap.2024.107535.

Manap, N., Borhan, M. N., Yazid, M. R. M., Hambali, M. K. A., & Rohan, A. (2021). Identification of Hotspot Segments with a Risk of Heavy-Vehicle Accidents Based on Spatial Analysis at Controlled-Access Highway. Sustainability, 13(3), 1487. doi:10.3390/su13031487.

Haybat, H., Zerenoğlu, H., & Özlü, T. (2022). Temporal and Spatial Analysis of Traffic Accidents: The Case of Bursa City. International Journal of Geography and Geography Education, 45, 404–423. doi:10.32003/igge.1016204.

Seasons of the Year. (2024). Seasons in Pakistan. Seasons of the Year, Malakhovka, Russia. Available online: https://seasonsyear.com/Pakistan (accessed on March 2024).


Full Text: PDF

DOI: 10.28991/CEJ-2024-010-06-013

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Copyright (c) 2024 Atif Ali Khan, Jawad Hussain

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