Exploring the Association Rules of Road Traffic Accidents
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Abstract
In this research, the objective is to extract patterns of road traffic accidents in Thailand using association rules and the FP-growth algorithm was employed to mine frequent patterns. The road accident data in Thailand used in this study was collected from Information and Communication Technology Center, Office of the Permanent Secretary of the Ministry of Transport between January 1, 2019 and September 30, 2022, with a total of 74,231 instances and 10 attributes included time, month, provinces, weather, types of cars, accident causes, accident form, road characteristics, road types, and results of accidents. The association analysis results on Thailand road traffic accidents showed that the most common patterns of road traffic accidents were rear-end collisions, rollovers, and falls onto the road. The speed limit violation led to the collision. Accidents are more likely to occur when the road is straight and no slope, and clear weather. Furthermore, the most common types of vehicles engaged are motorcycles, while the roads of the Ministry of Highway were the scene of the most collisions.
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References
OECD. 2022. Road accidents (indicator). Available at: https://data.oecd.org/transport/ road-accidents.htm. Retrieved 28 October 2022.
WHO. 2022. Road traffic injuries. Available at: https://www.who.int/news- room/fact-sheets/detail/road-traffic-injuries. Retrieved 31 October 2022.
WHO. 2018. Global Status Report on Road Safety 2018. Available at: https://www. who.int/publications/i/item/9789241565684. Retrieved 29 October 2022.
ศรีสิทธิ์ วงศ์วรจรรย์. 2565. เปิดสถิติ “อุบัติเหตุบนถนน” ประเทศไทยเกิดเหตุอะไรบ่อยสุด?. กรุงเทพธุรกิจ. แหล่งข้อมูล : https://www.bangkokbiznews.com/social/984601. ค้นเมื่อวันที่ 1 พฤศจิกายน 2565.
Cai, Q. 2020. Cause analysis of traffic accidents on urban roads based on an improved association rule mining algorithm. IEEE Access, 8, 75607-75615.
Tariq, M., Mehmood, N. Q., and Mahfooz, S. Z. 2022. Discovering associated factors behind road accidents using association rule mining: A case study from Gujarat, Pakistan. World journal of advanced research and reviews, 15(3), 1-11.
Salman, R.E., and Alzaatreh, A. 2022. Market Basket Analysis of Chicago Road Accidents. Proceedings of 2022 Advances in Science and Engineering Technology International Conferences (ASET), United Arab Emirates, 1-7.
Shahin, M., Iman, M.R.H., Kaushik, M., Sharma, R., Ghasempouri, T., and Draheim, D. 2022. Exploring Factors in a Crossroad Dataset Using Cluster-Based Association Rule Mining. Procedia Computer Science, 201, 231-238.
Dogrul, G. and Alkan, M. 2022. Investigation of fatal traffic accidents occurring outside of the city in Turkey using data mining. Selcuk University Journal of Engineering Sciences, 21(2), 75-85.
Dalai, B. and Landge, V.S. 2022. Crash risk factor identification using association rules in Nagpur city, Maharashtra, India. Current Science, 123(6), 781-790.
Feng, M., Zheng, J., Ren, J. and Xi, Y. 2019. Association Rule Mining for Road Traffic Accident Analysis: A Case Study from UK. Proceedings of 10th International Conference BICS 2019. China, 520–529.
ดวงใจ รุ่งพัฒนกิจชัย. 2561. ความสัมพันธ์ของปัจจัยที่เกี่ยวข้องกับอุบัติเหตุรถจักรยานยนต์เพื่อ การสืบสวนคดีอุบัติเหตจราจรเชิงลึกโดยใช้เทคนิคกฎความสัมพันธ์. วิทยานิพนธ์วิทยาศาสตรมหาบัณฑิต, สาขาวิชานิติวิทยาศาสตร์, บัณฑิตวิทยาลัย, มหาวิทยาลัยศิลปากร. [Duengjai Rungpatanakijchai. 2018. The relationship factors related to motorcycle accident for in-depth road traffic accident investigations using the Association Rule technique. M.Sc. Thesis, Forensic Science, Graduate School, Silpakorn University. (in Thai)]
ศิริจรรยา จันทร์มี และไกรศักดิ์ เกษร. 2565. การวิเคราะห์การเคลื่อนย้ายของนักท่องเที่ยว โดย ใช้ข้อมูลจากเครือข่ายสังคมจากวิธีการกฎความสัมพันธ์. วารสารวิทยาศาสตร์ลาดกระบัง. 31(1), 120-141. [Janmee, S. and Kesorn, K. 2022. Tourist Movement Analysis Based on Social Network Information Using Association Rules. Journal of Science Ladkrabang, 31(1), 120-141. (in Thai)]
Agrawal, R., Imieliński, T. and Swami, A. 1993. Mining association rules between sets of items in large databases. Proceedings of the 1993 ACM SIGMOD international conference on Management of data. The United States of America, 207-216.
Han, J., Pei, J., Yin, Y. and Mao, R. 2004. Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data mining and knowledge discovery, 8(1), 53-87.
El Mazouri, F.Z., Abounaima, M.C., Najah, S. and Zenkouar, K. 2019. Data mining for road accident analysis in a big data context. Proceedings of ICCWCS 2019: Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019. Morocco, 255-263.
Kumar, S., Toshniwal, D. and Parida, M. 2017. A comparative analysis of heterogeneity in road accident data using data mining techniques. Evolving systems, 8(2), 147-155.
Distefano, N., Leonardi, S., Pulvirenti, G., Romano, R., Boer, E. and Wooldridge, E. 2022. Mining of the association rules between driver electrodermal activity and speed variation in different road intersections. IATSS research, 46(2), 200-213.
กลุ่มสถิติสารสนเทศ. 2564. รายงานอุบัติเหตุจราจรบนทางหลวงแผ่นดิน 2564. แหล่งข้อมูล : https://bhs.doh.go.th/download/accident. ค้นเมื่อวันที่ 10 พฤศจิกายน 2565.