Results 31 to 40 of about 361,441 (286)

Traffic Anomaly Prediction System Using Predictive Network [PDF]

Remote Sensing, 2022
Anomaly anticipation in traffic scenarios is one of the primary challenges in action recognition. It is believed that greater accuracy can be obtained by the use of semantic details and motion information along with the input frames. Most state-of-the art models extract semantic details and pre-defined optical flow from RGB frames and combine them ...
Waqar Riaz, Chenqiang Gao, Abdullah Azeem, null Saifullah, Jamshaid Bux, Asif Ullah   +5 more
openaire   +2 more sources

Traffic Accident’s Severity Prediction: A Deep-Learning Approach-Based CNN Network

IEEE Access, 2019
In traffic accident, an accurate and timely severity prediction method is necessary for the successful deployment of an intelligent transportation system to provide corresponding levels of medical aid and transportation in a timely manner.
Ming Zheng, Tong Li, Rui Zhu, Jing Chen, Zifei Ma, Mingjing Tang, Zhongqiang Cui, Zhan Wang   +7 more
doaj   +1 more source

Freeway Traffic OscillationsObservations and Predictions [PDF]

, 2002
Freeway traffic was observed over multiple days and was found to display certain regular features. Oscillations arose only in queues; they had periods of several minutes; and their amplitudes stabilized as they propagated upstream. They propagated at a nearly constant speed of about 22 to 24 kilometers per hour, independent of the location within the ...
Mauch, Michael, Cassidy, Michael J.
openaire   +3 more sources

Exploiting road traffic data for very short term load forecasting in smart grids [PDF]

, 2014
If accurate short term prediction of electricity consumption is available, the Smart Grid infrastructure can rapidly and reliably react to changing conditions.
Aparicio, J, Arzig, K, Develder, Chris, Essl, A, Mediger, M, Rosca, J   +5 more
core   +1 more source

In-Depth Insights into the Application of Recurrent Neural Networks (RNNs) in Traffic Prediction: A Comprehensive Review

Algorithms
Traffic prediction is crucial for transportation management and user convenience. With the rapid development of deep learning techniques, numerous models have emerged for traffic prediction.
Yuxin He, Ping Huang, Weihang Hong, Qin Luo, Lishuai Li, Kwok-Leung Tsui   +5 more
doaj   +1 more source

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

, 2018
Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satisfy the requirements of mid-and-long term prediction tasks and often neglect ...
Yin, Haoteng, Yu, Bing, Zhu, Zhanxing
core   +1 more source

A system for learning statistical motion patterns [PDF]

, 2006
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways.
Fu, Z., Hu, W., Maybank, Stephen J., Tan, T., Xiao, X., Xie, D.   +5 more
core   +2 more sources

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

, 2014
Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and of human mobility.
Ercsey-Ravasz, Mária, González, Marta C., Ren, Yihui, Toroczkai, Zoltán, Wang, Pu   +4 more
core   +1 more source

T-LSTM: A Long Short-Term Memory Neural Network Enhanced by Temporal Information for Traffic Flow Prediction

IEEE Access, 2019
Short-term traffic flow prediction is one of the most important issues in the field of intelligent transportation systems. It plays an important role in traffic information service and traffic guidance.
Luntian Mou, Pengfei Zhao, Haitao Xie, Yanyan Chen   +3 more
doaj   +1 more source

Scalable Deep Traffic Flow Neural Networks for Urban Traffic Congestion Prediction

, 2017
Tracking congestion throughout the network road is a critical component of Intelligent transportation network management systems. Understanding how the traffic flows and short-term prediction of congestion occurrence due to rush-hour or incidents can be ...
Elmasri, Ramez, Fouladgar, Mohammadhani, Ghaderi, Amir, Parchami, Mostafa   +3 more
core   +1 more source