Road Traffic Forecasting: Recent Advances and New Challenges

By Ibai Lana, Javier del Ser, M. Vélez, Eleni I. Vlahogianni. IEEE Intelligent Transportation Systems Magazine, 2018

310 citations recorded by the source corpus.

Subfields: Building and Construction, Transportation, Signal Processing

View Paper: https://www.semanticscholar.org/paper/2126015a0c160795c36ed51e64c66a98bc57f188

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Baocai Yin
2. Nizar Bouguila
3. Saeed Rahmani
4. Asiye Baghbani
5. Zachary Patterson

In Transportation

1. Baocai Yin
2. Nizar Bouguila
3. Saeed Rahmani
4. Asiye Baghbani
5. Zachary Patterson

In Signal Processing

1. Damminda Alahakoon

Citations in the corpus

• Online Incremental Machine Learning Platform for Big Data-Driven Smart Traffic Management (2019, background): “Digital Object Identifier 10.1109/TITS.2019.2924883 Things (IoT), sensor networks and social media has surpassed traditional means of collecting data, by creating voluminous and continuous streams of real-time data.”
• Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions (2021, methodology): “[6] and [7] summarized relevant models based on classical methods and some early deep learning methods.”
• Graph Neural Networks for Intelligent Transportation Systems: A Survey (2023, background): “…traffic characteristics (such as speed, flow, or density) in a short or long future time horizon in order to aid different ITS applications [22], such as advanced traffic management and control systems to travelers’ information systems and shared, connected, and autonomous mobility systems…”