Results 31 to 40 of about 210,556 (289)

A Two-Stage Decomposition-Reinforcement Learning Optimal Combined Short-Time Traffic Flow Prediction Model Considering Multiple Factors

Applied Sciences, 2022
Accurate short-term traffic flow prediction is a prerequisite for achieving an intelligent transportation system to proactively alleviate traffic congestion.
Dayi Qu, Kun Chen, Shaojie Wang, Qikun Wang   +3 more
doaj   +1 more source

A Short-Term Traffic Flow Reliability Prediction Method considering Traffic Safety [PDF]

Mathematical Problems in Engineering, 2020
With the rapid development and application of intelligent traffic systems, traffic flow prediction has attracted an increasing amount of attention. Accurate and timely traffic flow information is of great significance to improve the safety of transportation. To improve the prediction accuracy of the backward-propagation neural network (BPNN) prediction
Shaoqian Li, Zhenyuan Zhang, Yang Liu, Zixia Qin   +3 more
openaire   +2 more sources

Self-Organizing Traffic Flow Prediction with an Optimized Deep Belief Network for Internet of Vehicles [PDF]

, 2018
To assist in the broadcasting of time-critical traffic information in an Internet of Vehicles (IoV) and vehicular sensor networks (VSN), fast network connectivity is needed.
Anisi, MH, Doctor, F, Goudarzi, S, Kama, MN, Soleymani, SA   +4 more
core   +3 more sources

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 MapReduce-based nearest neighbor approach for big-data-driven traffic flow prediction

, 2016
In big-data-driven traffic flow prediction systems, the robustness of prediction performance depends on accuracy and timeliness. This paper presents a new MapReduce-based nearest neighbor (NN) approach for traffic flow prediction using correlation ...
Li, Huaqing, Li, Yantao, Wang, Binfeng, Xia, Dawen, Zhang, Zili   +4 more
core   +1 more source

Prediction feedback in intelligent traffic systems

, 2009
The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we studied dynamics of traffic flow with real-time information provided and
Arnott, Ben-Akiva, Biham, Bing-Hong Wang, Chowdhury, Chuan-Fei Dong, Friesz, Guan-Wen Wang, Helbing, Helbing, Helbing, Helbing, Kachroo, Lee, Lehmann, Mahmassani, Nagatani, Nagel, Paveri-Fontana, Prigogine, Rothery, Wagner, Wahle, Wang, Xiao-Yan Sun, Xu Ma, Yokoya   +26 more
core   +1 more source

Traffic Flow Prediction Using Machine Learning

Third International Conference “Transport for Today’s Society “, 2021
Abstract –The main objective of this research was to define and verify the methodology of predicting the volume and structure of traffic flows, based on the building and application of a supervised machine learning models. The proposed methodology was applied in the case study of the prediction of traffic flows on selected routes in the Republic of ...
Janković, Slađana, Mladenović, Dušan, Mladenović, Snežana, Zdravković, Stefan   +3 more
openaire   +1 more source

Real-time freeway network traffic surveillance: large-scale field testing results in Southern Italy [PDF]

, 2011
This paper reports on some large-scale field-testing results of a real-time freeway network traffic surveillance tool that has recently been developed to enable a number of real-time traffic surveillance tasks.
Coppola, P, Messmer, A, Nuzzolo, A, Papageorgiou, M, Tzimitsi, A, Wang, Y   +5 more
core   +2 more sources

Spatial Performance Indicators for Traffic Flow Prediction

Applied Sciences
Traffic flow prediction, crucial for traffic management, relies on spatial and temporal data to achieve high accuracy. However, standard performance metrics only measure the average prediction errors and overlook the spatiotemporal aspects. To address this gap, this study introduces three simple spatial key performance indicators (KPIs): Global Moran’s
Muhammad Farhan Fathurrahman, Sidharta Gautama   +1 more
openaire   +3 more sources

Short-term Demand Forecasting for Online Car-hailing Services using Recurrent Neural Networks

, 2019
Short-term traffic flow prediction is one of the crucial issues in intelligent transportation system, which is an important part of smart cities. Accurate predictions can enable both the drivers and the passengers to make better decisions about their ...
Bahrak, Behnam, Mahini, Hamid, Nejadettehad, Alireza   +2 more
core   +1 more source