Artificial Intelligence in Road Traffic Accident Prediction
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Alagarsamy, S., Malathi, M., Manonmani, M., Sanathani, T., & Kumar, A. S. (2021). Prediction of road accidents using machine learning technique. 2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA), 1695–1701. doi: 10.1109/ICECA52323.2021.9675852
Alrajhi, M., & Kamel, M. (2019). A deep-learning model for predicting and visualizing the risk of road traffic accidents in Saudi Arabia: A tutorial approach. International Journal of Advanced Computer Science and Applications, 10(11). doi: 10.14569/IJACSA.2019.0101166
Augustine, T., & Shukla, S. (2022). Road accident prediction using machine learning approaches. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 808–811. doi: 10.1109/ICACITE53722.2022.9823499
Babu, S. N., & Tamilselvi, J. (2019). Generating road accident prediction set with road accident data analysis using enhanced expectation-maximization clustering algorithm and improved association rule mining. Journal Europeen Des Systemes Automatises, 52(1). doi: 10.18280/jesa.520108
Bahiru, T. K., Manjula, V. S., Akele, T. B., Tesfaw, E. A., & Belay, T. D. (2023). Mining road traffic accident data for prediction of accident severity. 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 606–612. doi: 10.1109/IDCIoT56793.2023.10053409
Ballamudi, K. R. (2019). Road accident analysis and prediction using machine learning algorithmic approaches. Asian Journal of Humanity, Art and Literature, 6(2), 185–192. doi: 10.18034/ajhal.v6i2.529
Barachi, M. El, Kamoun, F., Ferdaos, J., Makni, M., & Amri, I. (2020). An artificial intelligence based crowdsensing solution for on-demand accident scene monitoring. Procedia Computer Science, 170, 303–310. doi: 10.1016/j.procs.2020.03.044
Becker, N., Rust, H. W., & Ulbrich, U. (2020). Predictive modeling of hourly probabilities for weather-related road accidents. Natural Hazards and Earth System Sciences, 20(10), 2857–2871. doi: 10.5194/nhess-20-2857-2020
Begum, A. P. S. B. (2022). Road accidents prediction and classification. International Journal for Research in Applied Science and Engineering Technology, 10(6), 4488–4491. doi: 10.22214/ijraset.2022.44988
Behura, A., & Behura, A. (2020). Road accident prediction and feature analysis by using deep learning. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1–7. doi: 10.1109/ICCCNT49239.2020.9225336
Bokaba, T., Doorsamy, W., & Paul, B. S. (2022). Comparative study of machine learning classifiers for modelling road traffic accidents. Applied Sciences (Switzerland), 12(2). doi: 10.3390/app12020828
Boo, Y., & Choi, Y. (2021). Comparison of prediction models for mortality related to injuries from road traffic accidents after correcting for undersampling. International Journal of Environmental Research and Public Health, 18(11), 5604. doi: 10.3390/ijerph18115604
Boo, Y., & Choi, Y. (2022). Comparison of mortality prediction models for road traffic accidents: an ensemble technique for imbalanced data. BMC Public Health, 22(1), 1476. doi: 10.1186/s12889-022-13719-3
Borucka, A., Kozłowski, E., Oleszczuk, P., & Świderski, A. (2020). Predictive analysis of the impact of the time of day on road accidents in Poland. Open Engineering, 11(1), 142–150. doi: 10.1515/eng-2021-0017
Budiawan, W., Sriyanto, Saptadi, S., Arvianto, A., Pamuji, H., & Andarani, P. (2022). Design of traffic accident prediction model in toll road using a decision tree algorithm. International Journal of Applied Science and Engineering Review, 03(06), 11–31. doi: 10.52267/IJASER.2022.3602
Charandabi, N. K., Gholami, A., & Bina, A. A. (2022). Road accident risk prediction using generalized regression neural network optimized with self-organizing map. Neural Computing and Applications, 34(11), 8511–8524. doi: 10.1007/s00521-021-06549-8
Chen, L., Li, C. Y., Zhan, L., Tan, Q., Tian, X. M., Cheng, H., & Li, K. (2022). Influencing factors analysis and prediction of urban road traffic accident patterns. Chang’an Daxue Xuebao (Ziran Kexue Ban)/Journal of Chang’an University (Natural Science Edition), 42(4). doi: 10.19721/j.cnki.1671-8879.2022.04.010
Cheng, R., Zhang, M.-M., & Yu, X.-M. (2019). Prediction model for road traffic accident based on random forest. DEStech Transactions on Social Science, Education and Human Science, icesd. doi: 10.12783/dtssehs/icesd2019/28223
Dabhade, S. (2020). Road accident analysis and prediction using machine learning. International Journal for Research in Applied Science and Engineering Technology, 8(1), 100–103. doi: 10.22214/ijraset.2020.1018
Dia, Y., Faty, L., Sall, O., Tona Landu, T., & Ngor Sarr, E. (2022). Predicting the severity of the road accidents in Senegal: An empirical study. 2022 the 5th International Conference on Data Storage and Data Engineering (DSDE), 91–96. doi: 10.1145/3528114.3528129
Dia, Y., Faty, L., Sarr, M. D., Sall, O., Bousso, M., & Landu, T. T. (2022). Study of supervised learning algorithms for the prediction of road accident severity in Senegal. 2022 7th International Conference on Computational Intelligence and Applications (ICCIA), 123–127. doi: 10.1109/ICCIA55271.2022.9828434
Dias, D., Silva, J. S., & Bernardino, A. (2023). The prediction of road accident risk through data mining: A case study from Setubal, Portugal. Informatics, 10(1), 17. doi: 10.3390/informatics10010017
Donchenko, D., Sadovnikova, N., & Parygin, D. (2020). Prediction of road accidents’ severity on Russian roads using machine learning techniques. In Lecture Notes in Mechanical Engineering (pp. 1493–1501). doi: 10.1007/978-3-030-22063-1_157
Farina, E., Nabhen, J. J., Dacoregio, M. I., Batalini, F., & Moraes, F. Y. (2022). An overview of artificial intelligence in oncology. In Future Science OA (Vol. 8, Issue 4). doi: 10.2144/fsoa-2021-0074
Fiorentini, N., & Losa, M. (2020). Handling imbalanced data in road crash severity prediction by machine learning algorithms. Infrastructures, 5(7), 61. doi: 10.3390/infrastructures5070061
Franklin, R. J., & Mohana. (2020). Traffic signal violation detection using artificial intelligence and deep learning. 2020 5th International Conference on Communication and Electronics Systems (ICCES), 839–844. doi: 10.1109/ICCES48766.2020.9137873
Gangwani, D., & Gangwani, P. (2021). Applications of machine learning and artificial intelligence in intelligent transportation system: A review. In Lecture Notes in Electrical Engineering (Vol. 778, pp. 203–216). doi: 10.1007/978-981-16-3067-5_16
Gorzelańczyk, P., Jurkovič, M., Kalina, T., & Mohanty, M. (2022). Forecasting the road accident rate and the impact of the covid 19 on its frequency in the polish provinces. Communications - Scientific Letters of the University of Zilina, 24(4), A216–A231. doi: 10.26552/com.C.2022.4.A216-A231
Guo, Q., Guo, B., Wang, Y., Tian, S., & Chen, Y. (2022). A combined prediction model composed of the GM (1,1) model and the BP neural network for major road traffic accidents in China. Mathematical Problems in Engineering, 2022, 1–11. doi: 10.1155/2022/8392759
Gupta, U., MK, V., & Srinivasa, G. (2022). A comprehensive study of road traffic accidents: Hotspot analysis and severity prediction using machine learning. 2022 IEEE Bombay Section Signature Conference (IBSSC), 1–6. doi: 10.1109/IBSSC56953.2022.10037449
Gutierrez-Osorio, C., & Pedraza, C. (2020). Modern data sources and techniques for analysis and forecast of road accidents: A review. Journal of Traffic and Transportation Engineering (English Edition), 7(4), 432–446. doi: 10.1016/j.jtte.2020.05.002
Huamaní, E. L., Mantari, A. A., Leon-Ayala, R., & Meneses-Claudio, B. (2023). Development of artificial intelligence algorithm for the analysis and prediction of car accidents on the roads of Peru. International Journal of Engineering Trends and Technology, 71(2), 52–60. doi: 10.14445/22315381/IJETT-V71I2P207
Infante, P., Jacinto, G., Santos, D., Nogueira, P., Afonso, A., Silva, M., Nogueira, V., Rego, L., Quaresma, P., Saias, J., Gois, P., & Rebelo Manuel, P. (2023). Prediction of road traffic accidents on a road in Portugal: A mixed artificial intelligence, statistics, and geographic information systems approach. SSRN Electronic Journal. doi: 10.2139/ssrn.4334671
Jain, S., Krishna, S., Pruthi, S., Jain, R., & Nagrath, P. (2022). Analysis of road accidents in India and prediction of accident severity. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 71, pp. 69–87). doi: 10.1007/978-981-16-2937-2_6
Jha, A. N., Chatterjee, N., & Tiwari, G. (2021). A performance analysis of prediction techniques for impacting vehicles in hit-and-run road accidents. Accident Analysis & Prevention, 157, 106164. doi: 10.1016/j.aap.2021.106164
Ji, W., Yang, T., Yuan, Q., Cheng, G., & Yu, S. (2023). Prediction model of accident vehicle speed based on artificial intelligence decision tree algorithm. In Lecture Notes in Electrical Engineering: Vol. 941 LNEE (pp. 317–324). doi: 10.1007/978-981-19-4786-5_44
Joshi, S., Alsadoon, A., Senanayake, S. M. N. A., Prasad, P. W. C., Yong, S. Y., Elchouemi, A., & Vo, T. H. (2020). Pattern mining predictor system for road accidents. In Communications in Computer and Information Science (Vol. 1287, pp. 605–615). doi: 10.1007/978-3-030-63119-2_49
Kaliraja, C., Chitradevi, D., & Rajan, A. (2022). Predictive analytics of road accidents using machine learning. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 1782–1786. doi: 10.1109/ICACITE53722.2022.9823773
Kandasamy, S., Akshaya, S., Anush, J., & Arunkumar, S. (2021). A machine learning approach to analyze and predict the severity of road accidents. Annals of the Romanian Society for Cell Biology.
Khan, S., Adnan, A., & Iqbal, N. (2022). Applications of artificial intelligence in transportation. 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET), 1–6. doi: 10.1109/ICECET55527.2022.9872928
Kim, D., Jung, S., & Yoon, S. (2021). Risk prediction for winter road accidents on expressways. Applied Sciences (Switzerland), 11(20). doi: 10.3390/app11209534
Kim, H., Kim, J.-T., Shin, S., Lee, H., & Lim, J. (2022). Prediction of run-off road crash severity in South Korea’s highway through tree augmented naïve bayes learning. Applied Sciences, 12(3), 1120. doi: 10.3390/app12031120
Kim, Y., Park, J., & Oh, C. (2021). A crash prediction method based on artificial intelligence techniques and driving behavior event data. Sustainability, 13(11), 6102. doi: 10.3390/su13116102
Kshirsagar, P. R., Dadheech, P., Yuvaraj, T., Moorthy, C. A. S., & Upadhyaya, M. (2022). Fatigue detection using artificial intelligence. AIP Conference Proceedings, 2393, 020080. doi: 10.1063/5.0074121
Kumar, B. V., Srinivas, K. K., Anudeep, P., Yadav, N. S., Kumar, G. V., & Harsha Vardhini, P. A. (2021). Artificial intelligence based algorithms for driver distraction detection: A review. 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC), 2021-October, 383–386. doi: 10.1109/ISPCC53510.2021.9609349
Kushwaha, M., & Abirami, M. S. (2022). Comparative analysis on the prediction of road accident severity using machine learning algorithms. International Conference on Micro-Electronics and Telecommunication Engineering, 373, 269–280. doi: 10.1007/978-981-16-8721-1_26
Lazar, H., & Jarir, Z. (2022). Road traffic accident prediction: a driving behavior approach. 2022 8th International Conference on Optimization and Applications (ICOA), 1–4. doi: 10.1109/ICOA55659.2022.9934000
Lu, Y., Wu, J., Shao, S., Shi, S., Zhou, R., & Wang, W. (2022). Prediction model for road transport accidents of hazardous chemicals based on Bayesian network. China Safety Science Journal, 32(3). doi: 10.16265/j.cnki.issn1003-3033.2022.03.024
Lv, Z., & Xie, S. (2021). Artificial intelligence in the digital twins: State of the art, challenges, and future research topics. Digital Twin, 1, 12. doi: 10.12688/digitaltwin.17524.1
Mane, G., & Rathod, V. U. (2022). Road accident prediction using machine learning techniques. International Journal of Research in Engineering and Science (IJRES), 10. https://www.ijres.org/papers/Volume-10/Issue-7/1007808815.pdf
Mapa, J. S. (2019). Road traffic accident case status prediction integrating a modified C4.5 algorithm. International Journal of Advanced Trends in Computer Science and Engineering, 8(5), 2622–2625. doi: 10.30534/ijatcse/2019/114852019
Mehta, K., Jain, S., Agarwal, A., & Bomnale, A. (2022). Road accident prediction using Xgboost. 2022 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), 50–56. doi: 10.1109/ICETCI55171.2022.9921367
Meocci, M., Branzi, V., Martini, G., Arrighi, R., & Petrizzo, I. (2021). A predictive pedestrian crash model based on artificial intelligence techniques. Applied Sciences, 11(23), 11364. doi: 10.3390/app112311364
Mor, N., Sood, H., & Goyal, T. (2020). Application of machine learning technique for prediction of road accidents in Haryana-A novel approach. Journal of Intelligent & Fuzzy Systems, 38(5), 6627–6636. doi: 10.3233/JIFS-179742
N, A. P., & Punithavalli, M. (2019). Prediction of road accident locations in road accident database by mining spatio-temporal association rules. ARPN Journal of Engineering and Applied Sciences, 14(12).
N, A. P., & Punithavalli, M. (2020). Bounded memory based frequent pattern growth approach with deep neural network and decision tree for road accident prediction. Indian Journal of Computer Science and Engineering, 11(5), 623–633. doi: 10.21817/indjcse/2020/v11i5/201105189
Ning, J., She, H., Zhao, D., Luo, D., & Wang, L. (2022). A road-level traffic accident risk prediction method. Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 45(2). doi: 10.13190/j.jbupt.2021-142
Olayode, O. I., Tartibu, L. K., & Okwu, M. O. (2020). Application of artificial intelligence in traffic control system of non-autonomous vehicles at signalized road intersection. Procedia CIRP, 91, 194–200. doi: 10.1016/j.procir.2020.02.167
Olugbade, S., Ojo, S., Imoize, A. L., Isabona, J., & Alaba, M. O. (2022). A review of artificial intelligence and machine learning for incident detectors in road transport systems. Mathematical and Computational Applications, 27(5), 77. doi: 10.3390/mca27050077
Oueida, S., Hossain, S. Q., Kotb, Y., & Ahmed, S. I. (2022). A fair and ethical healthcare artificial intelligence system for monitoring driver behavior and preventing road accidents. In Lecture Notes in Networks and Systems: Vol. 359 LNNS (pp. 431–444). doi: 10.1007/978-3-030-89880-9_33
P, C., & M, S. (2022). Road accident prediction and classification using machine learning. 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1–8. doi: 10.1109/MysuruCon55714.2022.9972671
Pachaivannan, P., Hemamalini Ranganathan, R., Navin Elamparithi, P., & Dhanagopal, R. (2020). Indian road conditions and accident risk predictions using deep learning approach – A review. 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), 199–202. doi: 10.1109/ICISS49785.2020.9316128
Panda, C., Mishra, A. K., Dash, A. K., & Nawab, H. (2023). Predicting and explaining severity of road accident using artificial intelligence techniques, SHAP and feature analysis. International Journal of Crashworthiness, 28(2), 186–201. doi: 10.1080/13588265.2022.2074643
Parthiban, D., Vijayan, D. S., Shadhil, M. H., Reshma, U., & Krishnan, R. (2022). Analysis of road accident with prediction model using machine learning algorithm in the region of Kerala. AIP Conference Proceedings, 2426, 020009. doi: 10.1063/5.0111414
Patil, J., Patil, V., Walavalkar, D., & Lobo, V. B. (2021). Road accident analysis and hotspot prediction using clustering. 2021 6th International Conference on Communication and Electronics Systems (ICCES), 763–768. doi: 10.1109/ICCES51350.2021.9489074
Paul, J., Jahan, Z., Lateef, K. F., Islam, M. R., & Bakchy, S. C. (2020). Prediction of road accident and severity of Bangladesh applying machine learning techniques. 2020 IEEE 8th R10 Humanitarian Technology Conference (R10-HTC), 2020-Decem, 1–6. doi: 10.1109/R10-HTC49770.2020.9356987
Popoola, O. M., Abiola, O. S., Odunfa, S. O., & Ismaila, S. O. (2019). Comparison of road traffic accident prediction models for two-lane highway integrating traffic and pavement condition parameters. Journal of Natural Sciences Engineering and Technology, 16(2), 1–10. doi: 10.51406/jnset.v16i2.1841
Prakash, T. D., & V, N. (2022). Comparative analysis using K-Nearest neighbour with artificial neural network to improve accuracy for predicting road accidents. 2022 International Conference on Edge Computing and Applications (ICECAA), 1092–1096. doi: 10.1109/ICECAA55415.2022.9936227
Radzuan, N. Q., Hassan, M. H. A., Abdul Majeed, A. P. P., Musa, R. M., Mohd Razman, M. A., & Abu Kassim, K. A. (2020). Predicting serious injuries due to road traffic accidents in Malaysia by means of artificial neural network. In Lecture Notes in Mechanical Engineering (pp. 75–80). doi: 10.1007/978-981-13-9539-0_8
Rajkumar, A. R., Prabhakar, S., & Priyadharsini, A. M. (2020). Prediction of road accident severity using machine learning algorithm. International Journal of Advanced Science and Technology, 29(6).
S, S., J, A. B., D, V., D, M. G., & Anusha. (2022). Road accident analysis and prediction model using a data mining hybrid technique. International Journal for Research in Applied Science and Engineering Technology, 10(7), 4300–4304. doi: 10.22214/ijraset.2022.45977
Sahu, S., Maram, B., Gampala, V., & Daniya, T. (2023). Analysis of road accidents prediction and interpretation using KNN classification model. In Lecture Notes in Networks and Systems (Vol. 490, pp. 163–172). doi: 10.1007/978-981-19-4052-1_18
Shaheen, M., Arshad, M., & Iqbal, O. (2020). Role and key applications of artificial intelligence & machine learning in transportation. European Journal of Technology, 4(1), 47–59. doi: 10.47672/ejt.632
Shaik, M. E., Islam, M. M., & Hossain, Q. S. (2021). A review on neural network techniques for the prediction of road traffic accident severity. Asian Transport Studies, 7, 100040. doi: 10.1016/j.eastsj.2021.100040
Singh, G., Pal, M., Yadav, Y., & Singla, T. (2020). Deep neural network-based predictive modeling of road accidents. Neural Computing and Applications, 32(16), 12417–12426. doi: 10.1007/s00521-019-04695-8
Sundari, M. R., Reddi, P., Murthy, K. S., & Sowmya, D. S. (2023). Fatality prediction in road accidents using neural networks. In Lecture Notes in Networks and Systems (Vol. 600, pp. 25–33). doi: 10.1007/978-981-19-8825-7_3
Tonni, S. I., Aka, T. A., Antik, M. M., Taher, K. A., Mahmud, M., & Kaiser, M. S. (2021). Artificial intelligence based driver vigilance system for accident prevention. 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), 412–416. doi: 10.1109/ICICT4SD50815.2021.9396916
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).
Whasphutthisit, T., & Jitsakul, W. (2022). Comparison of prediction models for road deaths on road network. 2022 14th International Conference on Knowledge and Smart Technology (KST), 137–142. doi: 10.1109/KST53302.2022.9729086
Wu, D., & Wang, S. (2020). Comparison of road traffic accident prediction effects based on SVR and BP neural network. 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA), 1150–1154. doi: 10.1109/ICIBA50161.2020.9277150
Xiao, Z., Tian, Y., Cao, D., & Zhang, Z. (2020). Road traffic risk safety prediction based on BP neural network. 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 527–533. doi: 10.1109/ITAIC49862.2020.9339063
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), 1576. doi: 10.1007/s42452-020-3125-1
Yeole, M., Jain, R. K., & Menon, R. (2022). Prediction of road accident using artificial neural network. International Journal of Engineering Trends and Technology, 70(2), 143–150. doi: 10.14445/22315381/IJETT-V70I2P217
Yeole, M., Jain, R. K., & Menon, R. (2023). Road traffic accident prediction for mixed traffic flow using artificial neural network. Materials Today: Proceedings, 77, 832–837. doi: 10.1016/j.matpr.2022.11.490
Yuan, M. H., & Wu, Y. F. (2022). A gray prediction method for economic loss of road traffic accidents based on Logistic model. Advances in Transportation Studies, 4(Special issue). doi: 10.53136/97912218027646
Yuan, Y., Yi, A., Wang, Y., & Chen, X. (2021). Research on technical model and method of urban road traffic accident and traffic conflict based on artificial intelligence. 2021 International Conference on Aviation Safety and Information Technology, 885–889. doi: 10.1145/3510858.3511416
Zhang, C., Li, Y., & Li, T. (2022). A road traffic accidents prediction model for traffic service robot. Library Hi Tech, 40(4), 1031–1048. doi: 10.1108/LHT-05-2020-0115
Zhao, F., Fu, L., Zhong, M., Cui, G., & Zheng, C. (2020). Traffic accident prediction on provincial road using fuzzy neural network. CICTP 2020, 3959–3968. doi: 10.1061/9780784482933.340
DOI: https://doi.org/10.37905/jji.v5i2.22037
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