This paper aims to study, compare and analyse the performance of six major machine learning techniques to better understand the occurrence of traffic accidents. The methods considered are Decision Trees, Support Vector Machines, Nave Bayes, Random Forest, K-Nearest Neighbour and Logistic Regression. ...
Machine LearningAccident PredictionSurveyClassification TechniquesRecent studies have predicted that in 2030, traffic accidents will be the fifth leading cause of death worldwide. The root cause of traffic accidents is hard toVenkat, ArunM, Gokulnath...
Predictive analytics of road accidents in Oman using machine learning approach The paper addresses an in-depth analysis that identifies the contributory factors, causes behind the road crashes and the quantification of the factors that... G Narasimhan,BG Ephrem,S Cheriyan,... - International Confere...
Machine Learning Techniques for Fatal Accident Prediction Ensuring public safety on our roads is a top priority, and the prevalence of road accidents is a major concern. Fortunately, advances in machine learning a... H Zermane,A Zermane,MZM Tohir - 《Acc Journal》 被引量: 0发表: 2024年 Ev...
Accident Analysis & Prevention, 129, 382–389. Google Scholar Breiman, 2001 L. Breiman Random forests Machine Learning, 45 (1) (2001), pp. 5-32 Google Scholar Cafiso et al., 2010 S. Cafiso, A. Di Graziano, G. Di Silvestro, G. La Cava, B. Persaud Development of comprehensive ...
Accident; Analysis and Prevention, 38 (1) (2006), pp. 185-191, 10.1016/j.aap.2005.09.007 View PDFView articleView in ScopusGoogle Scholar Jahangiri and Rakha, 2015 A. Jahangiri, H.A. Rakha Applying Machine Learning Techniques to Transportation Mode Recognition Using Mobile Phone Sensor Data ...
This paper mainly focuses on the task of detection and classification of surface road damages using an Android device. Other challenges may include introducing new features such as Severity analysis, Pixel-level damage analysis for covering a wider range of surface road damages. Multiple eval...
Akhand MdN, Das S, Hasan M (2022) Traffic density estimation using transfer learning with pre-trained INCEPTIONRESNETV2 Network. Machine Intell Data Sci Applications 132:363–375 Article Google Scholar Gawali TK, Deore SS (2023) Survey on spatio-temporal transportation using deep convolution netw...
Analyzing the transition from two-vehicle collisions to chain reaction crashes: a hybrid approach using random parameters logit model, interpretable machine learning, and clustering Accident Analysis & Prevention, 202 (2024) Google Scholar [25] S. Dong, A. Khattak, I. Ullah, J. Zhou, A. Hussai...
Accident analysis for construction safety using latent class clustering and artificial neural networks Journal of Construction Engineering and Management, 146 (3) (2020), p. 04019114 View in ScopusGoogle Scholar Bengio, 2012 Y. Bengio Practical recommendations for gradient-based training of deep architec...