Results 1 to 10 of about 2,028,364 (331)
Accident Detection and Alert System
International Journal of Advanced Research in Science, Communication and Technology, 2023 One of the primary causes of car accidents is speed. Many lives could have been saved if emergency personnel had received accident information in time and arrived. This project is about an accident detection system that uses several components and alerts
Prof. M. K. Pawar +4 more
semanticscholar +1 more source
Traffic Accident Severity Prediction Based on Random Forest
Sustainability, 2022 The prediction of traffic accident severity is essential for traffic safety management and control. To achieve high prediction accuracy and model interpretability, we propose a hybrid model that integrates random forest (RF) and Bayesian optimization (BO)
Ming Yan, Yindong Shen
semanticscholar +1 more source
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning [PDF]
ACM Multimedia, 2020 Traffic accident anticipation aims to predict accidents from dashcam videos as early as possible, which is critical to safety-guaranteed self-driving systems.
Wentao Bao, Qi Yu, Yu Kong
semanticscholar +1 more source
RiskOracle: A Minute-level Citywide Traffic Accident Forecasting Framework [PDF]
AAAI Conference on Artificial Intelligence, 2020 Real-time traffic accident forecasting is increasingly important for public safety and urban management (e.g., real-time safe route planning and emergency response deployment).
Zhengyang Zhou +4 more
semanticscholar +1 more source
Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction
De Computis, 2021 Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses.
Daniel Santos +3 more
semanticscholar +1 more source
Unsupervised Traffic Accident Detection in First-Person Videos [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2019 Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems.
Yu Yao +4 more
semanticscholar +1 more source
Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights [PDF]
SIGSPATIAL/GIS, 2019 Reducing traffic accidents is an important public safety challenge, therefore, accident analysis and prediction has been a topic of much research over the past few decades.
Sobhan Moosavi +4 more
semanticscholar +1 more source
Accident Analysis and Prevention
, 2020 This paper introduces a framework for modelling the cyclist’s comfort zone. Unlike the driver’s comfort zone, little is known about the cyclist’s.
Murat Darçın
semanticscholar +1 more source
Knowledge Discovery and Data Mining, 2018 Predicting traffic accidents is a crucial problem to improving transportation and public safety as well as safe routing. The problem is also challenging due to the rareness of accidents in space and time and spatial heterogeneity of the environment (e.g.,
Zhuoning Yuan, Xun Zhou, Tianbao Yang
semanticscholar +1 more source