Results 21 to 30 of about 359,562 (287)

Apparatus and method for congestion control in high speed networks [PDF]

, 2004
An adjustable bit rate (ABR) feedback control scheme is provided where the effects of multiloop delays and high priority traffic transmission are built into the control model. The data traffic is filtered by a low pass filter.
Li, San-Qi, Sigarto, Samuel
core   +1 more source

Attention-Based Gated Recurrent Graph Convolutional Network for Short-Term Traffic Flow Forecasting

Journal of Mathematics, 2023
Traffic flow prediction is the basis of dynamic strategies and applications of intelligent transportation systems (ITS). Accurate traffic flow prediction is of great practical significance in alleviating road congestion and reducing urban road traffic ...
Ping Lou, Zihao Wu, Jiwei Hu, Quan Liu, Qin Wei   +4 more
doaj   +1 more source

Road occupancy prediction of traffic participants [PDF]

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013
We predict the road occupancy of traffic participants for collision avoidance systems. The occupancy sets are computed for consecutive time intervals and contain all reachable positions of traffic participants in compliance with a proposed dynamic model.
Matthias Althoff, Daniel Hess, Florian Gambert   +2 more
openaire   +2 more sources

Augmentation of Deep Learning Models for Multistep Traffic Speed Prediction

Applied Sciences, 2022
Traffic speed prediction is a vital part of the intelligent transportation system (ITS). Predicting accurate traffic speed is becoming an important and challenging task with the rapid development of deep learning and increasing traffic data size. In this
Adnan Riaz, Hameedur Rahman, Muhammad Ali Arshad, Muhammad Nabeel, Affan Yasin, Mosleh Hmoud Al-Adhaileh, Elsayed Tag Eldin, Nivin A. Ghamry   +7 more
doaj   +1 more source

Attention-based spatio-temporal graph convolutional network considering external factors for multi-step traffic flow prediction

Digital Communications and Networks, 2022
Traffic flow prediction is an important part of the intelligent transportation system. Accurate multi-step traffic flow prediction plays an important role in improving the operational efficiency of the traffic network. Since traffic flow data has complex
Jihua Ye, Shengjun Xue, Aiwen Jiang
doaj   +1 more source

Integrating Pattern Features to Sequence Model for Traffic Index Prediction

International Journal of Computational Intelligence Systems, 2021
Intelligent traffic system (ITS) is one of the effective ways to solve the problem of traffic congestion. As an important part of ITS, traffic index prediction is the key of traffic guidance and traffic control.
Yueying Zhang, Zhijie Xu, Jianqin Zhang, Jingjing Wang, Lizeng Mao   +4 more
doaj   +1 more source

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

Set-Based Prediction of Traffic Participants Considering Occlusions and Traffic Rules [PDF]

IEEE Transactions on Intelligent Vehicles, 2021
Provably safe motion planning for automated road vehicles must ensure that planned motions do not result in a collision with other traffic participants. This is a major challenge in autonomous driving, since the future behavior of other traffic participants is not known and since traffic participants are often hidden due to occlusions. In this work, we
Markus Koschi, Matthias Althoff
openaire   +2 more sources

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