Traffic flow prediction based on deep learning in internet of vehicles
In Internet of Vehicles (IoV), accurate traffic flow prediction is helpful for analyzing road
condition and then timely feedback traffic information to managers as well as travelers …
condition and then timely feedback traffic information to managers as well as travelers …
A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data
There are many systems to evaluate driving style based on smartphone sensors without
enough awareness from the context. To cover this gap, we propose a new system namely …
enough awareness from the context. To cover this gap, we propose a new system namely …
Estimation of missing values in heterogeneous traffic data: Application of multimodal deep learning model
With the development of sensing technology, a large amount of heterogeneous traffic data
can be collected. However, the raw data often contain corrupted or missing values, which …
can be collected. However, the raw data often contain corrupted or missing values, which …
Pattern sensitive prediction of traffic flow based on generative adversarial framework
Traffic flow prediction is one of the most popular topics in the field of the intelligent
transportation system due to its importance. Powered by advanced machine learning …
transportation system due to its importance. Powered by advanced machine learning …
Two-stream multi-channel convolutional neural network for multi-lane traffic speed prediction considering traffic volume impact
Traffic speed prediction is a critically important component of intelligent transportation
systems. Recently, with the rapid development of deep learning and transportation data …
systems. Recently, with the rapid development of deep learning and transportation data …
Revealing heterogeneous spatiotemporal traffic flow patterns of urban road network via tensor decomposition-based clustering approach
Understanding the complex heterogeneity of traffic flow for the road network is of great
importance to relieving traffic congestion and designing traffic control strategies. This study …
importance to relieving traffic congestion and designing traffic control strategies. This study …
Exploratory framework for analysing road traffic accident data with validation on Gauteng province data
T Makaba, W Doorsamy, BS Paul - Cogent Engineering, 2020 - Taylor & Francis
Exploratory data analysis (EDA) is often a necessary task in uncovering hidden patterns,
detecting outliers, and identifying important variables and any anomalies in data …
detecting outliers, and identifying important variables and any anomalies in data …
Real-Time Traffic Flow Prediction using IoT-Driven Machine Learning
SS Waseem, H Sattar, S Ramzan, N Nasir… - Journal of Computing & …, 2024 - jcbi.org
Road accidents result in deaths, infections, and many injuries. The main causes of these
accidents are traffic congestion, road blockages, and traffic anomalies. Several factors, such …
accidents are traffic congestion, road blockages, and traffic anomalies. Several factors, such …
A Study on the Compression and Major Pattern Extraction Method of Origin-Destination Data with Principal Component Analysis
Origin-destination data have been collected and utilized for demand analysis and service
design in various fields such as public transportation and traffic operation. As the utilization …
design in various fields such as public transportation and traffic operation. As the utilization …